jssh vol. 11 (1) mar. 2003

ISSN: 0128-7702

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VOLUME 11 NO. 1MARCH 2003

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Pertanika Journal of Social Science and Humanities

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Pertanika Journal of Social Science & Humanities

Volume 11 Number 1 (March) 2003

Contents

Residential Satisfaction and Social Integration in Public Low Cost 1Housing in Malaysia - Ahmad Hariza Hashim

Kreativiti Guru Pendidikan Seni - Chua Yan Piaw, Sharifah Md. Nor, 11Nairn b. Mohd & Wan Zah Wan Alt

Ekonomi Negeri Kelantan dari Perspektif Analisis Shift-Share Wilayah 19— Zakariah Abdul Rashid

Predictability of ASEAN-5 Exchange Rates in the Post-Crisis Era — Liew 33Khim Sen & Ahmad Zubaidi Baharumshah

Is MYR/USD a Random Walk? New Evidence from the BDS Test - K.P. 41Lim, M. Azali & H.A, Lee

Organizational Creative Climate & Learning Organization: Factors 51Contributing Towards Innovation Within an Organization - AzahariIsmail, Meriam Ismail, Bahaman Abu Samah, Shamsuddin Ahmad,Khairuddin Idris & Jegak Uli

Perbandingan Pencapaian Kognitif, Afektif dan Kompetensi Pelajar 69Program Keusahawanan Remaja yang Berlainan Latar BelakangKeluarga - Norasmah Hj. Othman & Zaidatol Akmaliah Lope Pihie

Status Program Pembelajaran di Kalangan Saudara Baru: Satu Kajian 81Kes di Negeri Melaka - Mohd Azmi Mat Sah & Maimunah Ismail

Impact of Credict Risk on Farm Planning in Chiang Mai Valley, 97Thailand - Zainal Abidin Mohamed, Pichit Thani & Eddie Chiew FookChong

Pertanika J. Soc Sci. & Hum. 11(1): 1-10 (2003) ISSN: 0128-7702© Universiti Putra Malaysia Press

Residential Satisfaction and Social Integration inPublic Low Cost Housing in Malaysia

AHMAD HARIZA HASHIMDepartment of Resource Management and Consumer Studies

Faculty of Human Ecology, Universiti Putra Malaysia43400 UPM Serdang, Selangor, Malaysia

Keywords: Public low cost housing, residential satisfaction, residential attachments, communityinvolvement, social integration

ABSTRAKKajian ini menilai perkaitan di antara integrasi sosial dan kepuasan perumahan di kalanganpenghuni rumah kos rendah di Malaysia. Dua kawasan bandar dan luar bandar di Selangor telahdipilih dalam kajian ini dan melibatkan seramai 472 responden. Responden ini terdiri daripada58% Melayu, 22% China dan 20% India. Hasil kajian mendapati bahawa penghuni yangmempunyai kejelekitan tempat tinggal yang kuat serta tahap kepuasan yang tinggi adalah lebihaktif terlibat dengan aktiviti komuniti di kawasan tempat tinggal mereka. Kajian juga menunjukkanbahawa faktor seperti keadaan struktur rumah yang rosak, persekitaran sosial dan fizikal yangtidak baik memberi kesan kepada integrasi sosial di kawasan kejiranan. Oleh itu satu projekperumahan yang dirancang dengan mengambil kira aspek kepuasan perumahan adalah pentinguntuk dipertimbangkan kerana dapat membantu proses sosialisasi penghuninya ke dalam komuniti.

ABSTRACTThe research examined the relationship between social integration and residential satisfaction ofresidents in low cost housing in Malaysia. Two urban and non-urban areas in Selangor werechosen for this study involving 472 respondents. 58% of the respondents are Malay, 22% Chineseand 20% Indians. It was shown that residents with strong residential attachments and high levelsof satisfaction are actively involved in the community activities held in their neighbourhood. Itwas also found that factors such as default in the physical structures of the house and poor socialand physical environments could affect the social integration in the neighbourhood. Thereforeproperly planned residential projects with attention given towards residential satisfaction need tobe considered because they can help foster the process of socializing people into communities.

INTRODUCTIONOne of the important factors that will affectsocial integration is the resident's feeling ofsatisfaction with his residence. Satsangi andReams (1992) stated that the satisfaction scorein housing studies has been deemed as anindicator of service quality or organisationalsuccess and effectiveness. Satisfaction has alsobeen heralded as an important means of listeningto consumers, and thus a necessary componentof organisations becoming more demand-responsive. Pacione (1990:18) points out thatresidents who cannot attain the desired level ofsatisfaction through modification of their current

setting, will suffer 'residential stress', and thismay eventually lead to migration. Basset andShort (1980:188), said that the provision ofhousing is not only a quantitative problem, butalso a qualitative problem in the sense that:a) housing contributed to the reproduction ofdifferent components of labour power withdifferent incomes and housing needs, andb) housing also contributed to the reproductionof social relations through correspondencebetween signs of residential status and positionwithin a social hierarchy, based on class divisions.

Drakakis-Smith (1980:305) also agrees withthe above ideas of using housing to build up or

Ahmad Hariza Hashim

to control the community, either by helping toencourage social interaction between differentsocial classes or by dispersing them into variouscommunities and interacting among themselves.This is because, from numerous studies, it wasshown that a strong correlation exists betweenbad housing and disease, delinquency, and otherpersonal and community disorders. Properlyplanned residential projects have been seen tohelp foster good relationships among people inthe community and also help raise theiraspirations. In addition to its high social utility,better housing will contribute to political stabilityby moderating people's impatience with the slowtempo of improvement in their living conditions.

Those who are against total heterogeneity,for example Gans (1968:129) argued that peoplederived more satisfaction from their residentialarea when they have neighbours who have similarbackgrounds and interests. The argument is thatpeople tend to choose friend on the basis ofsimilarities in background such as age and socio-economic level; values, such as those with respectto privacy or child-rearing; and interests, such asleisure-activity preferences. This finding suggeststhat social relationships are influenced andexplained by people's homogeneity with respectto a variety of characteristics. Other research hasshown that having neighbours similar to oneselfin terms of various characteristics is directlyrelated to satisfaction with the residentialenvironment (Weideman and Anderson1985:163). Cohen (1986:115) argues that "theattitudes of people toward their neighbourhoodcould serve as an indication of the degree towhich the neighbourhood is measured byattitudes towards it and particularly by attitudesthat reflect residential satisfaction from a dwellingand its principal surroundings". Therefore itcan be assumed that a neighbourhood wheremost of the population is satisfied with itsresidential conditions, is a stable neighbourhood.However, a neighbourhood where the majorityof its population is dissatisfied with the residentialconditions, is a less stable neighbourhood thatdoes not serve as a protection against thepressures of social change. A less stableneighbourhood is a place where its populationdoes not possess an informal social network andthis indicates that those who lived there are notprotected against the pressures of the widersociety to which they belong. It could well serveas an indication of alienation, anomie, and

apathy. In another study done in the Republicof Ireland, it was found that anomie wassignificantly related to dissatisfaction withneighbours. This is not surprising given thatanomie measures alienation from society andthe lack of social integration (Davies and Fine-Davies 1981:483). In conclusion, it can be saidthat people who are satisfied with their residentialarea will also be satisfied with their neighbours.This is then followed by an attachment to theneighbourhood, creating a strong social cohesionin the neighbourhood. This is because residentialareas serve as an area for social interaction, anagent for socialization, a component of socialstatus, a source of opportunities and services, anenvironment for self-fulfillment, and a protectedarea for inhabitants (Menahem and Spiro1989:29).

Therefore in this study 'residentialsatisfaction' encompasses both housingsatisfaction and neighbourhood satisfaction. Thefocus is on satisfaction because:1) A failure to meet low cost housing targets

means that housing demand cannot besatisfied. This, in turn, means that choice islimited. The government allocation policiesdetermine which house an applicant gets,and such restrictions may affect residentialsatisfaction.

2) Low cost housing implies a lower standardof housing. Compact design and lowerquality material may be used. This mightaffect the satisfaction of the residents (Peng1981:49-50) who discussed the poor qualityof housing construction, especially in lowcost housing. In trying to provide affordablehousing the standard of houses is alwaysbeing compromised. The finishing of thehouses, the material used, the design andsize of houses are among the majorcomplaints received about low cost housing.Other than the physical aspects, people whoare allocated low cost housing have no sayin choosing who their neighbours are, andif it involves squatters' allocation then thelocation of the area is also identified by theauthorities. All these factors influencepeople's evaluation of their housing andneighbourhood and will also influencepeoples' behaviour, especially in theirrelationships with others in the community.

3) Satisfaction is always being associated withthe residential environment, and is especially

PertanikaJ. Soc. Sci. & Hum. Vol. 11 No. 1 2003

Residential Satisfaction and Social Integration in Public Low Cost Housing in Malaysia

used as a predictor for migratory or movingbehaviour (Marans and Rodgers 1975). Withregard to mobility, in a community wherethe residents keep changing due to peopleoften moving in and out of the area, theintegration in the community will be lowcompared with an area where the residentsare less mobile. New residents take time toadjust to the new environment and tosocialise with the community. Therefore theassumption is that if satisfaction is shown toinfluence peoples' thoughts about movingor moving behaviour then it will alsoinfluence social integration in thecommunity.

The other important factor is ethnic groups.A study done in Singapore shows that peoplefrom different ethnic backgrounds live togetherpeacefully and harmoniously in public estates(Tai 1988). Tai also found out that living togetherbrings a greater opportunity for inter-ethniccontacts and living together in the sameresidential area harmoniously. Therefore, theinteractions and acceptance among the majorethnic groups living closely together in a housingarea is an important variable to study.

METHODOLOGYIn this paper the term 'estate' was used duringall interviews with the residents. In order toensure that the term 'estate ' would beunambiguous, the name of the housing estatewas mentioned when ever referring to theneighbourhood. For example, Taman Shah Java'was used in referring to the neighbourhood.Taman' here means housing estate, while 'ShahJaya' is the name of the estate. As for socialintegration, 'having more friends here ascompared to the previous place' is used asmeasurement (St. John, Austin and Baba 1986).A household was defined as two adults with orwithout children living together.

In terms of location, Selangor was chosenbecause of its high urbanization rate and becauseit is also among the earliest states that built lowcost houses. The other reason is that theproportion of the three major ethnic groups inSelangor is quite similar to that of Malaysia.There are nine administrative districts inSelangor. They are Gombak, Klang, KualaLangat, Kuala Selangor, Petaling, Sabak Bernam,Sepang, Ulu Langat and Ulu Selangor. For the

purposes of the research, these districts weregrouped into two categories: those surroundingKuala Lumpur (Malaysia's capital city) and thosefurther away. One district from each categorywas selected for this study. The housing estateschosen in Ulu Langat are located in or nearKajang, a town situated 20 km south of KualaLumpur. The three housing estates chosen inKuala Langat are in or near Banting town, located60 km southwest of Kuala Lumpur.Comparatively, Ulu Langat has a higherpopulation than Kuala Langat. In terms of ethniccomposition, there is not much differencebetween the two districts.

From each district a list of public low costhousing programmes was obtained. From thelist, housing estates which were less than fiveyears old and those with less than 100 houseswere removed before the random sample wasmade. From those remaining, three public lowcost housing estates in each of the two districtswere chosen randomly. For every housing estate,respondents were chosen at random by usingsystematically random sampling. The totalnumber of respondents involved in the surveysis shown in Table 1.

The first part of this analysis examinesdescriptively the household and housingcharacteristics of the respondents. The paperalso discusses the relationship between residentialsatisfaction and social integration. It then looksat whether the sets of structural variablessignificantly add to the social integration, overand above satisfaction. If indeed these variablesonly affect social integration as they affectsatisfaction, their inclusion will not addsignificantly to the fit of the model. Finally,both sets of structural variables are addedsimultaneously, and test the fit of the completemodel against each of the less inclusive models.At each step in the analysis, the relativemagnitude and direction of the effects of variousspecific factors are evaluated by looking at thelogistic regression coefficient (Landale and Guest1985).

Household and Housing CharacteristicsOf the total sample of 472 households, 58%were Malay, 22% were Chinese and 20% Indians.All the Malays in the survey are Muslim, with55% male, 31% between 41 to 50 years of age.52% received less than six years of formaleducation and 25% work in the public sector


Ahmad Hariza Hashim

TABLE 1Total number of respondents

Ethnic Groups District

Ulu

n

1565036242

Langat

%

642115100

Kuala

n

1185359232

Langat

%

51232599

Total

n

27410395472

%

582220100

MalaysChineseIndiansTotal

with monthly incomes of RM500 or less, whilethe wives are mostly housewives. 39% have oneor more children still living with them.

Most of the Chinese households (80%) areBuddhist but other religions are also represented.There are more female respondents as thehusbands were out at work when the interviewwas done. The Chinese surveyed are within theage range of 31 to 50 years and nearly half(45%) have received more than nine years offormal education. This is considerably higherthan for both the Malay and the Indianrespondents. In terms of husbands' occupations,50% are self-employed, in contrast to 14% Malayand 5% Indians. Perhaps not surprisingly, quitea high proportion of Chinese (56%) earn morethan RMl,000 per month. 68% have three ormore children living with them, again higherthan for the other two groups.

Most Indians (88%) are Hindu and themajority of the Indian respondents are male. Aswith the other ethnic groups, the majority (58%)belongs to the age group of 31 to 50 years. 57%received nine years or less of formal education.30% of the husbands work in the public sectorand 45% in the private sector. Householdincomes tend to be lower than those of Chineserespondents but higher than those of the Malays.

For housing characteristics, the majority ofthe respondents are homeowners (71%). Beforemoving here many of them rented a house(44%) and the rest either lived with their ownfamilies or in quarters provided by theiremployers. The house that they lived in at presentis a two-bedroom terrace house, with onebathroom and a separate toilet. There is onlyone small kitchen available and shared space forthe lounge and dining room.

EMPIRICAL RESULTS

The results of the logistics regression arepresented in Tables 2 and 3. Table 2 shows thatindependent variables which are significant asshown in column 1, Table 2 were omitted inturn to see its effect and significance on thesocial integration value in the neighbourhoodthrough the chi-square statistics (see column 2to column 7, Table 2). The results are discussedin detail below.

Individual and Household CharacteristicsIt is expected that individual and householdcharacteristics would influence social integration.Results show that only the age of respondents isconsistently significant at least at p<0.05. To bespecific, only residents in the age group of 30and below show significance at p<0.05. Thenegative coefficient for age indicates thatresidents who are 30 years and below were onefifth as likely as residents older than 30 years tointegrate into the community (see column 1,Table 2). The other variables did not show anysignificant relationship at the level of 0.05 (Table2). In the process of integration, especially inmaking new friends, occupational status,educational attainment, and income areimportant factors (Jackson 1977:59). Carey andMapes (1972:14-15) also point out that age, lifestage, and job status are among the characteristicsof individuals that are shown to affect the visitinglevel among the neighbours. Since this studyfocussed on the residents of low cost housing,these criteria are not so important, and are notmajor criteria influencing social integration. Thereason for this is that residents living in publiclow cost housing tend to be similar in terms ofeducational attainment, occupational status andincomes, because the allocation policy for publichousing is for people with incomes of RM750 or

PertanikaJ. Soc. Sci. 8c Hum. Vol. 11 No. 1 2003


ColumnVariable

Residential EducationalAttainment

5 years and below6 to 10 years

Household Incomes(RM)750 and below751 to 1250

No. of Children LivingTogether

1 to 23 to 45 and above

Age of Respondents30 and below31 to 45 years

Length of ResidenceIn Years

5 years and below6 to 10 years

Ethnic Group

Location

Residential SatisfactionHousing satisfactionNeighbourhoodSatisfaction

ResidentialAttachments

Tenancy Status

Constant

(-2) Log likelihoodd.f.

Chi-square valued.f.

Logistic

1

-0.18020.3450

0.01150.2596

-0.62530.28500.0894

-0.5921*-0.0678

-0.27180.0221

0.7124**

TABLE 2regression for social i

2

-0.6130**-0.0110

0.7153**

0.8669*** 0.8919***

0.7082**

0.9215**

0.6030*

-0.1118

-3.5875

0.6566**

0.8539**

0.4835

-3.9425

integration

model3 4

-0.7958**0.1240

0.6390**

1.0145***

0.4520

-2.4744

479.686 497.282 530.533379 394 42070.650 59.968 59.42717 7 5

-0.5556*0.0375

0.8068**

0.5703*

0.6700*

0.5861*

-2.7119

510.587397

49.8596

5

-0.5653-0.0639

0.6077**

0.8510***

0.6637**

1.0796***

0.4360

-2.2061

511.084 i396

46.1676

6

0.6702**

0.8719***

0.5963*

0.7689*

0.6920**

-3.0973

511.084396

46.165

7

-0.6940**-0.0040

0.7666**

0.6334**

0.8585**

3.0973

500.897395

56.3546

p<0.05, ** p<0.01, *** P<0.001

less per month. This is the reason why thesevariables are not significant in this study.

Location

It was assumed that the more urbanised thearea, the less integrated its community, as therelationships were more formal and neighbour-

hood functions were subsumed by other societalinstitutions, while the less urbanised areassuggested a high degree of social integrationand interaction among their residents. Resultsshow that location is consistently significant, tothe extent that it manifests the strongestrelationship with social integration at level 0.001,


Ahmad Hariza Hashim

except in column 4 when ethnic group is leftout (Table 2). The significance of this variableis also evident from the fact that its omissionfrom the equation reduces the chi-square statisticand the fit of the equation substantially. Thechi-square statistic falls from 59.97 (column 2,Table 2) to 43.66 (column 5, Table 2). Thissignificance indicates that residents in Ulu Langat(an area which is more urbanised and is alsosituated nearer to the business centre, KualaLumpur, the capital city of Malaysia) showshigher integration compared to Kuala Langat(an area with small towns, situated further awayfrom Kuala Lumpur). The table also shows thatresidents of public low cost housing in UluLangat are 2.4 times (eO8919=2.4, see column 2,Table 2) more likely to integrate into theirneighbourhood than residents in public low costhousing in Kuala Langat. Therefore thesefindings do not agree with Wirth's (1938) theorywhich argued that the primary relationshipbetween the residents has changed to a moreformal or secondary relationship as a result ofurbanisation. The results of this study haveparticular implications for social integrationprogrammes. Many of the programmes to induceamong members in a community have beenfocussed in urban areas, and the results indicatethat these programmes have been relativelysuccessful.

Ethnic Groups

Ethnic groups prefer to stay in areas where theyare the majority because they feel more secureand are more likely to integrate with each otherin this kind of community (Nuzhat Ahmad 1993).The results from this study show that theassumption holds true for the ethnic groups inMalaysia. In Table 2, the ethnic group's variableis consistently significant at p <0.01. This impliesthat the Malays are more fully integrated in thecommunity as compared to other ethnic groups,and this is not surprising as the majority of diepopulation living in public low cost housing isMalay. This is due to the housing allocationratio set up by the government for low costhousing. The ratio is 7:2:1, 7 for Malays, 2 forChinese and 1 for Indians. From the table it canbe seen that the Malays in public low cost housingare 2 times (ea715s=2.0, see column 2, Table 2)more likely than the other ethnic groups tointegrate into the community. In addition, theoccupation of the respondents also shows that

the Malays, many of whom work in the publicsector, spend more time in the neighbourhoodcompared to the Chinese, many of whom areoccupied in their businesses. Normal workinghours for public servants are from 8.00 in themorning until 4.30 in the afternoon. Those whoare involved in business or private firms willtend to spend more time at work. The Malaysalso participate more in local organisations ascompared to the other ethnic groups. All thesefactors influence the Malays' level of integrationin the community especially among themselves,positively. This is not surprising because as statedby Mohd Razali (1992) the ethnic groups inMalaysia are more comfortable in their ownethnic groups and they sometimes, especiallythe Malays, demand that they should be allocatedtogether in a block or area with their own ethnicgroup. However, he also stated that the Malaycan more easily accept other ethnic groups to bewith their community as compared to Chineseor Indians.

Community Attachments

Oropesa (1989) argued that there are residentswho participate in local organisations because ofpersonal, social or economic interests.Specifically, residents who own valuable propertyhave an incentive to participate because of theireconomic interest in the state of the propertymarket. Homeownership is seen as the mostsecure form of housing tenure. One of thebenefits claimed for homeownership is that itcan enhance democracy through creatingincentives for greater community involvementand social attachment (Carlson 1989). Saunders(1990) also argued that homeowners have higherincentives to participate in local organisations.This would suggest that the same argument canbe used for social integration where it might beassumed that homeowners will integrate moreinto the community than tenants. But this is notthe case in this study. Table 2 shows that tenureis not a significant factor in social integration (atlevel 0.05). Homeownership or renting makesno difference to social integration among theresidents of the low cost housing sector in Selangor.

Length of residence has also been regardedas a good indicator for social integration. Thelonger the length of residency, the higher thepossibility for these people to integrate into thecommunity where they live. But this analysisreveals that length of residence is not an



important factor for social integration. However,the negative coefficient value for residents offive years or less shows that they are less likely tointegrate into the neighbourhood as comparedto the other residents who have lived therelonger (Table 2).

Many studies have shown the existence of arelationship between local friendships,neighbourhood and residential attachments. Itwas also found that attachment was generated byinformal and formal participation in the localarea (Woolever 1992:99-104). The analysis showsthat residential attachment is not consistentlysignificant with social integration. It is significantonly in column 4 at level 0.05 when ethnicgroups were left out and in column 6 at level0.01 when the age of respondents was left out(Table 2). What can be concluded from thesefindings is that residents who are attached totheir residence are 2 times more likely tointegrate into the community (eO692O=2.O, seecolumn 6, Table 2). Attachment towardsresidence may also be due to ethnicity. Sincemost of the neighbourhoods involved in thisanalysis are a Malay majority, it is not surprisingto see that attachment is a variable for socialintegration in this study. The findings also showthat households are more attached to aneighbourhood if the majority of the populationis of a similar ethnic group as theirs, giving riseto a reluctance to move out of thatneighbourhood. The implication of the findingis that in the future, there is likely to be anincrease in the segregation of people by ethnicbackgrounds in the public low cost housingsector.

Residential Satisfaction

This study shows that both housing andresidential satisfaction are constantly significantwith social integration (p<0.05, see Table 2).Residents who are satisfied with theirneighbourhoods are 2.4 times (e

08539=2.4 seecolumn 2, Table 2) more likely to integratecompared with residents who are not satisfiedwith their neighbourhoods. Residents who aresatisfied with their housing are 1.9 times(eo.6566=1 9 s e e c o i u m n 2, Table 2) more likely tointegrate than residents who are not satisfied.The finding implies that those who are satisfiedwith their residence are more likely to stay longerand be more integrated into the community ascompared to those who are not satisfied. Razali

(1991) stated that one of the reasons peoplemove is because they are not satisfied with theirexisting house and neighbourhood. If theturnover rate of residents is high in the area, itcan affect the style and strength of relationshipsin the area. This study also shows that withoutconsidering residential satisfaction (see column3, Table 2) age, ethnic groups and location aresignificantly related to social integration. Whenthe satisfaction variables are included as variable(column 2, Table 2), all the three statisticalvariables from column 3, which are significantlyrelated to social integration, continue to havethe same quality. Some of the coefficients arereduced in size, but the reduction is generallysmall. What can be concluded here is that allthe variables, which show significant values,operate in an independent manner to predictsocial integration. Therefore satisfaction is animportant variable in predicting socialintegration. In trying to solve housing demand,the government has introduced many standardsand designs for low cost housing. There areeven suggestions that size and quality should besacrificed to ensure that housing targets can beachieved This study suggests that for publichousing to be used as an instrument to achievesocial integration, subjective measurements, thatis the feelings, perceptions and attitudes of thepeople, should be taken into consideration.

Table 3 compares the two districts, UluLangat and Kuala Langat, and also Malays andnon-Malays. For residents in Ulu Langat, thevariable residential satisfaction has a significantrelationship with social integration at p<0.05(see Table 3). The other variables such as age,residential attachment and ethnic group did notshow any significant relationship. Therefore inUlu Langat, respondents who are satisfied withtheir houses are two times more likely(eo.679o=1 97 T a b l e 3 ) t o integrate into thecommunity than residents who are not satisfied.Residents who are satisfied with theirneighbourhood are 3 times (e11829=3.3, Table 3)more likely to integrate into the community.

For Kuala Langat, housing satisfaction, ageand ethnic group variables have a significantrelationship with social integration. Residentswho are satisfied with their houses are two timesmore (eo7192=2.O5, Table 3) likely to integrateinto the community compared with residentswho are not satisfied. The Malays here are threetimes (e1 °°32=2.7, Table 3) more likely to integrate


Ahmad Hariza Hashim

as compared with the non-Malays. The negativecoefficient indicated that the age group of 30years and less are one-quarter more likely toparticipate in social integration as comparedwith respondents of more than 30 years of age.

A comparison of the two districts shows thatin Ulu Langat there is no difference betweenethnic groups for social integration, while inKuala Langat there is a difference. The Malaysin Kuala Langat integrate more than the non-Malays. Residents in both areas feel that housingsatisfaction is an important predictor of socialintegration, as both show a significantrelationship with social integration at level 0.05(Table 3). Between the two districts, there areno significant differences for the relationshipbetween social integration and housingsatisfaction. This means that for both districts,housing satisfaction is a very important predictorfor social integration. One of the main reasonsfor this is that the majority of the respondents inboth districts are Malays. For the Malays, housingsatisfaction shows a strong significant relationshipwith social integration at level 0.001 (Table 3).The Malays who are satisfied with their housesare three times (eL175=3.2, Table 3) more likelyto integrate as compared with Malays who arenot satisfied with their houses. Residentialattachment and district are also importantpredictors, for the Malays, for social integration.Both these variables show a significant

relationship with social integration at level 0.05(Table 3).

Lastly, looking at the non-Malays column itcan be seen that none of the variables show asignificant relationship at level p<0.05 with socialintegration (Table 3). This is one of the majordifferences between the Malays and non-Malays.The reason for this difference is that for thenon-Malays, residential aspect is not an importantfactor in determining their behaviour for socialintegration. But for the Malays it is an importantaspect and may be due to the probability of theMalay obtaining other low cost housing beinghigher as compared to the non-Malays.

CONCLUSIONTo summarise the above findings, age ofrespondents, ethnic group, location, residentialattachment and residential satisfaction are majordeterminants of social integration in public lowcost housing in Selangor, Malaysia. The resultof this study shows that social integration amongresidents here is driven by considerationsdifferent from those found in other studies inthe developed countries. Even among the ethnicgroups in Malaysia, it is shown that socialintegration is driven by different considerations.This is not surprising as the different ethnicgroups have different cultures and ways of life.

The factors which could have a significantimpact on social integration, and implications

TABLE 3Logistic regression for social integration by ethnic groups and areas

Variables

Housing SatisfactionNeighbourhoodSatisfactionAge

30 years and lessmore than 30 years

Residential AttachmentEthnic GroupsDistrictConstant

-2 Log Likelihoodd.f.

Chi square valued.f.

Ethnic

Malay

1.1749***

0.7025

-0.4482-0.09140.7563*

1.2268***-3.5791

258.08923751.2

6

Groups

Non-Malay

-0.2208

0.9261

-0.87270.17580.2747

0.5760-2.3035

201.156151

15.86

District

Ulu Langat

0.6790*

1.1829**

-0.4095-0.10230.74310.3853

-2.7158

257.25920023.1

6

Kuala Langat

0.7192*

-0.0485

-0.7788*0.07780.49931.0032***

-1.1053

235.924188

25.76

* p<0.005,** p<0.01, *** p<0.001



for the restructuring policy of the governmentare location, ethnic group and residentialsatisfaction.

The significance of location suggests thatthe focus of the national unity programmesshould be widened to include both urban andnon-urban areas.

For ethnic groups, the results show thatthey prefer to live in an area where they are themajority. The results also suggest that the Malaysare more likely to stay in their own communityand the non-Malays are more receptive to livingamong other ethnic groups. This may be due tothe Malays being the majority while the otherethnic groups are the minority. Therefore, toensure the success of social integrationprogrammes in public housing, the allocationratio set by the government should be revisedand a more balanced allocation introduced. Onlythen can the feeling of living together in onearea be built up.

The significance of residential satisfactionin determining social integration also suggeststhat it may have wider implications for thenational integration programmes. The introduc-tion of a social integration policy for the residentsin low cost housing should be in line with housingpolicy designed to maximise residentialsatisfaction. The results suggested that residentswith a strong residential attachment and highlevel of residential satisfaction are more willingto participate in community activities, whichmay in turn enhance social integration. Factorswhich could affect residential satisfaction, suchas defects in the physical structure of the housing,lack of well-maintained public facilities, and poorsocial and physical environment could alsoadversely affect the achievement of greater socialintegration.

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Jerusalem: The Magness Press HebrewUniversity.

DAVIES, E. E., and M. FINK-DAVIES. 1981. Predictorsof satisfaction with housing and neighbourhood:a nationwide study in the Republic of Ireland.Social Indicators Research 9: 477-494.

DRAKAKIS-SMITH, D. 1980. The role of the privatesector in housing the urban poor in PeninsularMalaysia. In Issues in Malaysian Development, ed.J. C.Jackson and M. Rudner, p. 305-337. KualaLumpur: Heinemann Education Books (ASIA)Ltd.

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HUSNA, S. and Y. NURIZAN. 1987. Housing provisionand satisfaction of low-income households inKuala Lumpur. Habitat International 11(4):27-38.

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MARANS, R. W. and W. RODGERS. 1975. Towards anunderstanding of community satisfaction. InMetropolitan America, ed. A. H. Hawley andV. P. Rock. National Academy of Science.

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PACIONE, M. 1990. Urban liveability: a review. UrbanGeography 11(1): 1-30.

PENG, K. K. 1982. The housing crisis and FourthMalaysian Plan. Development Forum 12(1).


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Malay middle class in Kuala Lumpur, Malaysia.Thesis submitted to the University of Sheffield,Department of Town and Regional Planning,Unpublished Ph.D Thesis. June.

SAUNDERS, P. 1990. A Nation of Homeowners. London:Unwin Hyman Ltd.

SATSANGI M. and A. KFARNS. 1992. The use and

interpretation of tenant satisfaction surveys inBritish social housing. Government and Policy,Environment and Planning C 10(3): 317-331.

ST. JOHN, C , M. D. AUSTIN and Y. BABA. 1986. The

question of community attachment revisited.Sociobgical Spectrum 6: 411-431.

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WEIDEMANN, S. and J. R. ANDERSON. 1985. A

conceptual framework for residentialsatisfaction. In Human Behaviour andEnvironment ed. I. Altman and C. Werner, 2:153-182. New York: Plenum Press.

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(Received: 24 April 2001)

10 PertanikaJ. Soc. Sci. & Hum. Vol. 11 No. 1 2003

Pertanika J. Soc. Sci. & Hum. 11(1): 11-17(2003) ISSN: 0128-7702© Universiti Putra Malaysia Press

Kreativiti Guru Pendidikan Seni

CHUA YAN PIAW, SHARIFAH MD. NOR, NAIM B. MOHD & WAN ZAH WAN ALIJabatan Pendidikan

Fakulti Pengajian PendidikanUniversiti Putra Malaysia

43300 UPM, Serdang, Selangw, Malaysia

Kata kunci: Kreativiti, guru Pendidikan Seni sekolah menengah

ABSTRAK

Matlamat utama kajian ialah untuk membandingkan kreativiti guru Pendidikan Seni Terlatih danguru Pendidikan Seni Tidak Terlatih yang mengajar di sekolah-sekolah menengah. Kajian inimerupakan kajian deskriptif yang menggunakan alat Ujian Pemikiran Kreatif Figural Torranceuntuk memperoleh indeks kreativiti guru. Subjek kajian terdiri daripada seramai 34 guruPendidikan Seni terlatih dan 45 guru Pendidikan Seni tidak terlatih dari 22 sekolah menengahdaerah Hulu Langat, Selangor. Dapatan kajian menunjukkan bahawa kumpulan guru PendidikanSeni adalah lebih kreatif secara signifikan berbanding kumpulan guru Pendidikan Seni tidakterlatih dari segi kelancaran dan penghuraian. Ini bererti guru Pendidikan Seni terlatih ini lebihberupaya memahami, membaca dan menghuraikan idea-idea kreatif yang dihasilkan pelajar.Pengkaji mencadangkan agar kursus dan latihan yang diberikan kepada para guru PendidikanSeni pada masa depan lebih mengutamakan aspek kreativiti.

ABSTRACT

The main purpose of this study is to compare the creativity of trained and untrained art educationteachers. This is a descriptive study that uses the Torrance Test of Creative Thinking as itsinstrument to obtain the creative thinking indexes of the teachers. Subjects of the study comprise34 trained art education teachers and 45 untrained art education teachers from 22 secondaryschools located in the district of Hulu Langat, Selangor. The results of the study indicated thattrained art education teachers are significantly more creative than untrained art educationteachers in the aspects of fluency and elaboration. This suggests that trained art educationteachers can understand creative ideas better and elaborate on them in more detail thanuntrained art education teachers. The researcher suggests that in future teachers trainingprogrammes should place more emphasis on creativity.

PENGENALAN

Kreativiti merupakan salah satu keupayaan uniksemula jadi manusia. Adalah dipercayai bahawaseseorang individu tidak dapat menggunakanpotensi dirinya dengan sempurna tanpa kreativiti.Pendidikan seni merupakan salah satu matapelajaran utama di sekolah yang penting untukmerangsang pemikiran kreatif para pelajar.Walau bagaimanapun, menurut Victor (1978),guru-guru Pendidikan Seni yang tidak terlatihdalam Pendidikan Seni adalah kurang kreatifdan kurang berupaya memperkembang kreativitipelajar.

Dakwaan Victor disokong oleh PertubuhanSeni Negeri-negeri Barat, Amerika Syarikat(1976), yang melaporkan kajian ke atas lebihdaripada 5000 sekolah di Amerika Syarikat. Lebihdaripada 2000 pelukis dan seniman profesionalditempatkan di sekolah-sekolah tersebut sebagaiguru seni untuk meningkatkan keupayaan kreatifpelajar. Hasil kajian tersebut menunjukkan minatpelajar dan pencapaian mereka dalam akademikjuga bertambah.

Bagi memperlihat sama ada guru yang dilatihuntuk mengendali aktiviti kreatif dapatmeningkatkan kreativiti pelajar dalam mata

Chua Yan Piaw, Sharifah Md. Noor, Nairn b. Mohd & Wan Zah Wan Ali

pelajaran Pendidikan Seni, Richmond (1993)membina satu konsep imaginatif dalampengajaran Pendidikan Seni untuk membantumeningkatkan imaginasi pelajar dalam hasil senipelajar. Dalam kajian itu, guru-guru yang dilatihdengan konsep tersebut telah meningkatkankeupayaan kreatif pelajar. Ferrell, Kress dan Croft(1988) juga melaporkan bahawa hasil kajianmereka menunjukkan kumpulan guru yangdilatih di bawah program pengajaran yangberorientasikan konsep kreativiti adalah lebihinovatif, lebih kreatif dan lebih menghargai idea-idea pelajar daripada kumpulan guru yang dilatihdi bawah program pendidikan guru yang biasa.

Sementara itu, Mohan (1973) membuatkajian ke atas kreativiti guru dan mendapatikandungan kursus-kursus pendidikan pusatlatihan guru adalah kurang menekankan aspekkreativiti. Beliau mencadangkan bahawa programlatihan guru harus lebih mementingkan aspekkreativiti guru. Menurut beliau, kursus-kursuskreativiti adalah amat diperlukan oleh para guruterlatih dan guru pelatih.

Lowendeld dan Brittain (1975) berpendapatbahawa guru harus berminat dalam PendidikanSeni dan meningkatkan keupayaan diri untukmengendalikan aktiviti yang kreatif secaraberterusan bagi melibatkan pelajarnya dalamekspresi kreatif. Semua kanak-kanak mempunyaidesakan kreativiti dalaman yang dapat disalurkanmelalui aktiviti-aktiviti seni. Pelajar harusdidedahkan kepada sebanyak bentuk idea danrangsangan yang mungkin, kerana proses kreatifadalah bukan hanya satu keseronokan bagipelajar sendiri sahaja, ia merupakan latihanuntuk menemui dan memahami diri sendiri dandunia. Oleh itu, guru Pendidikan Seni harusdiberi latihan yang dapat meningkatkan kreativitiguru.

Di Malaysia, tiada kajian dilakukan untukmengenal pasti kreativiti guru-guru pendidikanseni, walaupun sebilangan besar guru yangmengajar mata pelajaran Pendidikan Seni disekolah-sekolah menengah adalah guru-guruyang tidak terlatih di bidang Pendidikan Seni(Chua 1998).

OBJEKTIF KAJIAN

Kajian ini dilakukan untuk melihat sama adaguru Pendidikan Seni yang terlatih lebih kreatifdaripada guru Pendidikan Seni Tidak Terlatih.

KAEDAH

Responden

Bagi menepati objektif kajian ini, 34 guruPendidikan Seni Terlatih dan 45 guru PendidikanSeni Tidak Terlatih di dalam Daerah HuluLangat, Selangor dipilih sebagai responden kajianini. Responden ini dipilih secara rawak daripada151 guru Pendidikan Seni dalam daerah tersebut.Guru Pendidikan Seni Terlatih adalah guru yangpernah mengikuti kursus Pendidikan Seni dimaktab perguruan atau institusi pengajian tinggiyang lain, manakala guru Pendidikan Seni TidakTerlatih adalah guru sekolah menengah yangtidak terlatih dalam bidang Pendidikan Seni,yang mengajar mata pelajaran Pendidikan Seni.

Alat Kajian

Alat kajian bagi penyelidikan ini dinamakanUjian Kreatif Figural Torrance (TTCT).Penggunaan dan penterjermahan alat kajiandibenarkan oleh pembina alat kajian ini.Terdapat tiga aktiviti melengkapkan gambarlukisan dalam TTCT yang menguji kreativiti guru-guru Pendidikan Seni. Lima komponen kreativitiyang dikenal pasti melalui TTCT ialah:1. Keaslian - idea yang unik, iaitu idea yang

jarang dijumpai.2. Kelancaran - Bilangan idea baru yang

dihasilkan oleh individu.3. Penghuraian - Kebolehan memberi butir-

butir lanjut yang menerangkan idea yangtelah dihasilkan.

4. Keabstrakan tajuk - keupayaan mensintesisdan menyusun pemikiran, memperolehmaklumat-maklumat penting yang diperlu-kan, mengetahui apa yang penting dalamgambar yang dilukis dan seterusnya memberitajuk yang baik kepada gambar tersebut.

5. Penentangan Penutupan "Premature" -keupayaan untuk menentang kecenderunganuntuk membuat keputusan akhir denganserta-merta tanpa memikir atau menimbangmaklumat-maklumat yang lain.

a, Kesahan dan Kebolehpercayaan TTCTKajian ten tang kesahan dankebolehpercayaannya telah banyakdijalankan dan dilaporkan. Sejumlah besarbukti ujian kesahan telah dihasilkan danditerbitkan (Torrance 1974). Kajian-kajiantersebut termasuk kesahan kandungan(content validity), kesahan ramalan



(predictive validity), kesahan seiring(concurrent validity) dan kesahan binaan(construct validity). Terdapat banyak kajianyang berkaitan dengan kesahan ramalan,kesahan seiring dan kesahan binaan. Kajian-kajian tersebut dihuraikan dalam 'TTCTStreamlined (Revised) Manual' (Torranceand Orlow 1984).

b. Adaptasi dan Ujian Rintis TTCT VersiBahasa Malaysia TTCT (BM)TTCT diterjemah ke dalam bahasa Malaysiadan kemudiannya disemak dan diperbaikioleh tiga guru yang mahir dalam kedua-duabahasa Inggeris dan bahasa Malaysia. Kajianrintis kemudian dijalankan denganmenggunakan 11 guru sekolah menengah.Semua guru tersebut kemudian ditemu bualsecara individu. Kesemua guru tersebutmengatakan bahawa arahan-arahan mudahdifahami dan tidak mengelirukan. Setelahdua bulan, TTCT (BM) diuji semula ke atasguru-guru yang telah menjalani ujian rintis.Pekali kolerasi Kebolehpercayaan uji danuji semula bagi komponen keaslian,kelancaran, penghuraian, keabstrakan tajukdan penentangan penutupan "premature"adalah 0.82, 0.76, 0.75, 0.84 dan 0.79 masing-masing pada p< .001. Pekali kolerasiKebolehpercayaan untuk kreativiti figuralialah 0.83. Berdasarkan keputusan kajian diatas, TTCT (BM) diputuskan sesuai danboleh dipercayai untuk memperoleh skoryang stabil daripada responden.

Prosedur

Ujian TTCT diberikan secara individu kepadaguru-guru pendidikan seni di sekolah masing-masing oleh pengkaji sendiri.

Analisis Data

Statistik seperti min, sisihan piawai, varian dikiramenggunakan perisian menganalisis data SPSS.Bagi membandingkan kreativiti kumpulan guruPendidikan Seni terlatih dan kumpulan guruPendidikan Seni tidak terlatih, data yangdipungut oleh alat kajian dianalisis menggunakanujian-t berdasarkan indeks kreativiti dan kelima-lima komponen kreativiti iaitu keaslian,kelancaran, penghuraian, keabstrakan tajuk danpenentangan penutupan "premature".

KEPUTUSANAnalisis Ujian t Membandingkan Indeks KreativitiGuru Pendidikan Seni Terlatih dan GuruPendidikan Seni Tidak TerlatihUjian t dua sampel tidak bersandar dijalankanuntuk menguji perbezaan antara:a. Min indeks kreativiti guru Pendidikan Seni

Terlatih dan min indeks kreativiti guruPendidikan Seni Tidak Terlatih.

b. Min setiap komponen kreativiti guruPendidikan Seni Terlatih dan guruPendidikan Seni Tidak Terlatih.

Berdasarkan nilai indeks kreativiti guru-gurupendidikan seni yang diperoleh daripada skorujian TTCT, Jadual 1 diperoleh seperti di bawah:

Berdasarkan Jadual 1, nilai min bagi indekskreativiti guru Pendidikan Seni Terlatih adalahlebih tinggi daripada nilai min bagi indekskreativiti guru Pendidikan Seni Tidak Terlatih.Guru Pendidikan Seni Terlatih mempunyai nilaimin bagi indeks kreativiti sebanyak 78.97 dansisihan piawai sebanyak 15.85. Nilai minimumdan nilai maksimum bagi indeks kreativiti pulaialah 53.80 dan 118.80. Bagi guru PendidikanSeni Tidak Terlatih pula, nilai min bagi indekskreativiti dan sisihan piawai ialah 63.61 dan16.36. Skor indeks kreativiti ialah dari 32.20

JADUAL 1Ujian t membandingkan indeks kreativiti di antara kedua-dua kumpulan guru Pendidikan Seni

MinSisihan piawai

MinimaMaksima

Guru Pendidikan SeniT'f*r\'3 t i l l

(n=34)

78.9715.88

53.80118.80

Guru Pendidikan Seni

(n=45)

63.6116.36

32.20104.00

Ujian t

t p< .005

4.03 Signifikan

Sisihan piawai min • 16.35, df = 75, t(krit.) • 2.66, Aras signifikan = 1 ekor.

PertanikaJ. Soc. Sci. 8c Hum. Vol. 11 No. 1 2003 13

Chua Yan Piaw, Sharifah Md. Noor, Nairn b. Mohd & Wan Zah Wan AH

sehingga 104.00. Nilai sebanyak 4.03 adalahsignifikan secara statistik pada p < .005menunjukkan bahawa indeks kreativiti guruPendidikan Seni Terlatih (min = 78.97) adalahlebih tinggi secara signifikan daripada indekskreativiti guru Pendidikan Seni Tidak Terlatih(min = 63.61).

Berdasarkan keputusan analisis ujian t tadi,jelaslah bahawa kumpulan guru PendidikanSeni Terlatih adalah lebih kreatif secara signifikandaripada kumpulan guru Pendidikan Seni TidakTerlatih.

Analisis Ujian t bagi Membandingkan Komponen-K&mponen Kreativiti Kedua-dua Kumpulan GuruPendidikan Seni

Berdasarkan skor setiap komponen kreativiti yangdiperoleh guru-guru Pendidikan Seni dalam ujianTTCT, Ujian t dua sampel tidak bersandar

dijalankan dan keputusannya dipersembahkandalam Jadual 2.

Seperti yang ditunjukkan dalam Jadual 2,guru Pendidikan Seni Terlatih mempunyai nilaimin keaslian sebanyak 106.58 dan sisihan piawaisebanyak 29.41 manakala nilai min keaslian dansisihan piawai bagi kumpulan guru PendidikanSeni Tidak Terlatih ialah 92.47 dan 28.13. Nilait sebanyak 1.90 (df = 75, p < .05) adalah tidaksignifikan secara statistik.

Keputusan ujian ini menunjukkan bahawatidak terdapat perbezaan yang signifikan di antaramin keaslian guru Pendidikan Seni Terlatih danguru Pendidikan Seni Tidak Terlatih. Denganerti kata lain, keputusan di atas menunjukkanbahawa tidak ada perbezaan kreativiti dari segimenghasilkan idea yang asli dan unik antaraguru Pendidikan Seni Terlatih dan guruPendidikan Seni Tidak Terlatih.

JADUAL 2Ujian t komponen-komponen kreativiti antara guru Pendidikan Seni

terlatih dan guru Pendidikan Seni tidak terlatih

i^omponen-ivoiiiponcn jvreauviu

KEASLIANMinSisihan piawaiMinimumMaksim um

KELANGARANMinSisihan piawaiMinimumMaksim um

PENGHURAIANMinSisihan piawaiMinimumMaksimum

KEABSTRAKAN TAJUKMinSisihan piawaiMinimumMaksimum

PENENTANGAN PENUTUPAN"PREMATURE"

MinSisihan piawaiMinimumMaksimum

Guru

Terlatih

106.5829.4172

172

104.525.1067

160

51.217.00

4472

55.0029.770

100

60.4414.580

85

Pendidikan Seni

Tidak Terlatih

92.4728.134

164

90.5622.450

151

46.887.34

3080

37.0042.14

0170

55.4713.840

85

t

1.90

2.16

2.07

1.63

1.30

Ujian t

Tidak signifikan

Signifikan

Signifikan

Tidak signifikan

Tidak signifikan

d.f = 75, p< .05

14 PertanikaJ. Soc. Sri. & Hum. Vol. 11 No. 1 2003


Data di dalam Jadual 2 menunjukkan bahawaterdapat perbezaaan yang signifikan antara minkelancaran guru Pendidikan Seni Terlatih danguru Pendidikan Seni Tidak Terlatih. GuruPendidikan Seni Terlatih mempunyai nilai minkelancaran sebanyak 104.50 dan sisihan piawaisebanyak 25.10, manakala guru Pendidikan SeniTidak Terlatih memperoleh nilai min sebanyak90.56 dan sisihan piawai sebanyak 22.45. Nilai tsebanyak 2.16 adalah signifikan pada arasp < .05. Daripada keputusan ujian ini, didapatikumpulan guru Pendidikan Seni Terlatih adalahlebih kreatif dari segi kelancaran daripadakumpulan guru Pendidikan Seni Tidak Terlatih,iaitu kumpulan guru Pendidikan Seni Terlatihadalah lebih berupaya menghasilkan bilanganidea baru yang banyak daripada kumpulan guruPendidikan Seni Tidak Terlatih.

Keputusan ujian t juga menunjukkanterdapat perbezaan yang signifikan di antarakedua-dua kumpulan guru Pendidikan Seni darisegi penghuraian. Min dan sisihan piawai bagiguru Pendidikan Seni Terlatih ialah 51.21 dan7.00 manakala min dan sisihan piawai bagi guruPendidikan Seni Tidak Terlatih ialah 46.88 dan7.34. Nilai t sebanyak 2.07 adalah signifikanpada p < .05. Ini bererti kumpulan guruPendidikan Seni Terlatih lebih berupayamentafsir dan menghuraikan idea-idea pelajardaripada kumpulan guru Pendidikan Seni TidakTerlatih.

Data dalam Jadual 2 juga menunjukkanbahawa tidak terdapat perbezaan yang signifikanantara guru Pendidikan Seni Terlatih dan guruPendidikan Seni Tidak Terlatih dari segikeabstrakan tajuk dan penentangan penutupan"premature".

PERBINCANGANKeputusan analisis ujian t dua sampel tidakbersandar menunjukkan bahawa terdapatperbezaan kreativiti yang signifikan antara kedua-dua kumpulan guru Pendidikan Seni Terlatihdan guru Pendidikan Seni Tidak Terlatih.Kumpulan guru Pendidikan Seni Terlatih adalahlebih kreatif secara signifikan daripada kumpulanguru Pendidikan Seni Tidak Terlatih padap < .005.

Selain daripada itu, keputusan kajian inijuga menunjukkan bahawa guru Pendidikan SeniTerlatih adalah lebih kreatif dari segi kelancarandan penghuraian. Ini bererti guru PendidikanSeni Terlatih lebih berupaya menghasilkan idea-

idea yang lebih banyak dalam masa yang singkatdan lebih berupaya menghuraikan idea-ideasecara teliti daripada guru Pendidikan Seni TidakTerlatih, dan mereka lebih mementingkankreativiti dalam catan pelajar daripada guruPendidikan Seni Tidak Terlatih semasa membuatpenilaian. Dapatan kajian ini selaras denganpendapat Lowenfeld dan Brittain (1975) danVictor (1978) bahawa guru Pendidikan Seni yanglebih kreatif lebih memahami idea-idea barudan luar biasa pelajar-pelajarnya berbanding guruPendidikan Seni yang kurang kreatif.

Mengapa kumpulan guru Pendidikan SeniTerlatih mempunyai kreativiti yang lebih tinggidaripada kumpulan guru Pendidikan Seni TidakTerlatih ? Soalan ini mungkin dapat diterangkanoleh dapatan kajian Wikstrom, Ekvall danSanstrom (1994); Ferrel, Kress dan Croft (1988)dan Liikanen (1975).

Dapatan kajian Wikstrom, Ekvall danSanstrom (1994) menunjukkan bahawa aktiviti-aktiviti Pendidikan Seni meningkatkan kreativitidari segi penambahan idea-idea luar biasa iaitukelancaran. Selain itu, kajian Ferrel, Kress danCroft (1988) juga menunjukkan bahawa guru-guru yang telah menghadiri program latihanPendidikan kreatif adalah lebih inovatif dankreatif.

Hasil kajian di atas juga sepadan dengankajian Liikanen (1975) yang menggunakan alatkajian yang sama dengan kajian ini iaitu alatTTCT untuk menyukat kreativiti responden.Dapatan kajian beliau menunjukkan bahawaprogram latihan Pendidikan Seni meningkatkankreativiti pelajar dari segi keaslian, kelancaran.Ini bererti guru-guru Pendidikan Seni harusdiberi kursus atau latihan Pendidikan Seni untukmeningkatkan kreativiti mereka.

Walaupun dapatan kajian ini menunjukkanbahawa guru Pendidikan Seni Terlatih lebihkreatif dari segi kelancaran dan penghuraian,keputusan juga menunjukkan bahawa tidakterdapat perbezaan di antara kedua-duakumpulan guru tersebut dari segi keaslian,keabstrakan tajuk dan penentangan penutupan"premature". Dengan erti kata yang lain, dapatankajian ini menunjukkan bahawa latihan gurutidak meningkatkan keupayaan guru PendidikanSeni untuk menghasilkan idea-idea yang kreatif(keaslian). Selain daripada itu, ia juga tidakmeningkatkan keupayaan guru untuk mensintesis,menyusun pemikiran dan seterusnya mentafsiridea-idea utama dalam karya seni yang


Chua Yan Piaw, Sharifah Md. Noor, Nairn b. Mohd & Wan Zah Wan Ali

diperhatinya (keabstrakan tajuk). Di sampingitu, latihan guru dalam bidang Pendidikan Senijuga tidak meningkatkan keupayaan guru untukmenentang kecenderungan membuat keputusanakhir tentang sesuatu idea dengan serta-mertatanpa memikirkan dan menimbangkan maklumatyang lain (penentangan penutupan "premature").

Dapatan ini adalah amat penting keranakeupayaan seseorang guru untuk menjalankanproses pengajaran dan pembelajaran yang berjayabergantung kepada keupayaan guru tersebutmenggunakan pengetahuannya yang sedia adasecara kreatif. Jika guru-guru tidak dapatmenghasilkan idea-idea baru (keaslian), adalahsukar bagi guru untuk menyelesaikan pelbagaimasalah yang dihadapi dalam proses pengajarandan pembelajaran. Begitu juga jika guru tidakdapat mensintesis, menyusun pemikiran,mentafsir idea utama (keabstrakan tajuk) dalamcatan pelajar dan terus membuat keputusansecara serta-merta tentang idea tersebut tanpamemikirkan maklumat-maklumat yang lain(penentangan penutupan "premature"), adalahsukar bagi guru untuk membuat penilaian yangtepat dan adil terhadap catan pelajar.Memandangkan hakikat bahawa tiada perbezaankreativiti secara signifikan antara guruPendidikan Seni Terlatih dan guru PendidikanSeni Terlatih dari segi keaslian, keabstrakan tajukdan penentangan penutupan "premature", usahaperlu dilakukan untuk meningkatkan kreativitiguru Pendidikan Seni dari ketiga-tiga komponenkreativiti ini, kerana guru yang kreatif lebihmemahami dan menggalakkan pemikiran kreatifpelajar (Lowenfeld dan Brittain 1975). Disamping itu, berdasarkan hasil kajian ini, kajianlanjut juga boleh dilakukan untuk menyelidiksama ada terdapat perbezaan kreativiti antarapelajar yang mengambil mata pelajaranpendidikan seni dan pelajar yang tidakmengambil mata pelajaran seni.

RUMUSANKajian ini telah membandingkan kreativiti guru-guru Pendidikan Seni sekolah menengah didaerah Hulu Langat. Rumusan hasil kajianadalah seperti berikut:L Terdapat perbezaan yang signifikan dari segi

kreativiti di antara kumpulan guruPendidikan Seni Terlatih dan guru

Pendidikan Seni Tidak Terlatih.Kumpulan guru Pendidikan Seni Terlatihadalah lebih kreatif secara signifikandaripada kumpulan guru Pendidikan SeniTidak Terlatih.

2. Guru Pendidikan Seni Terlatih adalah lebihkreatif dari segi kelancaran danpenghuraian. Walau bagaimanapun,keputusan menunjukkan tiada perbezaanantara kedua-dua kumpulan guru tersebutdari segi keaslian, keabstrakan tajuk danpenentangan penutupan "premature".

RUJUKANCHUA, Y. P. 1988. Penilaian guru pendidikan seni

terhadap kreativiti catan pelajar. Thesis Master,Universiti Putra Malaysia, Serdang.

FERRELL, B., M. KRESS dan J. CROFT. 1988.Characteristics of teacher in a full day giftedprogram. Roeper Review 10(3): 136-139.

LIIKANEN, P. 1975. Increasing Creativity Through ArtEducation Among Pre-School Children, JyvaskylaUniversity. Jyvaskyla, Finland: Jyvaskyla UniversityLibrary.

LOWENFELD, V. dan W. L. BRITTAIN. 1975. Creativeand Mental Growth. 6th ed. New York: MacmillanPublishing Co.

MOHAN, M. 1973. Is there a need for a course increativity in teacher education? Journal ofCreative-Behavior 7(3): 175-86.

Pertubuhan Seni Negeri-Negeri Barat AmerikaSyarikat. 1976. A Study of the Poetry and VisualArts Components of the Artists-in-Schools Program.Study Summary and Study Highlights, m.s.1-24.Denver: Colo.

RICHMOND, S. 1993. Art, imagination and teaching:researching the high school classroom.Canadian Journal of Education 18(4): 366-380.

TORRANCE, E. P. 1974. Torrance Test of CreativeThinking. Lexitgon, Mass: Personal Press/Ginnand Company.

TORRANCE, E. P. dan E. B. ORLOW. 1984. TorranceTest of Creative Thinking Streamlined (Revised)Manual Including Norm and Direction forAdministering and Scoring Figural A and B.Bensenville: Scholastic Testing Service.

VICTOR, D. 1978. The preparation of the teacherand the grade teacher. Dalam Seminar on

16 PertanikaJ. Soc. Sci. 8c Hum. Vol. 11 No. 1 2003


Elementary & Secondary School, Education in the W l K s r R O M > B . M . ( R . EKVALI d a n o E SANDSTROM.

visual Arts, disunting oleh C. Howard, m.s. 93- 1 9 9 4 stimulating the creativity of elderly95. New York: New York University Printing institutionalised women through works of art.o f f i c e - Creativity Research Journal 7(2): 171-182.

(Diterima: 23 Februari 2000)

Pertanika J. Soc. Sci. & Hum. Vol. 11 No. 1 2003 17

Pertanika J. Soc. Sci. & Hum. 11(1): 19-31 (2003) ISSN: 0128-7702© Universiti Putra Malaysia Press

Ekonomi Negeri Kelantan dari Perspektif Analisis Shift-Share Wilayah

ZAKARIAH ABDUL RASHIDJabatan Ekonomi Universiti Putra Malaysia

43400 UPM Serdang, Selangor, MalaysiaE-mail:zar@upm. econ. edu. my

Kata kunci: Analisis shift-share wilayah, subtempoh, perindustrian, perubahan struktur nasional

ABSTRAK

Dengan menggunakan rangka kerja analisis shift-share wilayah, kajian yang merangkumi tempoh1980-95 yang dipecahkan kepada dua subtempoh ini bertujuan untuk mengkaji prestasi ekonominegeri Kelantan berbanding ekonomi nasional. Data KDNK Kelantan menurut sektor-sektorutamanya, dikumpul dari sumber UPE dan UPEN Kelantan dan dinyatakan dalam sebutan benardengan menggunakan deflator KDNK. Hasil kajian mendapati bahawa lokasi negeri ini kurangmenarik pelabur, kemajuan perindustrian nasional membantu memajukan perindustrian Kelantan,dan kelebihannya dalam sektor utama juga terjejas oleh arus perubahan struktur nasional. Kajianini mengemukakan beberapa cadangan dasar untuk memajukan negeri ini.

ABSTRACT

Using regional shift-share analysis the present study, covering the overall period of 1980-95 whichis subdivided into two sub-periods, aims at analysing the performance of Kelantan's economy vis-a-vis national economy. The state GDP data according to its major sectors are collected from EPUand the state EPU which is expressed in its real value by using GDP deflator. The results showthat to investors the state is unattractive locationally, good performance of national industrialisationstimulates that of the state, and its advantage in primary sector is erroded because of structuralchange at the national level. The study offers few policy recommendations.

PENGENALAN

Objektif pembangunan wilayah di Malaysiabertujuan untuk mengimbangi pembangunanantara wilayah-wilayah. Kelantan yang terletak diwilayah timur Semenanjung Malaysia, merupakansebuah negeri yang paling rendah pendapatanper kapitanya. Tujuan utama kertas kajian iniialah menerangkan pembangunan ekonominegeri Kelantan berbanding ekonomi Malaysiadan menghuraikan faktor-faktor yangmenyebabkan keadaan tersebut.

Dalam tahun 1995, sektor pertanianKelantan mengeluarkan output sebanyak RM689juta1 dan merupakan penyumbang terbesarkepada KDNK negeri tersebut. Output sektor ini

terus meningkat tahun demi tahun sejak tahun19802 lagi tetapi dengan sumbangan kepadaKDNK negeri yang semakin berkurangan. Sektor-sektor lain yang menunjukkan peningkatansumbangan kepada KDNK Kelantan terdiridaripada sektor perkilangan dan sektorperdagangan.

Pergantungan yang kuat kepada sektorpertanian khususnya dan sektor utama amnyaberlaku terutamanya di peringkat awal tempohkajian. Dalam tahun 1980, sektor utama3

menyumbang hampir satu perdua (43%) kepadaKDNK negeri. Dalam tempoh 1980-95, kajian inimendapati, ekonomi Kelantan telah mengalamiproses kepelbagaian kegiatan. Dalam akhir

1 Kajian ini menggunakan Indeks Harga Pengeluar sebagai deflator yang diasaskan kepada tahun 1970.Tempoh kajian ialah antara 1980-95, ditentukan oleh kedapatan data.Deft nisi sektor-sektor menurut seperti yang digunakan oleh Rancangan Lima Tahun Malaysia, Unit PerancangEkonomi, Malaysia.

Zakariah Abdul Rashid

tempoh kajian, tahun 1995, sumbangan sektorutama telah merosot kepada 20%. Proseskepelbagaian kegiatan ini dapat dikesan melaluiperubahan struktur ekonomi negeri seperti yangditunjukkan olehjadual 1.

Walau kepelbagaian kegiatan berlaku, dalamtahun 1995, sektor pertanian masih lagi menjadipenyumbang terbesar kepada KDNK. Berbandingdengan sumbangan sektor ini di peringkatnasional, Kelantan didapati masih kuatbergantung kepada kegiatan pertanian.Perkembangan sektor perkilangan pulamenampakkan trend yang menggalakkan,menyumbang 16% pada tahun tersebut.Sumbangan sektor-sektor lain adalah sepertiberikut: sektor perdagangan (14.1%),pengangkutan (9.7%), kewangan (7.2%) danpembinaan (4.1%). Sektor perkhidmatankerajaan pula memberikan sumbangan yang agakbesar iaitu 23.2% manakala sektor perlombonganmenyumbang hanya 0.2%.

Kertas kajian ini diatur sedemikian:Bahagian II menghuraikan ciri-ciri asas ekonomiKelantan dari segi tahap kepelbagaian,pertumbuhan tahunan, pendapatan per kapitadan produktiviti buruh. Bahagian III meng-huraikan rangka kerja teoretikal model shift-share wilayah yang akan digunakan dalam kajianini dan pengumpulan data. Bahagian IVmembincangkan hasil penemuan model tersebutdisusuli dengan Bahagian V menyimpulkanperbincangan kertas kajian ini.

CIRI ASAS EKONOMI KELANTAN

Pemusatan Kegiatan Ekonomi Negeri-Negeri

Terpilih

Jadual 2 membandingkan tahap kepelbagaiankegiatan ekonomi dengan menggunakan indekspemusatan kegiatan Gini-Hirschman4 bagi negeri-negeri terpilih. Indeks ini mengukur sejauhmanakah kegiatan ekonomi sesebuah negeriterpusat kepada sebilangan kecil kegiatan atau

JADUAL 1Struktur ekonomi Kelantan 1980-2000, (%)

Sektor 1980 1985 1990 1995 2000*

PertanianPerlombonganPerkilanganPembinaanPengangkutanPerdaganganKewanganPerkhidmatan Kerajaan

42.20.86.44.58.66.8

10.420.3

38.20.8

7.74.98.76.7

10.522.6

30.90.8

14.53.69.0

11.86.8

22.6

25.20.6

15.94.19.7

14.17.2

23.2

20.80.4

17.74.4

10.616.77.4

22.0

Jumlah 100 100 100 100 100

Sumber. Dikira dari Jadual Apendiks dan data UPEN

JADUAL 2Indeks pemusatan Gini-Hirschman

1980 1985 1986 1988

JohorSarawakKelantanTerengganuPahangMalaysia

Sumber: Dikira dari dataUnit Perancang

0.45380.41720.49330.52410.50490.3871

Rancangan MalaysiaEkonomi (EPU)

0.41700.42810.46980.52410.49990.3725

Lima Tahun,

0.44900.45300.43640.63870.48890.3782

pelbagai tahun

0.45350.43730.43340.63670.48820.3884

4 Rumus Indeks Gini-Hirschman yang digunakan adalah seperti berikut:



tersebar kepada pelbagai kegiatan. Dalamtempoh lima belas tahun 1980-95, indeks baginegeri Kelantan menjadi semakin mengecil,tetapi lebih tinggi berbanding indeks nasional.Ini menunjukkan tahap kepelbagaian ekonomiKelantan, walaupun semakin diperbaiki tetapimasih jauh daripada memuaskan dibandingkandengan yang berlaku di negeri-negeri lain. IndeksGini Kelantan pada tahun 1988 dibandingdengan indeks Gini Malaysia pada tahun 1980,menunjukkan tahap kepelbagaian ekonomiKelantan pada tahun 1988 sama dengan tahapkepelbagaian ekonomi nasional pada lapan tahunsebelumnya. Berbanding dengan Johor danSarawak, tahap kepelbagaian ekonomi Kelantanterialu jauh daripada memuaskan.

Kadar Pertumbuhan

Kelantan mengalami pertumbuhan ekonomitahunan yang sederhana (Jadual 3). Dalamtempoh 1980-85, kadar pertumbuhan tahunanKDNKnya ialah 5.96%, kemudian merosotkepada 2.54% dalam tempoh 1985-90, danmeningkat kembali kepada 6.2% dalam tempoh

JADUAL 3Kadar pertumbuhan tahunan, (%)

Tempoh

1980 - 19851985 - 19901990 - 19951980 - 19951996 - 20001991 - 2000

Kelantan

5.962.546.204.896.66.4

Malaysia

5.835.988.696.828.08.3

Sumber. Dikira dari Jadual 1

1990-95. Purata kadar pertumbuhan bagi tempoh1980-95 adalah 4.8%. Kecuali dalam tempoh1980-85, kedua-dua tempoh lima tahun yanglain, kadar pertumbuhan Kelantan adalah lebihrendah berbanding kadar yang dinikmati olehekonomi nasional.

Berdasarkan data KDNK tahunan yang dapatdiperoleh, tempoh 1985-90 menyaksikan terdapatsatu ketika yang menunjukkan KDNK negeriKelantan mengecut, iaitu pada tahun 1986. Iniselaras dengan apa yang berlaku dalam ekonomi

nasional yang juga mengecut kerana tekananresesi negara-negara maju. Dalam tempoh 15tahun antara 1980-95. KDNK Kelantan meningkatmenjadi dua kali ganda, sedangkan ekonominasional menikmati pembesaran sebanyak 2.6kali ganda.

Dalam tahun 1995, dengan menyumbang2.3% kepada KDNK nasional, Kelantanmenduduki tangga kedua terkebawah selepasPerlis. Perbandingan tanpa mengambil kira saizpenduduk seperti ini, walau bagaimanapun,adalah kurang tepat. Dengan mengambil KDNKper kapita negeri ini yang berjumlah RM1727,kajian ini mendapati Kelantan berada di anaktangga yang terkebawah sekali. Saiz pendapatanper kapita Kelantan adalah lebih kurang satupertiga daripada saiz KDNK per kapita nasionalyang berjumlah RM5815.4. Ini menunjukkandengan pertumbuhan ekonomi yang perlahantetapi pertumbuhan penduduk yang lebih pantas,ekonomi Kelantan telah tercicir dalam aruspembangunan ekonomi nasional.

Produktiviti Buruh

Produktiviti (output setiap orang pekerja)Kelantan didapati jauh ketinggalan ke belakangberbanding produktiviti nasional. Pada tahun1980 Kelantan mempunyai indeks produktivitiburuh 4.57 sedangkan ekonomi nasionalmempunyai 9.03. Walaupun Kelantan telahmemperbaiki taraf produktivitinya, meningkatkepada 5.17 pada tahun 1990, kajian inimendapati produktiviti nasional meningkatdengan kadar yang lebih pantas lagi, yaknikepada 13.27. Ini menjadikan jurang produktivitiKelantan-Malaysia semakin melebar. Jika dalamtahun 1980, produktiviti Kelantan menyamai 0.5produktiviti Malaysia, dalam tahun 1990 ia telahmerosot menjadi 0.38. Gambaran produktivitiKelantan-Malaysia bagi sektor-sektor ekonomiditunjukkan dalam Jadual 4.

Produktiviti buruh

Tahun

1980199019952000

JADUAL 4Kelantan dan Malaysia 1980-2000

Kelantan

4.575.185.786.70

Malaysia

9.0311.2714.7818.94

PertanikaJ. Soc. Sci. & Hum. Vol. 11 No. 1 2003 21


Mengapakah keadaan seperti ini berlaku?Banyak faktor yang menyumbang kepada masalahini. Kajian ini akan mengemukakan faktor-faktoryang dapat diterangkan dari perspektif analisisshift-share wilayah sahaja.

ANALISIS WILAYAH - SHIFT-SHARE

Negeri Kelantan jauh tercicir dalam aruspembangunan ekonomi nasional. la berlakumungkin kerana barangan dan perkhidmatanyang dikeluarkan oleh negeri ini tidak berupayamerangsang pertumbuhan yang pantas, faktoryang dikategorikan sebagai "kesilapan" product-mix. Mungkin juga operasi pengeluaran di negeriini kurang berdaya saing, faktor yangdikategorikan sebagai kelemahan daya saing. Jikakita menganggap bahawa kedua-dua perkara inibenar, penyelesaian logikal ialah menukarproduct-mix berdasarkan kepada sesuatu kriteriatertentu dan meningkatkan kecekapan operasipengeluaran dengan menggunakan teknikpengeluaran yang lebih sesuai. Oleh keranaKelantan merupakan sebuah negeri di dalampersekutuan Malaysia, kita merasakan kajian yangmembandingkan prestasi ekonomi negeri inidengan ekonomi nasional menggunakan analisisshift-share amat sesuai.

Buat pertama kali diperkenalkan oleh Dunn(I960)5, teknik ini kemudian digunakan olehPerloff (1960) yang mengkaji data-data gunatenaga dan pekerjaan. Brown (1969), Franklindan Hughes (1973), Stevens dan Moore (1980),Andrikopoulos, Brox dan Carvalho (1990) telahmenggunakan teknik yang sama untuk mengkajidata-data guna tenaga dan nilai-tambah wilayah,menghuraikan jurang perbezaan pertumbuhanantara wilayah. Franklin dan Hughes (1973) danStevens dan Moore (1980) telah menggunakanteknik ini untuk membuat unjuran denganmenggunakan data tahunan dua digit industriyang diambil dari Biro Statistik Buruh AmerikaSyarikat. Dengan menggunakan teknik yangsama, Brown (1969) menggabungkan teknik inidengan teknik ekonometrik untuk mengun-jurkan guna tenaga. Beliau mengira koefisienketaksamaan Theil untuk menentukan araskecekapan ramalannya. Beliau mendapati modelsuper ingrown adalah efisien. Wee dan Wong

(1987) menggunakan kaedah ini untukmengenal pasti alternatif pasaran eksport.

Model Shift-Share

Teknik ini merupakan salah satu daripada teknik-teknik yang amat popular dalam kajian wilayah.Kelebihan teknik ini kerana dua sebab: (1)Teknik ini mudah digunakan dan bergantungkepada data yang mudah diperoleh, menjadikankajian ini cepat dilaksanakan dengan ketepatanyang boleh diterima. (2) Teknik ini belum lagimenerima kritikan dalam kajian empirik sehinggadapat menimbulkan kesangsian di kalanganpengamal. Oleh kerana teknik ini tidakmempunyai kelemahan yang serius, pengamalterus menggunakan teknik ini kerana kebaikan-kebaikan yang dinyatakan di atas.

Teknik ini akan memilih sebuah wilayahlain sebagai standard perbandingan. Perubahanstruktur Kelantan akan dibandingkan denganperubahan struktur wilayah standard ini. Dalamkajian ini wilayah standard yang dimaksudkanialah ekonomi nasional. Kaedah ini dapat jugamembandingkan prestasi subsektor-subsektor didalam kedua-dua wilayah, mengenal pastisubsektor-subsektor di Kelantan yang tumbuhlebih pantas dan yang berkembang lebihperlahan, berbanding yang dialami oleh ekonominasional. Maklumat sedemikian sangat bergunadalam menerangkan perubahan strukturekonomi Kelantan, yang mencorakkan senariopertumbuhan yang ada sekarang ini.

Kaedah ini memisahkan faktor-faktor yangmenghasilkan perubahan dalam KDNK wilayahdengan mengenal pasti komponen-komponenperubahan tersebut. Hasil kajian ini akan dapatmenerangkan dua peringkat maklumat, iaituperihal pertumbuhan dan kemerosotan (a)sesebuah wilayah dalam ekonomi nasional dan(b) sesebuah industri dalam sesebuah wilayah.Komponen 'peralihan wilayah' menerangkanprestasi relatif wilayah tersebut dalam sesebuahindustri. Peralihan wilayah (regional shift)berangka positif bermakna industri berkenaanmenikmati kelebihan berbanding lokasi(locational comparative advantage) bagi wilayahtersebut dan sebaliknya pula bagi peralihanwilayah berangka negatif.

Beliau membentangkan hasil kajiannya di dalam satu mesyuarat Sains Wilayah di Amerika Syarikat, memperkenalkankaedah ini untuk mengkaji secara sistematik data ekonomi wilayah.



Setiap komponen dalam persamaanperalihan (shift) menyediakan paras terjangkabagi output pada akhir tempoh, setiap parasoutput terhasil daripada kuasa-kuasa yangmenghasilkan pertumbuhan atau kemerosotansesebuah industxi dalam wilayah tersebut dalamtempoh berkenaan. Jumlah paras terjangkadalam output ini merupakan jumlah outputdalam sesebuah sektor pada penghujung tempoh.

Komponen-komponen dalam analisis shift-share ini dapat diterangkan seperti di dalampersamaan-persamaan berikut:

Share Nasional (National Share):NSt =

Industri-Mix (Industry Mix):/M,= q^Q'/Q? -

Peralihan Wilayah (Regional Shift):

(1)

(2)

q. dan Q. masing-masing menunjukkanoutput wilayah dan output nasional dalam sektori; q dan Q adalah jumlah output wilayah dannasional dalam semua sektor; dan 0 dan 1merupakan tahun permulaan dan akhirantempoh yang dikaji. Maka, secara definisi outputsektor i mempunyai kaitan seperti dalampersamaan (4).

q{ = NS. + IM. +RSI (4)

Share wilayah atau Regional share dalamsektor i (atau regional proportion) ditakrifkanseperti dalam persamaan (5):

(5)

Sebutan yang terakhir ini menerangkanjumlah output terjangka dalam industxi i dalamwilayah tersebut jika industxi tersebut dapatberkembang di wilayah tersebut pada kadar yangsama dengan kadar yang dialami di peringkatnasional.

Data

Dalam melaksanakan kajian ini, kita memilihbeberapa tempoh selang masa. Pemilihan selangmasa ini begantung kepada data yang dapat kitaperoleh dan pada tempoh masa yang kita fikirkan

wajar dalam mengkaji kesan industxi mix dankesan peralihan wilayah. Selang masa kajian iniadalah seperti berikut: 1980-85, 1985-90, 1990-95dan 1980-95.

Tahun asas bermakna tahun awalan,misalnya bagi selang masa 1980-85, tahun asasialah tahun 1980 manakala bagi selang-masa1985-90, 1990-95 dan 1980-95, tahun asas masing-masing ialah 1985, 1990 dan 1980. Subsektor imewakili subsektor yang dikaji seperti subsektorPertanian, Perlombongan, Perkilangan dansebagainya.

Kajian ini menggunakan data-data KDNK(pada harga tetap 1978) Kelantan dan Malaysiaseperti yang diterbitkan dalam pelbagai terbitanRancangan Malaysia dan Kajian SemulaRancangan Malaysia. Data terkini KDNK ialahbagi tahun 1995 dan bagi kedua-dua ekonomitersebut diperoleh dari sumber yang tidakditerbitkan oleh Unit Perancang Ekonomi,Jabatan Perdana Menteri. Data-data tersebutadalah seperti yang terlampir di bahagianApendiks.

HASIL KAJIAN

Kajian ini mendapati bahawa dalam tempohkeseluruhan, 1980-95, Kelantan telah mengalamikesan peralihan wilayah yang negatif (Jadual 5 -Jadual 8), menunjukkan negeri ini memilikikelemahan wilayah, berlaku dalam semuasubtempoh kecuali sub tempoh 1980-85. Nilai RSbagi subtempoh-subtempoh 1985-90, 1990-95 dantempoh keseluruhan 1980-95 semuanya negatifdan masing-masing adalah -RM362.46 juta,-RM3356.26 juta dan -RM862.55 juta; manakalabagi subtempoh 1980-85 adalah positif, iaituRM 11.07 juta. Ini menunjukkan kelebihanwilayah yang dimiliki oleh negeri ini padaperingkat awal telah bertukar menjadi kelemahanpula pada peringkat akhir tempoh kajian.

Dalam tempoh keseluruhan inijuga, kajianini mendapati nilai regional proportion (RP) lebihbesar daripada nilai output pada tahun akhiran.Nilai RP (RM3598.55 juta) ini adalah nilai yangdicapai jika jumlah output terjangka di Kelantanberkembang pada kadar yang sama dengan kadaryang dialami di peringkat nasional. Inimenunjukkan pertumbuhan ekonomi Kelantanbergantung sepenuhnya kepada pertumbuhannasional, sedangkan pengaruh wilayah menyum-bang secara negatif. Akibat perkembangan ini,



JADUAL 5Hasil analisis shift-share Kelantan-Malaysia, 1980-85 (RM juta - mengikut harga tahun 1978)

PertanianPerlombonganPerkilanganPembinaanPengangkutanPerdaganganKewanganPerkhidmatan KerajaanJUMLAH

RP

666.7914.72

109.3588.52

177.35127.65196.49321.06

1774.93

RS

16.210.28

27.65-1.52

-22.35-8.65-9.49

81.9411.07

1980-85

NS

748.7114.60

114.1779.65

152.66120.80184.52359.75

1774.87

NS*

184.713.60

28.1719.6537.6629.8045.5288.75

437.87

IM

-81.920.12-4.828.87

24.686.85

11.97-38.69

0.06

Sumber: Dikira dari model shift-share



RP

840.6819.37

257.4380.83

226.79138.78278.35388.53

2387.46

RS

-214.68-3.3736.57-7.83

44.79100.22

-140.3568.47

-362.46

1985-90

NS

912.9720.05

183.13116.29207.19159.07249.96538.69

2387.35

NS*

229.975.05

46.1329.2952.1940.0762.96

135.69601.35

IM

-72.29-0.6874.30

-35.4619.60

-20.2928.38

-150.160.12




RP

692.6718.44

548.67136.02301.30395.38229.18549.05

3071.26

RS

-3.67-1.44

-113.67-24.02-36.30-9.38

-32.1885.95

-335.26

1990-95

NS

949.3924.27

445.88110.71276.02362.47209.29693.09

3071.12

NS*

323.398.27

151.8837.7194.02

123.4771.29

236.091046.12

IM

-256.73-5.83

102.7925.3125.2832.9219.89

-144.040.14




JADUAL8Hasil analisis shift-share Kelantan-Malaysia, 1980-95 (RM juta - mengikut harga tahun 1978)


RP

908.1321.91

383.45153.25429.58246.27485.73371.89

3598.55

RS

-219.13-4.9151.55

-41.25-164.58139.73

-288.73263.11

-862.55

1980-95

NS

1518.0129.61

231.47161.49309.52244.93374.12729.40

3598.54

NS*

954.0118.61

145.47101.49194.52153.93235.12458.40

2261.54

IM

-609.87-7.69

151.98^8.24

120.061.35

111.61-357.51

0.02

Sumber: Dikira dari model shift^share

negeri Kelantan telah kehilangan sharewilayahnya sebanyak hampir 32 %6. Jika negeriKelantan dapat mengekalkan tahap persainganwilayahnya, nilai output negeri ini pada tahun1995 boleh mencapai hampir RM3600 juta(Jadual 8). Kajian ini mendapati bahawaperalihan wilayah yang positif dalam subtempoh1980-85 pula tersangat kecil, iaitu lebih kurang0.6% daripada output tahun 1985.

Analisis Setiap Komponen

Daya saing Kelantan sebagai sebuah wilayahdalam ekonomi nasional dapat diukur dengankomponen RS. Lajur ini menunjukkan peralihanwilayah, sama ada Kelantan mempunyaikelebihan wilayah (nilai positif) atau kelemahanwilayah (nilai negatif) berbanding ekonominasional. Ini dilakukan dengan membandingkankadar pertumbuhan output sesebuah sektor yangberlaku di Kelantan dengan yang berlaku diperingkat nasional. Misalnya, sektor pertanianKelantan yang telah berkembang dengan kadaryang lebih perlahan berbanding yang berlaku diperingkat nasional telah mengakibatkan negeriini kehilangan share wilayah sebanyak RM219juta atau 32 %7 daripada output sebenar yangdicapainya pada tahun 1995.

Dalam tempoh keseluruhan, kajian inimendapati bahawa nilai peralihan wilayah adalahnegatif dalam semua sektor, kecuali dalam sektor-sektor perkilangan, perdagangan danperkhidmatan kerajaan; menandakan, kecuali

tiga sektor yang dinyatakan ini, semua sektor diKelantan mengalami kemerosotan sharewilayahnya. Sektor yang mengalami kehilanganshare wilayah yang terbesar ialah sektor kewangan(-146%) manakala sektor yang menikmatikelebihan terbesar dalam share wilayah ialahsektor perdagangan (+59%). Sektor pertanianjuga mengalami kemerosotan share wilayah(-32%) sedangkan kelebihan share wilayah dalamsektor perkilangan adalah kecil (12%).

Subtempoh 1980-85 merupakan tempohyang menunjukkan Kelantan mempunyai dayasaing wilayah, itS-keseluruhannya positif denganbilangan terbanyak sektor yang kompetitif.Subtempoh 1985-90 pula merupakan tempohyang paling tidak kompetitif bukan dari segibilangan sektor yang didapati tidak kompetitiftetapi dari segi nilai output yang hilang,terutamanya dalam sektor pertanian. Dalamsubtempoh tersebut, nilai output yang hilangkerana ketumpulan daya saing wilayah lebihkurang 18% daripada output 1990, sektorpertanian sahaja kehilangan 34% daripadaoutput pertanian 1990. Subtempoh 1990-95 bolehdikatakan tidak menunjukkan perubahan yanglebih baik daripada subtempoh sebelumnya,kehilangan output keseluruhan ialah 12%, tetapisektor pertanian telah berjaya mengurangkankelemahannya dengan merekodkan kehilanganoutput sebanyak 0.6%.

Nilai output Kelantan pada tahun 1995, jikanegeri tersebut dapat mengekalkan share

6 Kehilangan share wilayah dikira seperti berikut: (RS,)/qe dan dikira daripada data dalam Jadual 5 - Jadual 8 danJadual Apendiks. Semua angka peratusan selanjutnya dikira berdasarkan kaedah ini.

7 op. ciL



wilayahnya, ditunjukkan dalam lajur RP. Misalnya,jika sektor pertanian dapat mengekalkan sharewilayahnya, outputnya pada tahun 1995 akanmenjadi RM908 juta. Jika output setiap sektor dinegeri Kelantan dibenarkan berkembangmenyamai dengan kadar pertumbuhan KDNKnasional, paras nilai outputnya pada 1995ditunjukkan seperti dalam lajur A/51. Misalnya,jika sektor pertanian dibenarkan berkembangmenyamai dengan kadar pertumbuhan KDNKnasional, nilai outputnya pada 1995 akan menjadiRM1518juta.

Lajur Aft* pula menunjukkan perubahandalam output sektoral jika ia diandaikanberkembang secepat kadar pertumbuhan KDNKnasional. Misalnya, output sektor pertanian akanmeningkat sebanyak RM954 juta jika iadibenarkan berkembang secepat kadarpertumbuhan KDNK nasional. Jika corakperubahan dalam industry mix (perubahanstruktur) yang berlaku di peringkat nasionaldiandaikan berlaku di negeri Kelantan, outputsetiap sektor negeri ini pada tahun 1995 akanmengalami pertambahan (positif) ataupengurangan (negatif) sebanyak nilai yangterdapat dalam lajur IM. Misalnya, jika negeriKelantan mengalami perubahan industry mixseperti yang berlaku di peringkat nasional, outputpertanian negeri ini pada tahun 1995 akanberkurangan sebanyak RM610 juta. Misalnya,kelambatan pertumbuhan sektor pertanianKelantan berbanding pertumbuhan sektortersebut yang berlaku di peringkat nasional telahmenyebabkan sektor tersebut kehilangan (sharewilayah) output dan kelambatan sektor iniberkembang di peringkat nasional berbandingkadar pertumbuhan KDNK telah menyebabkanoutput sektor tersebut berkurangan. Kedua-duakesan peralihan (total shift) ini telahmenyebabkan output sektor pertanianberkurangan sebanyak RM829 juta dalam tempohtersebut.

Analisis Sektor Pertanian dan Perkilangan

Sektor PertanianOutput sektor pertanian telah berkembangdaripada RM564 juta dalam tahun 1980 kepadaRM689 juta pada tahun 1995, iaitu kadarpertumbuhan tahunan 1.3%; sedangkanekonomi nasional mengalami pertumbuhanpertanian yang lebih pantas, 3.2%. Jika negeriKelantan dapat mengekalkan kadar pertumbuhanpertanian seperti kadar yang berlaku di peringkat

nasional, output pertanian negeri tersebut bolehmencapai RM908 juta.

Kelemahan pertumbuhan sektor ini di negeriKelantan berbanding prestasinya di peringkatnasional telah menyebabkan negeri inikehilangan share wilayahnya sebanyak RM219juta atau 32% daripada nilai output yangdicapainya pada tahun 1995. Kehilangan sharewilayah ini berlaku terutamanya dalam subtempoh 1985-90 (kehilangan share wilayahsebanyak RM215 juta atau 34% daripada outputpertanian 1990), sedangkan dalam subtempohsebelumnya, 1980-85, negeri ini mempunyai dayasaing dalam pertanian dengan kesan wilayahyang positif. Subtempoh seterusnya, 1990-95,walaupun sektor ini masih belum mempunyaidaya saing wilayah namun ia telah berupayamemperbaiki prestasinya dengan mengurangkankehilangan share wilayahnya kepada sebanyakRM3.6 juta atau 0.6% daripada output pertanian1995.

Bukan sahaja prestasi pertanian Kelantanlebih rendah daripada prestasi sektor ini diperingkat nasional, malah prestasi sektor ini diperingkat nasional juga adalah lebih rendahdaripada prestasi ekonomi keseluruhannya. Jikasektor pertanian Kelantan dibenarkanberkembang secepat perkembangan KDNKnasional yang jauh lebih pantas itu, outputpertanian Kelantan pada tahun 1995 bolehmencecah paras RM1518 juta, iaitu pertambahansebanyak RM954 juta. Kehilangan output keranakadar pertumbuhan pertanian Kelantan yanglebih rendah dengan kadar pertumbuhan KDNKberlaku dalam semua subtempoh.

Kadar pertumbuhan yang berbeza di antarasektor-sektor telah menghasilkan perubahanindustry mix atau perubahan struktur. Denganmengandaikan Kelantan mengalami perubahanindustry mix yang serupa dengan yang telahberlaku di peringkat nasional, output pertanianakan berkurangan sebanyak RM610 juta.Perubahan industry mix yang tidak menyebelahipertanian yang paling besar telah berlaku padasubtempoh 1990-95, dan ini telah mengurangkanoutput pertanian Kelantan sebanyak RM256 juta.

Dalam tempoh 1980-95, jumlah outputpertanian gagal berkembang sebanyak RM829juta kerana kesan negatif kedua-dua komponen:komponen peralihan wilayah (output pertaniandi Kelantan kurang daya saing) dan komponenindustry mix atau peralihan struktur (outputpertanian di peringkat nasional berkembang


Ekonomi Negeri Kelantan dan Perspektif Analisis Shift-Share Wilayah

lebih perlahan daripada pertum-buhan KDNKnasional). Fenomena ini amat ketara sekali dalamdua subtempoh yang terakhir, iaitu 1985-90 dan1990-95. Jika dalam subtempoh 1985-90 kesanperalihan wilayah mengatasi kesan industry mix,dalam sub-tempoh 1990-95 pula sebaliknyaberlaku, kesan industry mix mengatasi kesanperalihan wilayah, dalam menggagalkanperkembangan output pertanian. Implikasi dariperkembangan ini ialah jika dalam subtempoh1985-90 kegagalan output pertanian Kelantanlebih berpunca daripada kurangnya daya saingnegeri ini dalam pertanian; dalam subtempohseterusnya ia lebih berpunca daripada perubahanstruktur yang deras di peringkat nasional yangtidak menyebelahi sektor pertanian. Dalamsubtempoh awal pula, 1980-85, kajian inimendapati bahawa kelebihan daya saingpertanian Kelantan adalah terlalu kecilsehinggakan perubahan struktur yang berlakudi peringkat nasional dapat membatalkankelebihan ini.

Sektor PerkilanganOutput sektor perkilangan telah berkembangdaripada RM86 juta dalam tahun 1980 kepadaRM435 juta pada tahun 1995, iaitu kadarpertumbuhan tahunan 11.43 %; sedangkanekonomi nasional mengalami pertumbuhanperkilangan yang perlahan sedikit, 10.5%. Jikanegeri Kelantan mengekalkan kadarpertumbuhan perkilangan seperti kadar yangberlaku di peringkat nasional, output perkilangannegeri tersebut mencapai RM383 juta.

Kelebihan pertumbuhan sektor ini di negeriKelantan berbanding prestasinya di peringkatnasional telah menyebabkan negeri inimeningkatkan share wilayahnya sebanyak RM52juta atau 12% daripada nilai output yangdicapainya pada tahun 1995. Peningkatan sharewilayah ini berlaku hanya dalam dua subtempohyang awal sahaja, sedangkan subtempoh yangterakhir ia telah bertukar menjadi kelemahanwilayah. Dalam subtempoh 1980-85 kelebihanperalihan wilayah adalah sebanyak RM27 jutaatau 19% daripada output perkilangan 1985,manakala dalam subtempoh 1985-90, sebanyakRM36juta atau 12% daripada output perkilangan1990. Subtempoh seterusnya, 1990-95, sektor initelah kehilangan daya saing wilayahnya dengankesan peralihan wilayah yang negatif -RM113juta atau 26% daripada output perkilangan 1995.

Bukan sahaja prestasi perkilangan Kelantan

lebih baik daripada prestasi sektor ini diperingkat nasional, malah prestasi sektor ini diperingkat nasional juga adalah lebih baikdaripada prestasi ekonomi keseluruhannya. Jikasektor perkilangan Kelantan dibenarkanberkembang secepat perkembangan KDNKnasional yang sedikit perlahan itu, outputperkilangan Kelantan pada tahun 1995 bolehmencecah paras RM231juta, iaitu pengurangansebanyak RM214 juta. Kelebihan output keranakadar pertumbuhan perkilangan Kelantan yanglebih tinggi dengan kadar pertumbuhan KDNKberlaku dalam dua subtempoh yang terakhir.

Kadar pertumbuhan yang berbeza di antarasektor-sektor telah menghasilkan perubahanindustry mix atau perubahan struktur. Denganmengandaikan Kelantan mengalami perubahanindustry mix yang serupa dengan yang telahberlaku di peringkat nasional, output perkilanganakan meningkat sebanyak RM152 juta.Perubahan industry mix yang menyebelahiperkilangan telah berlaku pada subtempoh 1990-95, dan ini telah menyebabkan outputperkilangan meningkat sebanyak RM102 juta.

Dalam tempoh 1980-95, peningkatan outputperkilangan RM203 juta lebih disebabkan olehkesan positif industry mix atau peralihan struktur(output perkilangan di peringkat nasionalberkembang lebih perlahan daripada pertum-buhan KDNK nasional) berbanding kesan positifperalihan wilayah (output perkilangan di Kelantanlebih berdaya saing). Iaitu, tiga perempatdaripada peningkatan output perkilangan diKelantan disebabkan oleh perubahan strukturdi peringkat nasional manakala kelebihan wilayahmenyumbangkan bakinya. Analisis kedua-duakomponen ini menurut subtempoh mempamerhasil yang menarik: subtempoh 1980-85menyaksikan Kelantan sebagai lokasi perkilanganyang menarik sehingga dapat mengatasi kesannegatif perubahan struktur di peringkat nasional,subtempoh 1985-90 pula telah menawarkanperkembangan yang paling baik apabilapengekalan daya saing lokasi diperkukuh denganperubahan struktur yang sihat di peringkatnasional, dan akhir sekali subtempoh 1990-95menyaksikan daya saing lokasi Kelantan begituteruk menurun sehingga membatalkanperubahan struktur positif di peringkat nasional.Apa yang dapat dirumuskan dari perkembanganini ialah dalam tempoh 15 tahun ini sedangkanperubahan struktur yang berlaku di peringkatnasional sangat menggalakkan kegiatan



perkilangan keadaan yang sebaliknya pulaberlaku di peringkat negeri dengan negeri inimenyaksikan kehilangan daya saing lokasinya.

RUMUSAN DAN DASAR

Analisis shift-share yang kita bincangkan dibahagian yang lalu mengkaji sama ada Kelantanmempunyai kelebihan lokasi atau kelemahanlokasi dalam proses pertumbuhan ekonominyabagi tempoh 1980-95. Penentuan sama ada negeriini mempunyai kelebihan atau kelemahan lokasidibuat dengan membandingkan Kelantandengan ekonomi nasional. Maka sebagai kajianperbandingan, apabila kajian ini mendapatiKelantan mempunyai kelemahan lokasi bukanlahbermakna kelemahan lokasi secara mutlak tetapisecara bandingan. Kelemahan lokasi ini, antaralain disebabkan oleh faktor-faktor berikut:-

(1) Kelantan mempunyai kemudahaninfrastruktur yang sangat terbatas. Negeri initidak mempunyai pelabuhan. Pelabuhan Kuantandan Pelabuhan Kemaman telah disediakan bagimemberi khidmat kepada pedagang-pedagangyang beroperasi di koridor pantai timur.Begitupun, kedua-dua pelabuhan ini merupakanpelabuhan yang khusus dan tidak mampumengendalikan komoditi-komoditi tertentu.Hanya baru-baru ini sahaja Kelantan disediakandengan pelabuhan darat di Kuala Krai untukmenyokong kegiatan pengeksportan melaluilaluan kereta api. Misalnya, pengimportan danpengeksportan bahan-bahan tekstil dari kilangdi Pengkalan Chepa terpaksa menggunakanperkidmatan pengangkutan darat jalan rayauntuk dibawa ke pelabuhan Pulau Pinang.

(2) Kelantan tidak mempunyai jaringan jalanraya yang mencukupi, walaupun ia merupakansatu-satunya model pengangkutan yangterpenting kepada nadi pembangunan ekonominegeri ini. Jalan raya di kawasan estetperindustrian Pengkalan Chepa tidak disenggaradengan baik dan tidak mempunyai lampu jalan.Ini menjadikan estet perindustrian negeri inikurang menarik. Kekurangan kemudahan initelah meningkatkan kos pengilangan. Pengilangdi Kelantan mengakui bahawa kelebihan kosburuh yang murah tidak dapat dinikmatisepenuhnya kerana kos pengangkutan yangterlalu tinggi boleh mengakibatkan kesan bersihdari kedua-ndua elemen kos ini tidak memihakkepada Kelantan sebagai lokasi yang menarik.

(3) Tambahan pula, Kelantan tidakmempunyai perkhidmatan pengendalian kargo

udara. Kebanyakan pengendalian kargodilakukan melalui jalan raya. Oleh kerana tiadakemudahan pelabuhan dan kemudahan kargoudara, negeri ini tidak memenuhi syarat untukmembina estet perindustrian perdagangan bebascukai (free trade zone, PTZ). Walau bagaimanapun,terdapat beberapa kilang di Pengkalan Cepayang diberikan status Pengilang Berlesen(Licensed Manufacturing Warehouses, LMW) yangmembebaskan mereka dari cukai import daneksport terhadap bahan dan barangan yangdiperdagangkan.

(4) Bekalan air yang cukup dengan kualitiyang boleh diterima oleh para pengilangmerupakan prasyarat kepada sesebuah programperindustrian. Kilang-kilang yang bergantungkepada air, seperti kilang makanan danminuman, kilang kimia dan kilang tekstil,misalnya, sangat sensitif kepada kemudahan ini.Kilang tekstil dyeing, misalnya, memerlukankualiti air yang tinggi untuk mendapatkan warnacelupan yang diingini. Kilang minuman ringandi Pengkalan Chepa yang sepatutnya bolehmengilang air minuman, kini terpaksa berpuashati dengan melakukan kegiatan sebagai stokissahaja. Ini berlaku kerana bekalan dan kualitiair yang ada di negeri Kelantan jauh daripadamemuaskan.

(5) Kelantan mempunyai simpanan gas asliyang banyak di pesisir pantainya. Gas aslimempunyai potensi nilai komersil yang amatberharga dan merupakan hanya satu-satunyajalan pintas dan harapan yang ada untukmengubah landskap ekonomi negeri ini. Olehkerana negeri ini tidak mempunyai kemudahanasas untuk menyalurkan gas tersebut ke pantai,beberapa kemudahan asas telahpun dirancanguntuk menyalurkan gas asli tersebut ke PantaiSenok, yang seterusnya dapat memajukanperindustrian petrokimia khususnya dan industri-industri lain amnya di negeri ini.

(6) Industri di negeri Kelantan lebihberintensifkan buruh berbanding yang terdapatdi pantai barat Semenanjung Malaysia. Dasarnegara dalam peletakan industri, walaupunbersesuaian dengan matlamat perancangannasional tetapi memberi kesan yang tidak diinginidalam perancangan wilayah. Dasar yangmenempatkan industri berintensif modal dipantai barat semenanjung dan industriberintensif buruh di pantai timur semenanjungtelah menetapkan syarat bahawa penempatankilang di koridor pantai barat hanya jika nisbah



modal-buruhnya melebihi RM55,000, jika kurangdaripada jumlah itu kilang akan ditempatkan dikoridor pantai timur.

(7) Dasar peletakan semula industri ini bolehkita fahami - pantai barat semenanjung yangkekurangan buruh mestilah menggalakkanoperasi yang berintensifkan modal dan sebaliknyapantai timur semenanjung yang mempunyaikelebihan buruh secara relatif mestilahmenggalakkan operasi yang berintensifkanburuh. Kelantan yang berada di pantai timurdan yang mempunyai ramai buruh secara relatifberserta dengan harganya yang lebih murah,tentu akan menarik kegiatan perkilangan yanglebih berintensifkan buruh. Keadaan seperti inisedang berlaku dan natijah daripadanya ialahindustri negeri Kelantan secara bandingan lebihberintensifkan buruh, dan seterusnya mempunyaiproduktiviti buruh yang rendah. Walaubagaimanapun, dasar ini perlulah dilaksanakandengan bijaksana agar ia tidak bercanggahdengan dasar pembangunan wilayah.

(8) Kelantan kurang dapat meyakinkan parapelabur bahawa negeri ini dapat menawarkanperkhidmatan sokongan yang cekap danmemuaskan. Kerenah birokrasi yang meyulitkanhasil daripada gangguan pentadbiran dan politikyang terdapat dalam jentera pentadbiranmenjadikan banyak program yang bolehmerangsang pembangunan tidak dapatdilaksanakan.

(9) Kelantan menawarkan harga tanahperindustrian yang secara bandingan lebihmurah (harga tanah perindustrian di PengkalanChepa ialah RM4.50 sekaki persegi atau RM45semeter persegi). Walau bagaimanapun, negeriini sudah tidak mempunyai kawasan perin-dustrian yang masih kosong, namun ia masihcuba memajukan Kelantan sebagai destinasiperindustrian. Kawasan perindustrian baru telahdicadangkan, tetapi belum berhasil diwujudkankerana kekurangan tanah milik kerajaan yangsesuai ditambah dengan birokrasi yangmenyulitkan bagi mendapatkan tanahpersendirian. Bakal-bakal pengilang, padaumumnya, tidak tertarik dengan lokasi kilangyang berada di luar kawasan perindustrian keranaketiadaan infrastruktur yang bersepadu yangdicadangkan kepada mereka.

Dasar pembangunan ekonomi negeriKelantan haruslah dinilai dalam kontekspembangunan wilayah. Dalam kaitan ini,pembanguan ekonomi negeri ini haruslah

dirancang agar ia tidak tertinggal jauh dari arusperdana pembangunan ekonomi nasionaldengan memastikan sumber-sumber keluarannegeri digunakan secara cekap. Untuk mencapaidasar pembangunan ini strategi-strategi yangboleh dicadangkan ialah:

(1) Mempergiat usaha memajukan sektorperkilangan selaras dengan kerancakanpembangunan perkilangan di peringkat nasional.Ini dapat dilakukan dengan mengenal pastisektor-sektor strategik (niche) yang mempunyairantaian yang kuat dengan sektor-sektor lain.Kajian awal mendapati kegiatan-kegiatanperkilangan berasaskan kayu dan barangan kayu,petrokimia dan barangan kimia merupakansektor-sektor strategik. Selaras dengan dasar inikerajaan negeri haruslah meningkatkanproduktiviti buruh dengan memperbaiki tahappendidikan dan latihan dan menggunakan teknikpengeluaran berintensifkan modal danberteknologi tinggi.

(2) Menjadikan Kelantan sebagai satudestinasi pelaburan yang menarik. Ini dapatdilakukan dengan memperbaiki prasarana fizikal,termasuk meningkatkan taraf jalan-jalan raya,membekalkan kuantiti dan kualiti air yang bolehditerima oleh para pengilang, menaikkan taraflapangan terbang Kota Bahru kepada tarafantarabangsa agar ia dapat mengendalikan kargosecara lebih berkesan, dan menyediakan ZonPerdagangan Bebas.

(3) Menggiatkan sektor utama denganmengekal dan memulihkan kelebihan bandinganyang ia miliki dalam kegiatan sektor utama(primary), khususnya dalam sektor-sektorpertanian dan penternakan. Ini dapat dilakukandengan mengamalkan teknik pengeluaranmoden dan komersial dalam kedua-dua sektortersebut. Sektor tersebut harus mengubahkomposisi produk pertanian denganmengamalkan pendekatan yang lebih komersialdan menjadikan negeri Kelantan sebagai"Jelapang Makanan" dengan menggiatkan usahapertanian dan penternakan yang dapatmenambah bekalan makanan.

(4) Meningkatkan kemudahan sosial denganmeningkatkan peruntukan perbelanjaan yanglebih besar ke arah penyediaan perkhidmatansosial yang setanding dengan negeri-negeri lain.

Pembangunan ekonomi yang dinikmatidalam dekad-dekad yang lalu adalah hasildaripada kerjasama kerajaan-kerajaan negeri danpusat dalam menggubal dan melaksana program-



program pembangunan. Galakan yang disediakantelah berjaya merangsang sektor swasta terlibatsama dalam memajukan ekonomi negeri.Pembangunan ekonomi negeri Kelantan padamasa akan datang haruslah berteraskanmeningkatkan kerjasama yang telah sedia terjalinagar ketidakseimbangan pembangunan ekonominegeri ini dalam pembangunan nasional dapatditangani dengan baik.

RUJUKAN

ANDRIKOPOULOS, A., J. BROX dan E. CARVALHO. 1990.

Shift-share Analysis and the Potential for PredictingRegional Growth Patterns: Some Evidence for theRegion of Quebec, Canada. Baltimore: JohnHopkins.

BENJAMIN, H. S. dan L. M. CRAIG. 1980. A critical

review of the literature on shift-share as aforecasting technicques. Journal of RegionalScience 20(4) Nov.: 419-38.

BROWN, H. J. 1969. Shift and share projections ofregional economic growth: an empirical test.Journal of Regional Science 12(1): 15-25.

FRANKLIN, J. Jr. dan Jr. HUGHES. 1973. A test of shiftshare analysis as a predictive device. Journal ofRegional Science 72(1): 47-65.

HANNU TERVO dan PAAVO OKKO. 1983. A note on

shift-share analysis as a method of estimatingthe employment effects of regional policy,Journal of Regional Science 23(1): 115-125.

HENRY W. HERzoG,Jr. d a n j . O. RICHARD. 1977. Shiftshare analysis revisited: the allocation effectand the stability of regional structure. Journalof Regional Science 17(3): 441-454.

PERLOFF, H. S. et al. 1960. Regions, Resources andEconomic Growth. Baltimore: John Hopkins.

UNIT PERANCANG EKONOMI. Rancangan Malaysia LimaTahun dan Kajian Semula Separuh PenggalRancangan Malaysia Lima Tahun, PelbagaiTahun.

UNIT PERANCANGAN EKONOMI NEGERI KELANTAN. 1997.

Kelantan Socio-Economic Profile. 1997.

UNIVERSITI PUTRA MALAYSIA. 2000. Pelan StrategikPembangunan Negeri Kelantan.

WEE, C. H. dan P. W. WONG. 1987. Identifyingexport opportunities for Singapore firmsthrough shift share analysis. Marketing Review.

(Diterima: 5 Januari 2001)



APENDIKSKeluaran Dalam Negara Kasar (KDNK) Kelantan dan Malaysia 1980 - 2000

(RM juta - mengikut harga tahun 1978)

Kelantan Malaysia

Sektor 1980 1985 1990 1995 2000* 1980 1985 1990 1995 2020*

PertanianPerlombonganPerkilanganPembinaanPengangkutanPerdaganganKewanganPerkhidmatan Kerajaan

564 683 626 689 783 10189 12046 14827 16406 1766411 15 16 17 15 4487 6006 7757 8938 794986 137 294 435 666 8932 11357 21340 39825 6358960 87 73 112 166 2066 3048 2832 5277 8302115 155 182 265 399 3108 4793 7013 11610 1837091 119 239 386 629 5383 7551 8806 14568 21549139 187 138 197 279 3687 5212 7758 12884 20136271 403 457 635 828 7876 9331 8996 10808 19077

Jumlah 1337 1786 2025 2736 3765 44702 59344 79329 120316 176635

Sumber : Rancangan Malaysia Lima Tahun, Pelbagai Tahun Unit Perancang Ekonomi (EPU)Nota : * Anggaran oleh EPU



Predictability of ASEAN-5 Exchange Rates in the Post-Crisis Era

LJEW KHIM SEN 8c AHMAD ZUBAIDI BAHARUMSHAHDepartment of Economics, Faculty of Economics and Management,

Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor, Malaysia

Keywords: Exchange rate, depreciation, ARIMA, ARFIMA, forecasting

ABSTRAK

Lima mata wang ASEAN telah diselidiki demi menentukan sama ada pertukaran wang asingnegara tersebut selepas krisis kewangan lebih tepat diramal oleh dolar US ataupun yen Jepun.Keputusan kajian ini mencadangkan kesemua pertukaran asing sebelum berlakunya KrisisKewangan 1997/1998 lebih tepat diramal oleh mata wang dolar US. Mata wang Singapura selepaskrisis lebih tepat diramal oleh dolar US, sementara mata wang ASEAN yang lain lebih tepatdiramal oleh yen Jepun.

ABSTRACTFive ASEAN currencies are investigated in an attempt to determine whether the post-crisis ASEANexchange rates are more predictable by the US dollar or Japanese yen. Results suggest that priorto the 1997/1998 Financial Crisis, all exchange rates were better predicted by the US dollar asthe base currency. The post-crisis Singapore exchange rate continues to be better predicted in USdollar. On the other hand, Japanese yen better predicted other post-crisis ASEAN exchange rates.

INTRODUCTIONExchange rates play an important role in theinternational trade because they allow us tocompare prices of goods and services producedin different countries. One of the characteristicsof exchange rate in the post-Bretton Woods erais that it tends to be more volatile than themacroeconomic (fundamental) variables. Thefluctuations in exchange rates due to the changesin the market fundamentals and marketexpectations have damaging effect on lessdeveloped countries (LDCs) trade flows (Ianand Amusa 2002; Law and Tan 2000; Arize et al2000). These fluctuations have crucial impacton decisions of policy-makers, traders,speculators, households and firms. Hence, it isimportant to forecast the future exchange rateswith some accuracy. Unfortunately, exchangerates are difficult to forecast with any precisionand empirical evidence has so far proven illusive

(Meese and Rogoff 1983a,b; Berkowitz andGiorgianni 1997). This is simply becauseeconomic factors that affect exchange ratesthrough a variety of channels are complex andmeasurements are either costly or problematicin nature (Carbaugh 2000).

In the past decades, many researchers whoseek to predict exchange rates by econometrictechniques have faced the same problem: whilethe results help to explain the past movementsof exchange rates, the number of explanatoryvariables introduced on the right-hand side ofthe equations make them difficult to use forprojection (Six 1989). To overcome this difficulty,various attempts had been made by employingadvanced time-series analysis to gain furtherinsights into the properties of exchange rateseries. We note that, to this date, there is noclear superiority of time series analysis over othereconometric analysis or vice-versa1.

Earlier work of Wallis (1982), Lupoletti and Webb (1986), Litterman (1986), Keller (1989), Montogomery et al.(1990), Brooks (1997), Berkowitz and Giorgianni (1997), Palma and Chan (1997), Fildes et al (1998) and othershas demonstrated the superiority of (linear) time series model over other econometric models in terms of theirpredictability. However, recent empirical evidence shows mixed conclusion. For instance, Najand and Bond (2000),and Darbelly and Slama (2000), among others, suggest that advanced econometric models are able to outperformlinear time series models. Nevertheless, Sarno (2000), Baum et al (2001), Clement and Smith (2001) and othersusing nonlinear frameworks have rekindled the usefulness of time series analysis.

Liew Khim Sen & Ahmad Zubaidi Baharumshah

In this study, we dealt with the forecastingof the exchanges rates by employing the ARIMAmodel since ARIMA modelling is deemed oneof the most powerful approaches to the solutionof many forecasting problems.2 Besides utilisingthe point forecasts, we also generate intervalforecasts of ARIMA model, which are oftenneglected in comparing forecast performance(Melard and Pasteels 2000). The seminal paperby Palma and Chan (1997) shows that ARFIMAmodel can produce predictions that are moreefficient and reliable. For this reason, this paperalso attempted to fit ARFIMA to our exchangerate of the ASEAN-5 countries series.

The remainder of this paper is organized asfollows. The next section briefly explains theexchange rate system of the ASEAN-5. This isfollowed by brief descriptions of the data andmethodology employed in our analysis of theexchange rate time series. Results and discussionsare presented before we conclude in the finalsection.

EXCHANGE RATE SYSTEM IN ASEAN-5

In this study we attempt to model the currenciesof five neighbouring ASEAN countries -Singapore, Malaysia, Thailand, Indonesia andthe Philippines. The ASEAN-5 can be classifiedinto two broad categories according to the IMF'sclassification. The first group of countries, namelySingapore, Malaysia and Thailand are classifiedto have exchange rates pegged to a basket ofcurrencies or to a single currency. The secondgroup, namely, Indonesia and the Philippinesfollow a managed float during the period ofinvestigation. However, our data revealed thatIndonesia pursued a mixed policy of peggingagainst the US dollar. The time plot of therupiah against the US dollar displays the RP/USD rate is ladder-like and has an upward trendand with three large devaluations in 1978, 1983and 1986. The exchange rates of Singapore,Malaysia and Thailand appear quite stable priorthe 1997 financial crisis. After two largedevaluations in 1981 and 1984, the Thais bahtwas pegged to US dollar and fluctuates narrowlywithin a small range. The Singapore dollarappears to be most stable among the fivecurrencies. The Monetary Authority of Singapore

(MAS) frequently intervenes the exchange rateto keep the Singapore dollar within a rangedetermined by a basket of currencies set on ahorded weighted basis.

In the midst of 1997, the declaration ofinsolvency of various financial institutions inThailand followed by the failure of a large Koreanconglomerate, South Korea together with 4ASEAN countries, namely Malaysia, Indonesia,Thailand and the Philippines were in trouble(Dunn and Mutti 2000). Currencies of thesecountries plunged to its record low. For instance,Indonesian rupiah was more than 80 percentdown against the U. S. Dollar, and the currenciesof Thailand, South Korea, Malaysia and thePhilippines all dived by 35 to 50 percent(Carbaugh 2000). However, the Singapore dollarappears to be largely unaffected by the crisis. Tomitigate the sharp depreciation of exchangerate, Malaysia choose to fix the ringgit at RM3.80to USD1 on 2 September 1998, while otherASEAN countries maintain their exchange rateregime as before.

DATA DESCRIPTION

The exchange rate series considered in thepresent study are Malaysian ringgit (RM),Indonesian rupiah (RP), Thai baht (BAHT),Philippines peso (PESO) and Singapore dollar(SD), all denominated in US dollar (USD) aswell as the Japanese yen (YEN). It is well knownthat both the US and Japan are the two largestASEAN trading partners. Each series, consists of114 quarterly observations running from 1971:Ql to 1999: Q2, is divided into two portions forthe purpose of this study. The first 106observations beginning in 1971: Ql and endedin 1997: Q2 (before Asian Financial Crisis) areused to fit the model, while the remainingobservations from 1997: Q3 to 1999: Q2 (post-crisis period) are kept for the out-sampleforecasts. Our quarterly exchange rate data areaverages of the underlying monthly data. In thisstudy, we examine the predictive power of ourmodel during the post-crisis period. We vieweda good model as model that can produce anaccurate forecast. It is worth pointing out herethat the presence of a break in the trend (duethe crisis) during the forecasting period would

For instance, the development of automauc ARIMA modeling expert system by Melard and Pasteels (2000) certainlyreflects the usefulness of ARIMA models.



make the prediction exercise more difficult.Similar view is found in Garcia-Ferrer et al(1997).

METHODOLOGYThe process of time series modeling involvestransformation of data in order to achievestationarity, followed by identification ofappropriate models, estimation of parameters,model checking and finally forecasting.Generally, a univariate time series could beexpressed in the Autoregressive IntegratedMoving Average, ARIMA (p, d, q) specification(see for example Brockwell and Davis 1996, 178-200) :

{\-B)dYt =

where

e. =

(1)

observations at time g * = 1, 2, ..., Tnumber of differencing performed,autoregressive parameters to beestimated; i = 1, 2, ..., p.moving average parameters to beestimated; i = 1, 2, ..., q.

= Yt_. and \ir iid (0, o2).

The process as defined in (1) is a weaklystationary process. A weakly stationary process isa process with constant mean and covariance. Ifa non-stationary series is transformed to astationary series by using classical decompositionapproach, rather than method of differencing,we have Autoregressive Moving Average, ARMA

(p, q) model, i.e., d= 0 in equation (1). For non-integer d, (1) becomes fractionally intergratedautoregressive moving average, ARFIMA model.We employed 'Iterative Time Series Modeling(ITSM)' (Brockwell et al 1996) to estimate themodel.3 For more detailed on these models andtheir important characteristic, the readers arereferred to Brockwell and Davis (1996).

We have fitted 6 to 12 tentative models toeach set of data. Various methods, which areavailable in FTSM, had been employed to checkthe appropriateness of the specified models.4

The out-sample forecasting performance of theappropriate models for each data set is thenstudied using root mean squared percentageerror (RMSPE), mean absolute error (MAE)and mean absolute percentage error (MAPE). Abest-fitted model was then selected using theminimum MAPE criterion.5 Finally, theperformance of models for exchange ratesdenominated in US dollar was compared withmodels of the corresponding rates denominatedin Japanese yen.

RESULTS AND DISCUSSIONSTable 1 presents the empirical results of the bestfitting model for each of the transformed zero-mean stationary foreign exchange rate series.These models have passed through a battery ofdiagnostic tests and thus are appropriate for theforecasting purpose of this study.6 These modelsare utilized to generate eight out-of-samplequarterly exchange rate values (1997: Q3 to1999: Q2).

Briefly, the ITSM estimation procedures involved (1) the transformation of non-stationary series into stationary seriesvia differencing or variance decomposition; (2) the estimation of autoregressive or/and moving average parameters;(3) diagnostic checking; and (4) forecasting. ITSM allows us to model the transformed series for the purpose offorecasting the original series.They include the examination of ACF and PACF of residuals, Ljung-Box (1978) Q^tatistic, McLeod-Li (1983) Q:statistic, Turning Point Test, Difference-Sign Test and Rank Test. Only models that have passed all these diagnostictests are kept for forecasting.We used MAPE criterion instead of other criteria like FPE, BIC and AICC — which are also available in ITSM —for model selection for several reasons. FPE or Final Prediction Error criterion is asymptotically inconsistent becausethere remains a non-zero probability of overestimating the order of a model as the sample size grows indefinitelylarge (Akaike 1970; Beveridge and Oickle 1994). Bayesian Information Criterion or BIC, although is consistent, isfound to be not asymptotically efficient (Hurvich and Tsai 1989; Brockwell and Davis 1996). On the other hand, thebiased-corrected Akaike's Information criterion, AICC, while having a more extreme penalty to counteract thetendency of overfitting, as well as the property of asymptotically efficient, it was noted (Lalang et al. 1997; Shitan andLiew 2000) that the minimum AICC model does not have to be the best model in term of forecast accuracy. Inaddition, Liew and Shitan (2000) had found empirical evidence to suggest that minimum AICC model picks up thetrue model for only 62.63% of the time. Nevertheless, the most fatal deficiency in these criteria is that they are notsuitable for inter-series comparison — the main purpose of this study.Results are not reported here but are available upon request from authors.


F. E. Rate


TABLE 1Best fitting model for each foreign exchange rate (1971: Ql - 1997: Q2)

Model3 Equationb var (\i)c

RM/USDRP/USDBAHT/USDPESO/USDSD/USD

RM/YEN

RP/YENBAHT/YEN

PESO/YEN

SD/YEN

ARIMA (0,2,0)ARIMA (0,2,1)ARIMA (0,1,0)ARIMA (0,1,0)

ARFIMA(6, 0.2105, 0)ARMA (5, 0)

ARIMA (0,2,0)ARMA (5, 0)

ARMA (10, 0)

ARIMA(LLO)

RM(= RM( 2 + \it 1.000RP (- RP( '" + \it - 0.99u^ 3396BAHT( = BAHT, , + \it 0.249PESO(= PESO( \ + \it 0.640SD(= 0.756SD(_ ; + 0.046SD^ 2 - 0.003SD( _3 + 0.045SD, 4 0.028+ 0.014SD( r 0.012SD( 6 + \i(

RM(= 1.081RMr 7 - 0.326RM, 2 + 0.3884RM(_J - 0.000d

0.144RM( 4 - 0.164RM( _5 + u"(RP(= RP( 2 + \it 1.339BAHT( = 'l.032BAHT( ; - 0.304BAHT( f + 0.365BAHT(_3 0.000d

- 0.037BAHT( 4 - 0.241BAHT( 3 + \it

PESO,= 1.118PESO( , - 0.368PESO( 2 + 0.150PESO(_3 0.000d

+ 0.327PESO, 4 - 0.592PESO( 5- 0.227PESO^ -0.280PESOt ~- 0.479PESO, ~+ 0.412PESO( 9 -0.245PESO, w + \it

SD = 0.210SDf , + u 0.000d

Notes: a Specifications of models for the original series.bWe report the equation for each transformed zero-mean stationary series as given by ITSM.c residuals variance, var (\it) depends on the size of the exchange rate values.d var (\L() is very small in value.

The eight actual and forecasted exchangerate values are plotted in Figs. 1 and 2 togetherwith the forecast intervals. Bearing in mind thatin using any fitted model for forecasting, weassumed the economic fundamentals during theforecasting period remain the same as before. Ifthis assumption holds, 95% of the actualexchange rate during this forecasting period liesinside our forecast interval. In other words, theactual observations would be what we haveexpected. Otherwise, the forecast interval fails tocontain the actual observations; thereby implyingthe underlying assumption of "economicfundamentals remain the same" is not valid. Insuch a case, we have indirectly shown that theeconomic fundamentals during the forecastingperiod have changed. As revealed by Fig. i, theonly forecast interval that managed to containthe actual observations is the SGD/USD(Fig, la). This finding shows formally that, withthe exception Singapore, the economicfundamentals of all ASEAN-5 countries withrespect to US are affected by the recent financialcrisis.

The best fitting model for SD/USD rate,ARFIMA (6, 0.2105,0) model had RMPSE valuesof 0.00014. Furthermore, the actual observationshad the correct trend of depreciation over thefirst 2 years following the crisis, as predicted.

Nevertheless, the ARFIMA (6, 0.2105,0) modeltends to overestimate the strength of Singaporedollar (Fig. la).

Judging from the plots of Indonesia rupiah(Fig. lb), Thailand baht (Fig. 1c) and thePhilippines peso (Fig. Id), these countriesapparently had a different economic structureafter the crisis, as their actual exchange ratesduring the forecasting period (after crisis) aretotally beyond our expectation. Moreover, allthese 3 currencies experienced an unexpectedlysharp depreciation, suggesting that thesecurrencies were badly affected by the crisis. Forthe case of Malaysia, ringgit denominated in USdollar (Fig. le) had also experienced a worse-than-expected depreciation within the first yearafter the crisis.

By comparing Figs. 1 and 2, we find that ingeneral, the forecasts using models based onyen outperformed the models based on USdollar. Fig. 2a showed that the forecasted valuesof Singapore dollar denominated in yen fall inthe 95% confidence interval. Singapore dollar isthe only currencies in the sample that remainpredictable in both US dollar and Japanese yenbases models. It is worth noting here that theSingapore dollar was not affected by the recentcurrency crisis.



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Uew Khim Sen & Ahmad Zubaidi Baharumshah

Figs. 2b, 2c and 2d revealed that the first twoquarters after the crisis for the predicted peso,baht and the ringgit failed to be in the 95%confidence interval. Specifically, the modelsmispredict by more than 25% in the short term.Specifically, the models consistently over-predictsyen and dollar rate when it is used as thereference currencies in the short term.7 Wenoted that the out-sample forecasts are within95% confidence level after the third quarter,suggesting that our model based on Japaneseyen is more appropriate in the medium to longterm. As for rupiah, although model based onyen (Fig. 2e) performed better than that of USdollar, only the forecast after 7-quarter horizonfall in the 95% confidence interval. TheIndonesia rupiah performed poorly in both themodels. This finding is true due to the politicalturmoil that followed after the financial crisis.8

The performance of models based on USdollar and Japanese yen as determined by theroot mean square percentage error (RMSPE) issummarised in Table 2. Two importantconclusions may be drawn from this table. Firstly,a quick flash at the overall results showed that,the performance of the best fitting models haddeteriorated in the post-crisis period. Uponcomparing the performance term by term, it isclear that in fact all the models did not turn outto be as predictive as they were. As we havenoted earlier, this phenomenon might beattributed to the set in of the Asian Financial

The second obvious feature in Table 2 isthat models (except for Singapore dollar)denominated in Japanese yen outperformed theircounterparts in the post-crisis period. Inparticular, quoted per US dollar, the RMSPE forringgit, peso, rupiah, and baht were 0.00269,0.00503, 0.00640, and 0.00340 respectively. Thesevalues were much higher than theircorresponding values based on yen, i.e. 0.00103,0.00086, 0.00621 and 0.00039 respectively. TheRMSPE for SD/USD and SD/YEN were 0.00047and 0.00064 respectively. However, for the pre-crisis period, obviously the US dollardenominator is better than the Japanese yen.This is because by the RMSPE all the exchangerates based on US dollar denominator hadperformed better prediction.

The correlation between the actualobservations of each exchange rate series andtheir corresponding best fitting model'spredicted values is depicted in Table 3. All thecorrelations for pre-crisis period are significantat 1% level, with values ranging from 0.887 forthe case of RM/USD rate, to 0.997 for the caseof RP/USD rate. However, for the post-crisisperiod, only 40% of the computed correlationsare significantly at 5% level. These include RM/YEN (0.739), PESO/YEN (0.714), SD/YEN(0.734) and SD/USD (0.748) rates. This decreasein the degree of correlation for the post-crisisperiod is synonym to the deterioration of theperformance of the model in terms of tracking

crisis.

TABLE 2RMSPE of best-fitting models for various exchange rates

Forecast Period51

US dollar-basedPre-CrisisPost-CrisisJapanese yen-basedPre-CrisisPost-Crisis

RM

0.000390.00269

0.000610.00103

PESO

0.000070.00503

0.000610.00086

CurrenciesRP

0.000080.00640

0.000700.00621

SD

0.000140.00047

0.000640.00064

BAHT

0.000080.00340

0.000620.00039

Note. a Pre-crisis and post-crisis periods refer to the periods 1971: Ql to 1997: Q2 and 1997: Q3 to 1999: Q2respectively.

This coincides with the speculator attack that started with the Thai bath in July 1997. By the end of 1997, the Asiancurrency crisis solved the retinal currency of Thailand and Indonesia.Most of the currencies like Thai Bath became relatively stable in 1998, the Indonesian rupiah continue on itsdepreciation trend due mainly to political disturbance.



TABLE 3Correlation between actual values and predicted values*

Forecast Periodb

RM PESOCurrencies

RP SD BAHT

US dollar-basedPre-Crisis 0.887 (0.000) 0.995 (0.000) 0.997 (0.000) 0.989 (0.000) 0.989 (0.000)Post-Crisis 0.406 (0.318) 0.433 (0.283) 0.357 (0.385) 0.748 (0.033) -0.428 (0.291)Japanese yen-basedPre-Crisis 0.991 (0.000) 0.994 (0.000) 0.989 (0.000) 0.976 (0.000) 0.993 (0.000)Post-Crisis 0.739 (0.036) 0.714 (0.047) 0.435 (0.281) 0.734 (0.038) -0.224 (0.594)

Notes: a Values in brackets are p-values.b See Table 2.

the movement of the exchange rates in the post-crisis period.

Table 3 also showed that the ringgit, peso,rupiah and baht but not for Singapore dollar,could be better predicted by YEN for the post-crisis period. This is consistent with resultsreported earlier. The correlations for the RM/YEN, PESO/YEN, RP/YEN and BAHT/YEN ratesare respectively 0.739, 0.714, 0.435 and -0.224and are higher than their correspondences, i.e.0.406, 0.433, 0.357 and -0.428. The correlationfor the SD/USD rate (0.748) is higher than SD/YEN rate (0.734), however.

To sum, with the exception for Singaporedollar, the forecasting performance of all othermodels for ASEAN currencies denominated inyen had outperformed those denominated inUS dollar.

CONCLUSIONThe purpose of this paper is to investigatewhether ASEAN exchange rates are morepredictable by US dollar or Japanese yen in thepost Asian Financial Crisis era. Results suggestthat all exchange rates are better predicted bythe US dollar prior crisis. In the post-crisis period,Singapore dollar continues to be better predictedwhen denominated in US dollar. On the otherhand, Japanese yen better predicted other post-crisis ASEAN exchange rates. One majorimplication of this study is that exchange rateforecasters, who are interested to trace themovement of exchange rates, may resort to YENas a better predictor of post - crisis ASEANexchange rates.

ACKNOWLEDGEMENTS

We are indebted to two anonymous referees fortheir valuable comments and suggestions. The

authors acknowledge the financial support fromshort term fundamental research fund (ProjectNo: 06-02-02-0098s). Any other remaining errorsare our responsibility.

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40 Pertanika J. Soc. Sci. & Hum. Vol. 11 No. 1 2003


Is MYR/USD a Random Walk? New Evidence from the BDS Test

•KP. LIM, 2M. AZALI 8c ̂ .A . LEEiLabuan School of International Business and Finance

Universiti Malaysia Sabah, P.O. Box 8059487015 W.P. Labuan, Malaysia

2Department of EconomicsFaculty of Economics and Management

Universiti Putra Malaysia43400 UPM Serdang, Selangor, Malaysia

Keywords: Random walk, BDS test, Malaysian foreign exchange market

ABSTRAKKajian ini menyiasat secara empirikal hipotesis pergerakan rawak ke atas data harian pulangankadar pertukaran MYR/USD. Peningkatan kuasa-guna komputer ditambah dengan kemajuandalam dinamik tak linear dan kios, telah membantu penyelidik untuk memeriksa semulakebarangkalian jumpaan yang lebih kompleks bentuk pergantungan ke atas siri rawak. Kajian initelah menggunakan alat statistikal seperti Brock-Dechert-Scheinkman untuk menguji sama adasiri pulangan kadar pertukaran MYR/USD mempunyai sifat-sifat taburan bebas dan kesamaan.Keputusan kajian menolak hipotesis dan menunjukkan bahawa siri MYR/USD adalah tidak rawak,saling bergantungan dan ketidaksamaan. Ini menunjukkan bahawa siri ini tertakluk kepada patenaliran pusingan turun-naik, Implikasi kajian ini menunjukkan bahawa kedapatan keberkesananpasaran yang lemah terhadap penentuan struktur siri pulangan kadar pertukaran wang asingMYR/USD.

ABSTRACTThis study empirically investigates the daily MYR/USD exchange rate return series in the light ofthe random walk hypothesis. Recent breakthroughs pertaining to non-linear dynamics and chaos,coupled with the rapid acceleration in computer power, have made it possible to more robustlytest for the random walk in financial and economic data. This study uses a new non-linearstatistical test, namely the Brock-Dechert-Scheinkman (BDS) test to examine whether the MYR/USD exchange rate return series are random walk with the property of being independent andidentically distributed. The results overwhelmingly reject the hypothesis that the MYR/USD dataexamined in this study are random, independent and identically distributed since some cycles orpatterns show up more frequently than would be expected in a true random series. These resultsmay have implications for the weak form market efficiency, if the underlying structure can beprofitably exploitable, which remains an avenue for further research.

INTRODUCTIONNumerous efforts have been made to understandthe behaviour of exchange rates. The study ofthe foreign exchange market has become evenmore important in the post-Bretton Woods era.Since the inception of the floating exchangerate regime in 1973, most currency exchangemarkets have experienced continuous andsometimes dramatic fluctuations and volatility.The Malaysian ringgit, which is the focus of this

paper, has been no exception, especially sincelate 1997 when a currency crisis swept theeconomies of South East Asia.

In the early treatments of the efficientmarkets hypothesis, the statement that thecurrent price of a security 'fully reflects* availableinformation is assumed to imply that successiveprice changes are independent. Furthermore, itis usually assumed that successive changes areidentically distributed. Together, the two

Kian-Ping Lim, M. Azali & Hock-Ann Lee

hypotheses constitute the random walk model(Fama 1965).

A time series, X̂ is said to follow a randomwalk if the change in X(, from one period to thenext is purely random, that is, if we have:

(1)

where fxt is completely random, displaying nopattern over time. A purely random process iswhat statisticians call 'independently andidentically distributed', such as a Gaussian withzero mean and constant variance.

Over the years, there has been an explosionof empirical research on the random walkbehaviour of exchange rates. The consensus ofpublished empirical research was that a randomwalk described prices fairly well, though someanomalies have been reported (Cornell 1977;Mussa 1979; Frankel 1981; Meese and Rogoff1983; Newbold et al 1998). The motivation forthis line of inquiry was at least twofold. First,assumptions in statistical tests and many assetpricing models often include observations whichare independent and identically distributed(i.i.d). Thus, for valid inferences to be drawnfrom a statistical test, this statistical assumptionof i.i.d. must be met. Second, most of the earlierempirical studies hypothesized random walkbehaviour to test the efficiency of foreignexchange markets. A random walk series impliesthat the market is weak-form efficient. Since newinformation is deemed to come in a randomfashion in an efficient market, changes in pricesthat occur as a consequence of that informationwill seem random. Thus, investors in weak-formefficient market cannot expect to find anypatterns in the historical sequence of exchangerates that will provide insight into future ratemovements and allow them to earn abnormalrate of return. However, if the hypothesis of arandom walk is rejected, it would be a strongstatement to conclude that market is inefficient1.

The characterization of an exchange ratereturn series as random in nature has beenquestioned in recent times by the application ofnew non-linear statistical tests. Interest in thesenon-linear techniques is based on the assumption

that highly complex behaviour that appears tobe random is actually generated by an underlyingnon-linear process. The evidence that non-linearity abounds in financial time series hasfurther sparked the interest of many researchersand contributed to the growth in this area (Hsieh1989, 1991; Scheinkman and LeBaron 1989; DeGrauwe et al 1993; Abhyankar et al 1995; Steurer1995; Brooks 1996; Barkoulas and Travlos 1998;Opong et al 1999). With these breakthroughs innon-linear dynamics and chaos, coupled withthe rapid acceleration in computer power, it ispossible to test for the random walk hypothesismore robustly. Thus, this has promptedresearchers to re-examine the possibility ofuncovering a more complex form ofdependencies in the underlying financial timeseries that often appear completely random tostandard linear statistical tests, such as serialcorrelation tests, non-parametric runs test,variance ratio test and unit root tests.

A survey of the literature disclosed that alarge number of studies have applied these newnon-linear statistical tools to test whetherexchange rates are random walk (Hsieh 1989;De Grauwe et al 1993; Steurer 1995; Brooks1996; Mahajan and Wagner 1999). However, itwas observed that while major currencies ofJapanese yen, US dollar, British pound, andGerman deutschmark have received substantialattention from researchers, no study has beenconducted on the Malaysian ringgit. Thus, amajor objective of this study is to fill the gap inthe current literature so as to provide morereliable evidence on the univariate time-seriesproperties of the Malaysian exchange rate. Tothe knowledge of the writers, this is the firstattempt utilizing recent advances in non-lineardynamics to examine the random walk behaviourof the Malaysian exchange rate.

This paper is organized as follows: Section 2provides a review of the relevant literature. Thisis followed by a brief overview of the historicaldevelopment of the Malaysian foreign exchangemarket. Section 4 describes the data and theBDS test. The results are then summarized inSection 5 and are used to draw conclusions andimplications in the final section.

In this case, it is necessary to first uncover the structure of dependencies detected in this non-random series. Ifinvestors could have profitably operated a trading rule (net of all transactions costs) which exploits those detecteddependencies, then it would have been at odds with the weak-form efficient market hypothesis.



REVIEW ON RELATED LITERATURE

The characterization of exchange rate returnseries as random in nature has been questionedin recent times by the application of new non-linear statistical tools. The failure to uncoverrandomness in the market can be attributed tothe fact that most of the empirical statistical testsare based on linear models. Fama (1965), in hisearlier work admitted that linear modellingtechniques have limitations, as they are notsophisticated enough to capture the complicated'patterns' that the chartist observed in stockprices. Steurer (1995) expressed a similaropinion, that there is an order to the apparentrandomness of the market. This order is socomplex that the random walk concept wasproven by the standard linear statistical tests.Another researcher, Brooks (1996) agreed thatseries of financial returns often appearedcompletely random using standard linear andspectral tests. However, he strongly believed thatthrough a different approach, using morepowerful techniques, it may be possible touncover a more complex form of dependencein those series.

Statistical tests such as serial correlation tests,non-parametric runs test, variance ratio test andunit root tests are designed to uncover lineardependence in the data. However, the lack oflinear dependence does not imply that the seriesare random. Non-linear dependence may existin a series and this is supported by the growingempirical evidence that non-linearity abounds infinancial time series. Following weak-formefficient market hypothesis, even non-linearcombinations of previous prices are not usefulpredictors of future prices (Brooks 1996; Brooksand Hinich 1999; McMillan and Speight 2001).These linear statistical tests cannot detect non-linear departure from the random walkhypothesis (Hsieh 1989). Thus, this has promptedresearchers to re-examine the possibility ofuncovering a more complex form ofdependencies in the earlier observed series thatoften appeared random to standard linearstatistical tests.

Recent breakthroughs pertaining to non-linear dynamics and chaos, coupled with therapid acceleration in computer power, have made

it possible to more robustly test for the randomwalk hypothesis. Most of the empirical studies inthe literature have extensively applied the Brock-Dechert-Scheinkman test (Brock et al 1987,1996)2 to investigate whether financial andeconomic time series are random walk with theproperty of being independent and identicallydistributed (Hsieh 1989; Scheinkman andLeBaron 1989; De Grauwe et al 1993; Steurer1995; Brooks 1996; Mahajan and Wagner 1999;Opong et al 1999). The BDS test uses thecorrelation function (also known as correlationintegral) as the test statistic. The asymptoticdistribution of the correlation function is knownunder the null hypothesis of whiteness(independent and identically distributedobservations). As a result, the BDS test can beused as a formal statistical test of whitenessagainst general dependence, which includes bothnon-white linear and non-white non-lineardependence. The power of the BDS test indetecting departures from i.i.d. behaviour hasbeen proven in a number of Monte Carlosimulations (Brock et al 1991; Hsieh 1991).

The results from empirical studies onexchange rates using the BDS test have generallyrejected the null hypothesis of being independentand identically distributed (Hsieh 1989; DeGrauwe et al 1993; Steurer 1995; Brooks 1996).However, the evidence from a recent study byMahajan and Wagner (1999) using the BDS testrevealed that the null hypothesis of randomwalk cannot be rejected for all the exchangerate data under investigation. One notablefeature of all these earlier studies is that majorcurrencies like the Japanese yen, U.S. dollar,British pound, and German deutschmarkreceived substantial attention, while none hasbeen given to currencies of developing countries,including Malaysia.

THE MALAYSIAN FOREIGN

EXCHANGE MARKET

This section provides a brief account of theexchange rate regimes in Malaysia for the period1957-2001. Throughout those 44 years, Malaysiaimplemented a diverse range of exchange rateregimes, starting initially with pegging the ringgitto the pound sterling. This was followed by a

The growing popularity of the BDS test has witnessed its incorporation into commercial statistical package of E-Viewsversion 4.0.



floating regime, first against the U.S. dollar andlater in terms of a composite basket of currencies.Since 1st September 1998, the Malaysian ringgithas been pegged to the U.S. dollar.

In those earlier days after independence in1957, when the value of the Malaysian currencywas determined in terms of pound sterling, itsstability was closely related to the pound sterlingin the foreign exchange market. At that time,foreign exchange was only used to fulfill theneeds of exporters. The rate of the Malaysianringgit was managed by the Malaya Board ofCommissioners of Currency and British Borneo(the Currency Board) and fixed at 2s. 4d. sterling.Independence of the foreign exchange marketin Malaysia was attained on 12 June 1967 whenthe Central Bank of Malaysia assumed sole powerto issue currency from the Malaya Board ofCommissioners of Currency.

With the floating and devaluation of thepound sterling in early 1970, Malaysia adoptedthe U.S dollar as the intervention currency inJune 1972. Owing to uncertainty in theinternational foreign exchange markets, theringgit was allowed to float upwards from 21stJune 1973. Through that floating arrangement,the Central Bank of Malaysia was no longerbound to buy one unit of U.S. dollar with the setfloor rate of RM2.4805.

That floating regime against the U.S dollarwas in place for only two years before theMalaysian Government adopted a new exchangerate regime on September 27th, 1975.Henceforth, the rate of exchange of the ringgitwas determined in terms of a composite basket,comprising the currencies of Malaysia's majortrading partners. Under this floating exchangerate regime, Malaysia did not set targets forringgit exchange rate levels. Central Bankinterventions were only to ensure the stability ofthe ringgit, so that the exchange rate reflectedthe underlying economic fundamentals.

On July 2nd, 1997, the announcement ofthe Bank of Thailand to abandon its defence ofthe baht caused the collapse of its nationalcurrency. What appeared to be a local financialcrisis in Thailand quickly escalated into an Asian

financial crisis, spreading to other Asian countriesincluding Indonesia, Korea, Malaysia and thePhilippines. The Malaysian ringgit came underintense selling pressure and the Central Bankswas forced to intervene heavily to defend thevalue of the ringgit. At the same time, theMalaysian government undertook somecorrective measures such as tightening monetarypolicy, emphasising fiscal prudence andstrengthening the financial system, all aimed torestore confidence and stability in the markets.However, all these efforts were ineffective incurbing the downward pressure on the Malaysianringgit.

The ringgit continued to experience extremevolatility and reached a historical intra-day lowof USD1 = RM4.8800 on January 7th, 1998. Theringgit remained volatile under intensespeculative pressure and it traded within therange of USD1 = RM4.0900 to RM4.2650 duringJuly and August that year. In order to preventfurther pressure on the ringgit, the Malaysiangovernment implemented selective exchangecontrol policies on September 1st, 1998. Thisexchange control served to reduce theinternationalization of ringgit through theelimination of speculative activities in the foreignexchange markets, both external and at home.As part of these measures, the ringgit was peggedto the U.S. dollar at RM3.8000. At the time ofwriting, the ringgit* s peg to the dollar has heldfirm though there have been pressures to re-pegthe ringgit at a higher rate following the declineof regional currencies against the U.S. dollar.

RESEARCH DESIGN AND METHODOLOGYThe Data

The daily spot exchange rates for Malaysianringgit (MYR/USD) are obtained from theFederal Reserve Statistical Release3 over theperiod January 2nd, 1990 to 31st August 1998.The sample period after this is excluded fromthe current study because Malaysia adopted afixed ringgit regime from September 1st, 1998.At the time of writing, the Malaysian ringgit pegat 3.80 to the U.S. dollar has held firm4.

These daily data are obtained from the Federal Reserve Board's official website at http://www.federalreserve.gov/releases/HlO/hist on 18/4/2001. The H.IO release contains daily rates of exchange of major currencies against theU.S. dollar. 6 J *We thank anonymous referee for highlighting us of the sample period selection. After this period the pegging ofringgit to the US dollar is irrelevant to our study.

44 Pertanika J. Soc. Sci. 8c Hum. Vol. 11 No. 1 2003


The raw exchange rate data are transformedinto the differenced-log return series (rr). Allsubsequent analyses are performed on thesetransformed Malaysian exchange rate returnseries, which can be interpreted as a series ofcontinuously compounded percentage dailyreturns (Brock et al. 1991). Formally, it can bewritten as:

rt= 100 (In (S) - I n (S(J) (2)

where Si is the exchange rate at time t, and S^the rate on the previous trading day.

This transformation has become standardin the finance literature (Hsieh 1989; De Grauweet al. 1993; Steurer 1995; Brooks 1996; Mahajanand Wagner 1999). Thus, this transformation isdone to conform to the literature and to allowcomparison with other studies in this domain.Another possible justification for using returnsrather than raw data is that the raw data is likelyto be non-stationary. Stationarity is a pre-requisitefor the BDS test. Hsieh (1991) pointed out thatnon-stationarity in the data series can cause arejection of the null hypothesis of i.i.d. on thebasis of the BDS test.

The Brock-DechertScheinkman Test (BDS Test)Brock, Dechert and Scheinkman (Brock et al.1987) developed a statistical test and the BDSstatistic. The original BDS paper took the conceptof the correlation integral5 and transformed itinto a formal test statistic which is asymptoticallydistributed as a normal variable under the nullhypothesis of i.i.d. against an unspecifiedalternative. A revision of this original paper wasdone in Brock et al (1996).

The BDS test is based on the correlationintegral as the test statistic. Given a sample ofindependent and identically distributedobservations, {x* t = 1, 2, , n], Brock et al.(1987, 1996) showed that:

Wm

(3)

has a Umiting standard normal distribution,where W (e) is the BDS statistic6, n is thesample size, mis the embedding dimension, andthe metric bound, e, is the maximum differencebetween pairs of observations counted incomputing the correlation integral. ^mn(e)measures the difference between the dispersionof the observed data series in a number ofspaces with the dispersion that an i.i.d. processwould generate in these same spaces, that isC n(e) -Cln(e)m. T n(s) has an asymptotic normaldistribution with zero mean and variance Vm(e)7.

This BDS test has an intuitive explanation.The correlation integral Cmn(e) is an estimate ofthe probability that the distance between anytwo wfr-histories, x™ = (x, x+1, , x+^) and x™ =(x, x ., , x ,) of the series {x}is less than e,

s s+i s+m-i t

that is, C (e) -> probflx - x k e, for all i = 0,' m,nx f r l r+i s+i *

1, ro-1}, as n -^ ooIf the series {xjare independent, then, for

\t-s\>m,

-> oo. Furthermore, if the series {xj are alsoidentically distributed, then Cmn(e) "• C^e)"1, asn -> oo.

The BDS statistic therefore tests the nullhypothesis that Cmn(e) = C,n(e)m, which is thenull hypothesis of i.i.d8.

The need to choose the values of e and mcan be a complication in using the BDS test. Fora given m, e cannot be too small because Cmn(e)will capture too few points. On the other hand,e cannot be too large because C n(e) will capturetoo many points. For this purpose, we adopt theapproach used by advocates of this test. Inparticular, we set e as a proportion of standarddeviation of the data, a. Hsieh and LeBaron(1988a, b) have performed a number of MonteCarlo simulation tests regarding the size of theBDS statistic under the null of i.i.d. and thealternative hypotheses. The Monte Carloevidence showed that the 'best' choice of e isbetween 0.50 and 1.50 times the standarddeviation.

On the other hand, at our chosen setting ofe, we produce the BDS test statistic, W^n(e) for

In Grassberger and Procaccia (1983), the correlation integral was introduced as a measure of the frequency withwhich temporal patterns are repeated in the data. For example, the correlation integral C(e) measures the fractionof pairs of points of a time series {x(} that are within a distance of £ from each other.

6 See Brock et al (1987, 1996) for the derivation of the BDS test statistic.7 Vm(e) can be estimated consistently by V^w(e). For details, refer Brock et al. (1987, 1996).8 The null of i.i.d. implies that C M(e) = C;n(e)m but the converse is not true.



all settings of embedding dimension from 2 to10, in line with the common practice of mostresearchers (Hsieh 1989; De Grauwe et al 1993;Brooks 1996; Mahajan and Wagner 1999; Oponget al 1999). However, it is important to takenote that the small samples properties of BDSdegrade as one increases the embeddingdimension. Thus, in this study, the results withembedding dimensions of 2 to 5 are given themost serious consideration9.

Asymptotically, the computed BDS statistics,W n(e) ~ N (0,1) under the null of i.i.d. againstan unspecified alternative. Thus, this wouldsuggest a two-sided test. However, this is a verytricky issue. Brooks (1996) and Opong et al(1999) clearly stated that the BDS test is a two-sided test so that the rejection of the null ofi.i.d. occurs when the estimated value of theW (e) is more extreme (in either tail) than thecorresponding statistic from the normal tables.However, Barnett et al (1995, 1997) run it as aone-tailed test. In this study, the BDS test istaken as a two-tailed test.

RESULTS AND ANALYSIS

Descriptive Statistics

Before proceeding to the formal BDS test, weprovide some descriptive statistics of theMalaysian exchange rate return series in orderto get a better view of some of the importantstatistical features of this series of returns.

Table 1 reveals that the Malaysian exchangerate return series exhibit some degree of negativeor left-skewness. On the other hand, thedistribution of this return series is highlyleptokurtic, in which the tails of its distributiontaper down to zero more gradually than do thetails of a normal distribution. Not surprisingly,given the non-zero skewness levels and excesskurtosis demonstrated within this series ofreturns, the Jarque-Bera (JB) test strongly rejectsthe null of normality. These results conform tothe consensus in the literature that thedistributions of exchange rate return series arenon-normal (Hsieh 1989; Steurer 1995; Brooks1996).

One area that deserves our attention is thestationarity of the exchange rate return series,which is a pre-requisite for the BDS test. Theresults from the Augmented Dickey Fuller (ADF)test in Table 2 show that the null hypothesis ofa unit root can be rejected for the Malaysianexchange rate return series even at the 1% levelof significance. Similar conclusions are madebased on the results of Phillips-Perron (PP) testsummarized in the same table. Thus, the resultsindicate that the transformed return series ofthe Malaysian exchange rate do not contain aunit root and thus are stationary, as displayed inFig. L Those statistics confirm theappropriateness of the differenced logarithmictransformation in rendering the exchange rate

TABLE 1Summary statistics of differenced-log returns for MYR/USD (rt)

Sample PeriodNo. of observationsMeanMedianMaximumMinimumStd deviationSkewnessKurtosisJB normality test statisticp-value

* Denotes a very small value.

MYR/USD

2/1/1990-31/8/19982179

0.0201030.0000007.195700

-9.1567000.694546

-0.08396843.14067

146292.7(0.000000)*

In a personal communication, LeBaron recommends the use of embedding dimension from 2 to 5 at sample sizescomparable to ours.



Augmented Dickey Fuller (ADF)Phillips-Perron (PP)

TABLE 2Unit root test results for MYR/USD

Level

Trend

0.4211340.587583

(6)(7)

First Difference

No Trend

-21.00660 (5)**-45.21833 (7)**

Note. The null hypothesis is that the series contains a unit root. The critical values for rejection are -3.97 formodels with a linear time trend and -3.43 for models without a linear time trend at a significant level of1% (**). Values in brackets indicate the chosen lag lengths.

30/12/91 24/12/93 19/12/95 16/12/97

Fig. 1: Differencedrlog returns of MYR/USD (rt), 2/1/1990 to 31/8/1998(2179 observations)

return series stationary.

BDS Test

Subsequently, we apply the BDS test on theMalaysian exchange rate return series in orderto test whether these return series are randomwalk with the property of being independentand identically distributed. Table 3 reports theresults of the BDS test. The BDS statistics, W (e),are calculated for all combinations of m and ewhere m = 2, 3, 10 and £ = 0.50a, 0.75a,1.00a, 1.25a and 1.50a, with a total of 45combinations. Although we report the resultswith embedding dimensions varying from 2 to10, the results with embedding dimensions of 2to 5 should be given the most seriousconsideration. This is because the small sampleproperties of BDS degrade as one increases thedimension. Specifically, as one gets beyond m=by

the small sample properties are not robust interms of normal approximations at sample sizes

comparable to ours.It is obvious from Table 3 that all the BDS

statistics are in the extreme positive tail of thestandard normal distribution. Specifically, all ofthe values are significant even at the 1 % level ofsignificance, especially at the suggesteddimensions of 2 to 5. According to Brock et al(1991), the large BDS statistics can arise in twoways. It can either be that the finite sampledistribution under the null of i.i.d. is poorlyapproximated by the asymptotic normaldistribution, or the BDS statistics are large whenthe null hypothesis of i.i.d. is violated. From thevarious Monte Carlo simulations, Brock et al(1991) ruled out the first possibility, thussuggesting that our large BDS statistics in Table3 provide strong evidence of departure from thei.i.d. null.

The rejection of the i.i.d. random behaviourimplies that there is indeed some dependencein the underlying generating process of Malaysian



TABLE 3BDS test results for differenced-log returns of MYR/USD (rt)

M

2345678910

0.50

7.259.03

10.6212.3414.4317.0020.1924.1429.05

0.75

10.3712.1613.5214.7716.2217.9219.9022.2224.90

E

1.00

13.9716.2217.7518.9220.1021.4122.9124.6226.58

1.25

15.6618.5320.3721.5522.6023.6624.8726.2127.74

1.50

15.7918.4820.4121.5922.4823.3224.2825.3426.55

Note. Asymptotically, the computed BDS statistics, Wm,n((t~) N (0,1) under the null of i.i.d. The BDS test is

taken as a two-tailed test. All the BDS statistics are significant at the 1% level of significance.

exchange rate return series. This is becausesome cycles or patterns show up more frequentlythan would be expected in a true random series.However, the results from the BDS test do notprovide any insight into the cause of rejection,which may be due to non-white linear and non-white non-linear dependence . Additionaldiagnostics tests are needed and this remains anavenue for further research.

CONCLUSIONS

This study has empirically examined thebehaviour of the Malaysian exchange rate returnseries in the light of the random walk hypothesis.With a new and powerful non-linear statisticaltool, namely the BDS test, it is possible to testfor the random walk hypothesis more robustlyin series of financial returns that often appearcompletely random to standard linear statisticaltests, such as serial correlation tests, non-parametric runs test, variance ratio test and unitroot tests. The outcomes of our econometricinvestigation reject the hypothesis that the MYR/USD relationships examined in this study arerandom, independent and identically distributed.This is because some cycles or patterns show upmore frequently than would be expected in atrue random series. These results may haveimplications for the weak form market efficiency,if the underlying structure can be identified andprofitably exploited. Specifically, it is necessaryfirst to uncover the structure of dependencies inthe underlying process, either in the form oflinear or non-linear, and then proceed to assesswhether investors could have profitably operated

a trading rule which exploited thesedependencies. This remains an avenue forfurther research.

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BROOKS, C. 1996. Testing for non-linearity in dailysterling exchange rates. Applied FinancialEconomics 6: 307-317.

BROOKS, C. and M. J. HINICH. 1999. Cross-correlationsand cross-bicorrelations in Sterling exchangerates. Journal of Empirical Finance 6(4): 385-404.

CORNELL, B. 1977. Spot rates, forward rates andexchange market efficiency'. Journal of FinancialEconomics 5: 55-65.

DE GRAUWE, P., H. DEWACHTER and M. EMBRECHTS.

1993. Exchange Rate Theory: Chaotic Models ofForeign Exchange Markets. Oxford: Blackwell.

FAMA, E. F. 1965. The behaviour of stock marketprices. Journal of Business 38: 34—105.

FRANKEL, J. A. 1981. Flexible exchange rates, prices,and the role of news: lessons from the 1970's.Journal of Political Economy 89: 665-705.

GRASSBERGER, P. and I. PROCACCIA. 1983. Measuringthe strangeness of strange attractors. Physica9D: 189-208.

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HSIEH, D. A. 1991. Chaos and nonlinear dynamics:application to financial markets. Journal ofFinanced: 1839-1877.

HSIEH, D. A. and B. LEBARON. 1988a. Finite sampleproperties of the BDS-statistics I: distributionunder the null hypothesis. Mimeograph.University of Chicago, and University ofWisconsin.

HSIEH, P. A. and B. LEBARON. 1988b. Finite sampleproperties of the BDS-statistics II: distributionunder the alternative hypothesis. Mimeograph.University of Chicago, and University ofWisconsin.

MAHAJAN, A. and A. J. WAGNER. 1999. Nonlineardynamics in foreign exchange rates. GlobalFinance Journal 10: 1-23.

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Nonlinearities in the black market zloty-dollarexchange rate: some further evidence. AppliedFinancial Economics 11: 209-220.

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K. FARAHMAND. 1999. The behavior of some UKequity indices: an application of Hurst andBDS tests. Journal of Empirical Finance 6:267-282.

SGHEINKMAN, J. and B. LEBARON. 1989. Nonlineardynamics and stock returns. Journal of Business62: 311-337.

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(Received: 14 June 2002)



Organizational Creative Climate & Learning Organization: FactorsContributing Towards Innovation Within an Organization

AZAHARI ISMAIL, MERIAM ISMAIL*, BAHAMAN ABU SAMAH, SHAMSUDDIN AHMAD,KHAIRUDDIN IDRIS 8c JEGAK ULI

*A-02-21, Damansara MAS, Persiaran KIP 2Sri Damansara, 52200 Kuala Lumpur, MalaysiaFaculty of Education, Universiti Putra Malaysia,

43400 UPM, Serdang, Selangor, Malaysia

Keywords: Organizational climate, creativity, innovation, learning culture

ABSTRAKKajian inovasi mencadangkan bahawa satu iklim organisasi yang kreatif cenderung untukmeinainkan peranan penting dan sebagai satu prediktor inovasi. Walau bagaimanapun, baru-baruini, kehadiran budaya pembelajaran dalam sesebuah organisasi cenderung untuk menerangkankesan yang harus dipertimbangkan turut mempengaruhi inovasi dan untuk menentukan yangmana satu boleh menjadi prediktor yang lebih baik untuk inovasi teknologi dan organisasi. Hasilkeputusan menunjukkan bahawa kedua<lua budaya pembelajaran dan iklim kreatif secarasignifikannya menyumbang 80.4% kepada varians dalam inovasi yang dibentuk dengan iklimkreatif organisasi yang menyumbang 55.6% dan budaya pembelajaran menyumbang 63.7%varians dalam inovasi yang diperhatikan. Hasil kajian juga mendapati bahawa dimensi organisasipembelajaran menyumbang lebih kepada varians dalam inovasi, khususnya dimensi "KepimpinanStrategik" mempunyai kuasa prediktor tinggi signifikan ke atas inovasi berlaku di dalam organisasikes dibandingkan dengan sepuluh faktor iklim kreatif organisasi dan selebihnya enam dimensiorganisasi pembelajaran.

ABSTRACTStudies on innovation have suggested that a creative organizational climate tends to play animportant role and is a predictor for innovation. However, lately, the presence of learning culturein an organization tends to explain a considerable influencing effect on innovation too. Thisparticular case study tries to examine the influence of both variables on innovation and todetermine which one of the two can be a better predictor for technological and organizationalinnovation. The results indicated that both learning culture and creative climate significantlycontributed 80.4% to the variance in the innovation construct with organizational creative climateon its own, contributing 55.6% and the learning culture on its own, contributing 63.7% of theobserved variances in innovation. The results of the study also found that the learning organizationdimensions contributed more to the variances in innovation, particularly the dimension of'Strategic Leadership* which had a significantly high predictive power on innovation occurringwithin the case organization as compared to the ten organizational creative climate factors andthe rest of the six learning organization dimensions.

INTRODUCTION and make use of new technologies of all kindsThere is a substantial body of evidence that (OECD 1997; Freeman 1994). French and Bell,suggests innovation can be considered as a Jr. (1995) considered three elements to ensuredominant factor in national economic growth continuous innovation in organizations; theseand international patterns of trade, while at the are empowering employees, encouragingmicro level (within organizations) R&D is seen employee participation and employeeas enhancing an organization's activity to absorb involvement. Innovation, for example, could be

Azahari Ismail, Meriam Ismail, Bahaman Abu Samah, Shamsuddin Ahmad, Khairuddin Idris 8c Jegak Uli

one of the outcomes that result from successfulchange efforts (Beer and Nohria 2000; ChainStore Age 1998; OECD 1997; Mensch 1975).

Among the many streams of researchregarding influencing factors on innovation, theidea of having a creative working climate (orenvironment) within an organization whichrelates to a suitable working culture to facilitatean environment which will then enhance theorganizational power is very often mentioned.This idea was put forward during the middle1980's and late 1990's by several scholars amongothers Ekvail, Arvonen and Waldenstrom-Lindblad (1983), Ekvail and Tangeberg-Anderson (1986), Zain Mohamed (1995), ZainMohamed and Rickards (1996) and Amabileand Conti (1999) who focused on organizationalclimate factors which are said to foster creativityand innovation. Zain Mohamed (1996) in hisstudy involving eight Malaysian firms used theEkvail et a/.'s (1983) Creative ClimateQuestionnaire (CCQ) which contained tendimensions of creative climate to compare theinnovation level of the organizations. In additionZain Mohamed's (1995) study identified fifteenfactors deemed favorable for innovationimplementations in private organizations bothlarge and small, of which five are similar toAmabile and Conti's (1999) eight organizationalclimatic factors likely to foster innovation. Thefive major factors favorable for innovation arementioned and common to both Amabile andConti's and Zain Mohamed's studies thoughphrased differently. They are (1) Organizationalencouragement (commitment), (2) Sufficientresources (user friendly technology), (3)Teamwork support, (4) Freedom (open to newideas), and (5) Supervisory encouragement.

Research on innovation has also identified anumber of human, social and cultural factorswhich are crucial to the effective operation ofinnovation at the organizational level (OECD1997). These factors, according to OECD (1997),were mostly centered around learning; it islearning by organizations as a whole (diffusionof knowledge to a broad range of key individualswithin them) which is critical to an organization'sinnovative capabilities. Beginning in the late1990's and the year 2000, the idea of learning atthe organizational level and knowledgemanagement have been closely linked toinnovation (Argyris and Schon 1978; Drucker1988; Garvin 1993; Nonaka and Takeuchi 1995).

This stream of research also called the neo-Schumpeterian approach stems from earlierscholars such as Polyanyi (1966) and Nonaka(1991), who viewed innovation in terms ofinteraction between market opportunities andthe organization's knowledge base andcapabilities. This approach has been followedup on recent studies by Mohanty (1999) and StaMaria (2000).

STATEMENT OF THE PROBLEMDespite achieving considerable successeconomically, the innovation practices in theMalaysian private organizations still remainrelatively under-researched as asserted by a fewscholars (Zain Mohamed and Rickards 1996;Malaysian Science and Technology InformationCenter (MASTIC) 1996). This statement is alsosupported by Sta Maria (2000) and Khairuddin(1999). Axtell, Holman, Unsworth, Wall andWaterson's (2000) were of the opinion that therewas a large literature on creativity in general butfew relating to innovation per se. Even thoughthere has been a huge volume of research oninnovation, with 3,085 publications on thediffusion of innovation out of which 2,297 areempirical works (Rogers 1983), surprisingly, goodmodels and principles on innovation have yet tobe developed as stated by Zairi Mohamed (1994).MASTIC (1996), realizing the situation and theneed for Malaysian organizations to upgradetheir innovations, has since conducted anationwide survey on innovation in 1994involving a large number of Malaysian privateorganizations. Following which, another surveywas conducted in 1998 (M. Kamaruzzmanpersonal communication, October 2000). Thus,the problem statement of this study can besummarized as "the critical need for morestudies to be conducted linking organizationalcreative climatic factors and learning factors inorder to analyze their influences on innovationwithin the Malaysian context is pressing".Specifically, the fields of organizational creativeclimatic factors and learning factors should beempharised. Undoubtedly with more research,more crucial information could be obtainedwhich will further assist in organizational decisionmaking and subsequently improve the nationalgrowth. Hence, the implementation of this studywas taken up generally to add value for thetheoretical development in this particular areaand specifically to obtain insights into the areas


Organizational Creative Climate 8c Learning Organization: Factors Contributing Towards Innovation

of working climate and learning culture oninnovation.

OPERATIONAL DEFINITIONS OF TERMSThe three major operational definitions of termsused in this study are as follows:

Organizational Creative ClimateThe definition of organizational climate forcreativity, takes the definition by Ekvall (1996)and Ekvall et al. (1983) who regard climate as anattribute of the organizations, a conglomerate ofattitudes, feelings, and behavior whichcharacterises life in organizations, and existsindependently of the perceptions andunderstandings of the members of theorganization (p. 105); it is conceived as anorganizational reality in an 'objectivistic' senseand therefore is not identical to organizationalculture. By Ekvall's (1996) understanding, climateis regarded as a manifestation of culture. Theorganizational climate for creativity containedseveral factors (Ekvall 1996) deemed favorablefor such climatic culture one which couldstimulate creativity and innovation. These factorsthen are referred to as creative climate factors.The creative climate in this study is assessed bythe ten factors of the Creative ClimateQuestionnaire (CCQ) forwarded by Ekvall et al.(1983) and Ekvall (1996). The factors are:challenge/motivation, freedom, idea support,liveliness/dynamism, playfulness/humour,debates, trust/openness, conflicts, risk takingand idea time.

Learning OrganizationA learning organization is one in which learningand work are integrated in an ongoing andsystematic fashion to support continuousimprovement and includes learning at theindividual, group, organization and global levels(Watkins 1996, p. 91). This learning occurs at alllevels within the organization and outside theorganization by Watkins' (1996) understandingand forms the basis needed for a learningorganization. Watkins and Marsick (1996a, 1999)forward seven dimensions for a learningorganization and these are known as learningorganizational factors. The learning culture inthis study is assessed by the seven dimensions ofthe Dimensions of the Learning OrganizationQuestionnaire (DLOQ) forwarded by Watkinsand Marsick (1996a). These are continuous

learning, dialogue and inquiry, team learning,embedded systems, empowerment, systemconnection and strategic leadership.

InnovationInnovation is defined as the process of creatinga commercial product from invention (Hitt et al.1999, p. 476). This definition which equatesinnovation to commercialization of invention(which includes improvement on alreadyavailable product or service) is similar to thoseof several scholars (OECD 1997; Rickards 1985;Robbins and Decenzo 2001; Taylor 1991). Whenan organization innovates, it often does so bothways, which is in radical manner (technological)as well as non-technological (OECD 1997). Thenon-technological component of innovation inthis study focuses on organizational innovation.Organizational innovation (OI) is included inthis study together with technological innovation(TI) since OI occurs as part of technologicalinnovation (OECD, 1997). The major componentbeing emphasized in OI in this study is themanagerial innovation or what some scholarswould call administrative innovation (Sta Maria,2000) which is the incremental (soft) side ofinnovation.

Technological InnovationTechnological innovation comprises implementedtechnologically new products and processes andsignificant technological improvements inproducts and processes (OECD 1997).Technological innovation is deemedimplemented if it has been introduced to themarket (product innovation) or used within aproduction process (process innovation).

Organizational Innovation

Organizational innovation in this study includesthe implementation of advanced managementtechniques such as the practice of qualityassurance program. In this study organizationalinnovation is reflected by the ISO 9000 programbeing adopted or implemented by the sampledorganizations as well as the practice of the fourbasic pillars of TQM. The basic pillars of TQMare: (1) satisfying the customer, (2) effectivemanagement system/process such as ISO 9000program, (3) teamwork practice and (4)improvement tools for continuous improvement.The component is being assessed by statementsin the questionnaire relating to the ISO 9000


Azahari Ismail, Meriam Ismail, Bahaman Abu Samah, Shamsuddin Ahmad, Khairuddin Idris & Jegak Uli

program implementation and its procedures aswell as the basic pillars of TQM.

Justifiably and also for ease of use, the terminnovation which is widely referred to in thiswriting includes the two major constructs ofinnovation, namely, technological innovation andorganizational innovation.

METHODOLOGYThe study used a quantitative case method withmultivariate statistical analysis, namely, multipleregression analysis and multiple correlation inan attempt to find answers to the researchquestions being posed. Multivariate analysis issuitable in analyzing phenomena either fordiscovery or hypothesis testing (Davis 2000). Inthis study, the analysis used was more for gettinganswers to the questions posed rather than forhypothesis testing. The survey case method as aform of causal-comparative is seen suitable forconducting studies that are seeking explanationon attitudes and behavior on the basis of datagathered at a point in time (Ary Jacobs andRazavieh 1990-pg. 407). The survey involvedconvenient sampling on a cross sectional basiswhich was deemed appropriate for makinggeneralizations from samples being studied tothe broader population group. Since the studyinvolved three different variables which werenot controlled or manipulated and whichconcerned the relationships among the variablesand the ability to explain and predict values ona variable from the relationships, a multipleregression analysis is seen appropriate to use insummarizing Lehman's (1995) point of view.The independent variables were assumed to sharevery little variance with each other (not collinear)but together, they accounted for much of thevariance in the dependent variable (Davis 2000).In addition, the multiple correlation analysis wasconducted to obtain explanation of therelationship of the criterion variable on theentire set (not just one in particular) of thepredictor variables. Thus, the analysis can explainhow much of the total variation in the criterionvariable, innovation, is accounted for by theindependent variables taking the idea fromLehman's (1995) statement. Thus this study isalso an explanatory study (Ary et ai 1990).

Along with the multiple regression analysis,ANOVA also used and a post hoc test wasfollowed, where appropriate, to investigatedifferences among population means.

INSTRUMENTATIONThree instruments were used in this study, ofwhich two were the ones developed byresearchers for their previous work and havebeen validated. Two instruments which formpart of the whole questionnaire were obtainedfrom the original questionnaires developed byvarious scholars (Ekvall et al (1983); Watkinsand Marsick 1996a). All the statements were inthe English language. The third instrument toassess innovation was developed by theresearcher, Meriam Ismail.

The instrument used to measure theorganizational climate factors is the CreativeClimate Questionnaire (CCQ) developed byEkvall et al (1983). The ten factors are (i)challenge/motivation (5 items), (ii) freedom (5items),.(iii) idea support (5 items), (iv) liveliness/dynamism (5 items), (v) playfulness/humour (5items), (vi) debates (5 items), (vii) trust/openness (5 items), (viii) conflicts (5 items),(ix) risk taking (5 items) and (x) idea time (5items). The total items are fifty. The itemsconsisted of statements which required therespondents to determine the degree to whichthe statements are true or otherwise of theorganizational working climate occurring in theorganizations. The scales used representing eachstatement is from a continuum of 0 to 3. The "0"represented a degree equivalent to "not at allapplicable" and the "3" represented "applicableto a high degree". The CCQ was selected for thiscase study over other instruments because of itswide range of ten factors covering workingclimate within an organization both stimulatingand hampering innovation. It was also selectedbecause the factors were said to be able toexplain effects on productivity, job satisfaction,profit, quality, innovation, well-being which inturn will give performance impact on theorganizational resources both human and non-human according to Ekvall (1990) as cited byEkvall (1996). The stability aspect of the reliabilityof the CCQ has been illustrated in a longitudinalstudy of a product development project in ahigh-tech company (Ekvall 1993) as cited byEkvall (1996). The CCQ has previously beenapplied for use in many researches both inEurope and Asia, in particular in a study involvingSwedish, German and Spanish organizations.

The instrument used to measure learningorganization dimensions is the Dimensions ofLearning Organization Questionnaire (DLOQ)


Organizational Creative Climate & Learning Organization: Factors Contributing Towards Innovation

forwarded by Watkins and Marsick (1999) witheach dimension having at least six items ormore. The seven dimensions of learningorganization with the relevant items are (1)continuous learning- 7 items, (2) dialogue andinquiry- 6 items, (3) team learning - 6 items, (4)embedded systems- 6 items, (5) empowerment-6 items, (6) system connections- 6 items and (7)provide leadership- 6 items. The total items areforty-three. The instrument has been constructedin a way where each item requires the respondentto determine the degree to which the statementis true or otherwise of the extent of organizationalapproach practised in the organization. Eachstatement of either instrument will be measuredon a common scale of 1 to 6 continuum rangingfrom "1" representing "almost never" to "6"representing "almost always". The DLOQ wasselected for this study because it has been widelyused in studies involving innovation in Malaysiaand in the USA besides other parts of the world.It has proved to be a reliable measure of learningculture. The DLOQ has also been used in over200 companies worldwide.

The innovation construct, on the other hand,contained two main constructs namely (I)technological product and process innovation(technological transfer & absorptive capacity,and diffusion of innovation), and (2)organizational innovation focusing on basicelements of TQM and quality assurance programsuch as ISO 9000 certification. There were thirty-two items to cover all the two sub constructs.The breakdown of the items were nineteen fortechnology transfer/absorptive capability, five fordiffusion of innovation and eight fororganizational innovation concentrating onaspects of ISO 9000 implementation and basicfoundation of TQM. The thirty-two items on thetwo constructs of technological innovation andorganizational innovation were constructed bythe researcher Meriam Ismail and validated usingfactor analysis (Rotation method), based on theguidelines provided by Wong et al. (1999),OECD(1997) and MASTIC (1996). Thestatements required the respondents todetermine the degree to which something istrue or otherwise. All the items were constructedusing rating scales on a continuum of 1 to 6.The u l " represented a degree equivalent to"almost always" and the "6" represented a degreeequivalent to "almost never" of the statements.The scales "2", through "5" represented the

degree? equivalent to between "almost always" to"almost never" of the statements. All items forthe three constructs have been reviewed by twoacademics (Zain Mohamed and Ekvall) in therelated fields (please see Appendix 1).

Finally, the fourth section contained eightitems that seek information on the respondents'demographic backgrounds. This includedgender, age in years, job category, educationbackground, tenure of service with theorganization, and the length of organizationestablishment in years.

MEASURES

Following are Tables 1 and 2 depicting reliabilityestimates for each of the ten factors of the CCQand each of the seven dimensions of the DLOQ.The original estimates of the CCQ aredetermined by Ekvall and colleagues (Ekvall1996). The reliability estimates for the innovationconstructs are shown in Table 3 after a pilot testof the instrument was conducted during thecase investigation.

The Cronbach Alpha's reliability index forthis innovation questionnaire is .97. Theconstructs have proved consistently reliable withall the scales above the recommended . 70(Nunally 1978).

POPULATION AND SAMPLEThe sample of respondents from the caseorganization was obtained through convenientsampling (selected by the liaison person in thecase organization) from a cross section of apopulation of about a hundred employees andwas close to random sampling. A total of fortyrespondents from three major levels ofemployment namely top/senior management,middle/lower management/supervisory and thetechnical/administrative support staff respondedto the questionnaire. All the responses wereusable.

ANALYSIS

The analysis procedures conducted were in linewith the research questions being posed. Twomajor types of analyses were conducted; one wasthe simple descriptive statistics and the otherwas the inferential statistics (multiple regressionand ANOVA and independent T-Test). Beforethe data was analyzed, an exploratory data analysisEDA was first executed on the data. This is todetermine whether the spread of data subscribed


Azahari Ismail, Meriam Ismail, Bahaman Abu Samah, Shamsuddin Ahmad, Khairuddin Idris &Jegak Uli

TABLE 1Reliability estimates for the original measures in the CCQ inventory

Subscale

Challenge/motivationFreedomIdea supportLiveliness/dynamismPlayfulness/humourDebatesTrust/opennessRisk takingIdea timeConflicts

Total

Number of items

5

555555555

50

Cronbach's Alpha(original)

0.820.740.890.790.810.750.790.730.780.85

Cronbach's Alpha(from current pilot test)

0.780.680,830.760.740.780.550.680.720.61

The overall reliability for 50 items of the CCQ in the pilot test was .94

TABLE 2Reliability estimates for the measures in the DLOQ

Subscale

Continuous LearningDialogue and InquiryTeam LearningEmbedded SystemsSystems ConnectionsEmpowermentProvide Leadership

Total

Number of items

7666666

43

Cronbach Alpha's(original)

0.810.870.860.820.840.790.77

Cronbach Alpha's(current pilot test)

0.830.890.870.810.880.900.92

However the overall reliability for the 43 items of the DLOQ is .97

TABLE 3Reliability estimates for the innovation construct

Subscale Number of items Cronbach Alpha's (original)

Tech. Transfer/Absorptive capabilityDiffusion of innovationOrganizational innovation

1958

0.960.930.94

Total items 32

to the normality test, an assumption neededwhen running the inferential statistics. Anotherpurpose for conducting EDA is to test the datafor homogeneity of variance, a neededassumption for multiple regression analysis. Fromthe EDA it was found that the normalityassumption was met for all the three variablesbased on the Kolmogorov-Smirnov and Shapiro-

Wilk's normality test: organizational climate forcreativity (P=.200, P=.827), learning organization(P-.200, P= .643) variables and the innovationconstructs (P=.2OO, P=.827). Then the data wasassessed for collinearity. A highly correlatedcoefficient (near or equal to 1) between the twopredictor variables denotes a high collinearity.In examining the data for collinearity for n=40,


Organizational Creative Climate 8c Learning Organization: Factors Contributing Towards Innovation

the analysis revealed that the two predictorvariables have a moderate collinearity from thetable of coefficients analysis.The research questions posed are:1. To what extent do the factors of the variable

organizational creative climate independentlyexplain observed variances in organizationalmembers' perceptions on innovation in theorganization?

2. Which factor/s of the organizational creativeclimate variable is/are highly predictive ofinnovation?

3. To what extent do the dimensions of thelearning organization variable independentlyexplain observed variances in organizationalmembers' perception on innovation in theorganization?

4. Which dimension/s of the DLOQ is/arehighly predictive of the innovation construct?

5. To what extent do both organizationalcreative climate and learning organizationvariables explain observed variances inorganizational members' perceptions oninnovation in the organization?

6. Which factor/s together from eithercriterion variables contributes highly to theprediction of innovation in the organization?

7. What are the differences in the members'perceptions on innovation, organizationalcreative climate and learning culture amongthe three levels of employee groups in theorganization?

8. Are there any differences in the members'perceptions on innovation, organizationalcreative climate and learning culturebetween (1) males and female employees;(2) employees of different ages; (3)

employees' education background; and (4)employees' tenure of service in theorganization?

FINDINGSThe case organization is a medium sizedconsulting quantity surveying firm. The full timeemployees in the department are about ahundred. The demographics of the respondentscan be summarized as made up of 55% male tofemale, 85% of top to middle/lower managementlevel, the rest are supervisory and support staff.In addition, 70% are between the ages of 20 to40 years, while the rest are above 41 years of age.Nearly 75% of the respondents have at least abachelor's degree while the rest have at least an'A' level equivalent. Forty-five percent of therespondents have served the organization forless than 5 years.

RESULTS

In answering research question 1, the multipleregression analysis was conducted involving theten factors of organizational creative climatewith the innovation construct. The findingsrevealed that the organizational climate forcreativity factors did explain signifkandy observedvariances of the members' perceptions oninnovation as much as 55.6% with F valuesignificant as seen from Table 4 and Table 5,using the enter method. However, none of theten factors were seen to contribute significantlyas reported from Table 7.

The analysis also found that the correlationof the organizational creative climate variablewith the innovation construct was moderate

overall innovationtotal challengetotal conflicttotal debatetotal freedomtotal idea supp.total idea timetotal livelinesstotal playfulnesstotal risktotal trust

TABLE 4Descriptives- innovation level and organizational climatic factors

Mean

133.638.909.204.857.188.686.507.608.187.706.88

Std. Deviation

25.991.821.872.792.552.292.152.562.832.342.58

N

4040404040404040404040



TABLE 5Model summary of the multiple regression analysis of the organizational climatic factors with innovation

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .745 .556 .402 20.09

a Predictors: (Constant), total trust, total debate, total idea supp., total risk, total challenge, total freedom,total liveliness, total playfulness, total idea time, total conflict

b Dependent Variable: overall innovation

TABLE 6ANOVA- Organizational climate for creativity factors with innovation

Model

OCCfactors

Total

RegressionResidual

Sum of Squares

14635.44411701.931

26337.375

df

1029

39

Mean Square

1463.544403.515

F

3.627

Sig.

.003

a Predictors: (Constant), total trust, total debate, total idea supp., total risk, total challenge, total freedom,total liveliness, total playfulness, total idea time, total conflict


TABLE 7Coefficients of relationships between organizational creative climate (OCC) factors and innovation

Model

OCC (Constant)total challengetotal conflicttotal debatetotal freedomtotal idea supp.total idea timetotal livelinesstotal playfulnesstotal risktotal trust

UnstandardizedCoefficients

B Std. Error

65.3743.270

-4.786.560

3.3241.775-.6162.9982.0549.432E-02

.714

21.6153.4754.4161.3332.0802.0953.2182.0982.4702.1082.891

StandardizedCoefficients

Beta

.229-.344.060.326.157

-.051.295.224.009.071

t

3.024.941

-1.084.420

1.598.847

-.1911.429.832.045.247

Sig.

.005

.354

.287

.678

.121

.404

.850

.164

.412

.965

.807

CollinearityStatistics

Tolerance

.258

.152

.750

.368

.449

.216

.359

.212

.424

.185

VIF

3.8796.5931.3342.7202.2284.6192.7884.7132.3615.392

a Dependent Variable: overall innovation

(r=.673) and significant at (P<.01). Table 8 showsthe detailed correlation of each factor withinnovation. Table 9 reflects the amount ofcollinearity present among the factors of theorganizational creative climate. The conditionindex was very much less than 30.0 (thresholdvalue) which means the two CCQ factors have alow degree of collinearity with each other. Inaddition, results from Table 7 show that the VIFvalues of the factors are much less than 10.0which indicated low collinearity among thefactors.

In answering research question 2, a stepwiseregression was conducted to determine whichfactor/s is/are having high predictive power onthe dependent variable, innovation. There weretwo factors of such nature, namely, 'Freedom'and 'Liveliness/dynamism' as shown in Table10 and Table 11 where the values of t weresignificant (P<.05) for both factors, at 2.767 and2.641 respectively.

In answering research question 3, themultiple regression analysis was again conductedinvolving the seven dimensions of the learning


CCQ


TABLE 8Correlations of the organizational creative climate factors with innovation construct

Correlations index ( r ) P

Climate of Challenge/motivationClimate of conflictsClimate of debatesClimate of freedomClimate of idea timeClimate of idea supportClimate of liveliness/dynamismClimate of playfulness/humorClimate of risk takingClimate of trust

.738**

.726**.239.773**.833**.521**.766**.786**.549**.824**

.000

.000

.137

.000

.000

.001

.000

.000

.000

.000

** Correlation is significant at the .01 level (2-tailed)

TABLE 9Collinearity diagnostics

Model Dimension Eigenvalue Condition Index VarianceProportions(Constant)

total freedom total liveliness

1

2

12

123

1.9445.645E-02

2.9015.865E-024.019E-02

1.0005.868

1.0007.0338.496

.03

.97

.01

.95

.04

.03

.97

.01

.32

.67

.01

.08

.91


TABLE 10ANOVA: Organizational creative climate with innovation

Model

1

2

RegressionResidualTotal


Sum of Squares

10827.38915509.98626337.375

13287.84313049.53226337.375

df

13839

23739

Mean Square

10827.389408.158

6643.921352.690

F

26.527

18.838

Sig.

.000

.000

a Predictors: (Constant), total freedomb Predictors: (Constant), total freedom, total livelinessc Dependent Variable: overall innovation

organization with the innovation construct. Thefindings revealed that the learning organizationdimensions did explain significantly observedvariances of the members' perceptions oninnovation as much as 73.0% as seen from Tables12, 13, 14 respectively. The dimension 'Dialogueand Inquiry' (total dialogue) seemed to be having

significant relationship (P<.05) as seen fromcoefficients values (t= 2.222) in Table 15 below.This meant that 'Dialogue and Inquiry' could bethe dimension which has a high predictive poweron innovation. To confirm this assumption, themodel was tested once more using the stepwisemethod.



TABLE 11Coefficients of the relationship between the organizational creative climate factors and innovation (stepwise)

Model

1

2

(Constant)total freedom(Constant)total freedomtotal liveliness


B

86.7596.532

74.2284.1243.922

Std. Error

9.6441.268

10.1431.4901.485


Beta

.641

.405

.386

t

8.9965.1507.3182.7672.641

Sig.

.000

.000

.000

.009

.012


Tolerance

1.000

.626

.626

VIF

1.000

1.5981.598


TABLE 12Descriptives: Innovation construct and the dimensions of learning organization

Mean Std. Deviation N

overall innovationtotal continuous learntotal dialoguetotal embedded systotal empowermenttotal leadertotal system conntotal team learning

133.637.83

26.1523.2322.0321.4320.3523.20

25.992.615.484.925.385.745.485.18

4040404040404040

TABLE 13Model summary of the multiple regression analysis of the learning

organization dimensions with innovation construct

Model SummaryModel R Square Adjusted R Square Std. Error of the Estimate

1 .854 .730 .671 14.91

a Predictors: (Constant), total team learning, total continuous learn, total empowerment, total dialogue, totalembedded sys, total system conn., total leader


TABLE 14ANOVA- Dimensions of the learning organization with innovation construct

Model

1 RegressionResidualTotal

Sum of Squares

19222.9337114.442

26337.375

df

73239

Mean Square

2746.133222.326

F

12.352

Sig.

.000

a Predictors: (Constant), total team learning, total continuous learn, total empowerment, total dialogue, totalembedded sys. total system conn., total leader




TABLE 15Coefficients of relationship between learning dimensions and innovation

Model

DLOQfactors


(Constant)total continuous learntotal dialoguetotal embedded systotal empowermenttotal leadertotal system conntotal team learning

B

44.370.435

-1.8111.845.598

1.8391.062.697

Std. Error

13.1981.439.815.983.930

1.002.931.869


Beta

3.362.044

-.382.349.124.406.224.139

t

.002

.302-2.2221.877.643

1.8351.141.802

Sig.

.765

.034

.070

.525

.076

.262

.429


Tolerance

.404

.286

.244

.228

.172

.219

.281

VIF

2.4763.4994.1064.3845.8024.5753.560


TABLE 16Correlations of DLOQ dimensions with innovation construct

DLOQ Correlation index (r )

Continuous learningDialogue 8c inquiryEmbedded systemsEmpowermentLeadershipSystems connectionTeam learning

.420**

.511**

.700**

.696**

.798**

.722**

.647**

.003

.000

.000

.000

.000

.000

.000

** Correlations significant at the .01 level (2-tailed)

The results from Table 13 revealed that theseven dimensions of the learning organizationsignificantly explained 73.0% of the variances ininnovation (P<.05). In addition, the Pearson-Correlation coefficients for six of the sevendimensions against innovation are significantlyhigh at r>0.5 (Table 16) with the highest beingStrategic Leadership (r=-,798). The values ofVIF in Table 15 were less than 10.0, the thresholdvalue which indicated the collinearity amongthe seven dimensions of the DLOQ were low.

In answering question 4, the model wastested again to determine which of the sevendimensions of the learning culture is/are highlypredictive of the variance in innovation. In thestepwise method, the results of the analysis werepresented in Table 17 and Table 18. The singledimension providing 'Strategic Leadership' (totalleader) was seen as uniquely contributingsignificantly to the variance in innovation withthe t value larger than 2 (8.159) from Table 18.

TABLE 17ANOVA: Learning dimensions with innovation

Model

DLOQ Regressionfactors Residual

Total

Sum of Squares

16766.0229571.353

26337.375

df

13839

Mean Square

16766.022251.878

F

66.564

Sig.

.000

a Predictors: (Constant), total leaderb Dependent Variable: overall innovation



TABLE 18Coefficients of relationship between learning dimensions and innovation

Model

DLOQfactor

(Constant)total leader


B Std.

56.198 93.614

. Error

.816443


Beta

.798

t

5.7258.159

Sig.

.000

.000


Tolerance

1.000

VIF

1.000


In answering research question 5, a multipleregression analysis was undertaken with bothsets of independent variables. The results wereshown in Tables 19, 20, and 21 respectively. Thefindings revealed that both sets of variablestogether explained 80.4% of the variance ininnovation.

From the tables above, it was observed thatboth sets of the independent variables togethersignificantly explained 80.4% of the variance inthe innovation construct, a higher value thaneither of the separate variables alone. Recall thatorganizational creative climate factors didcontribute significantly (55.6%) to theexplanation of the variance in innovation andthe learning organization dimensions on its owncontributed 73.0% of the variance in innovation.But when both variables were taken intoconsideration together, an increase in theexplanation of the variance in innovation wasrecorded. In the full model the learningorganization dimension, 'Dialogue and Inquiry'

was seen as having a significantly high predictivepower on the dependent variable (Table 21)with absolute t value of 2.709. To confirmwhether the learning dimension of 'Dialogueand Inquiry' was the one having the highestpredictive power of the variance in innovationbased on the full model, a stepwise regressionwas conducted. From this model a regressionequation was obtained. The results of the analysisresults are shown in Tables 22, Table 23 andTable 24 below.

From Table 22 and Table 23 and thecoefficient of Table 24, 'Strategic Leadership'(total leader) was the single predictor factor ofthe full model which seemed to uniquelycontribute to the variance in innovation. Thusthe full regression model equation obtainedwhich could be used to predict the dependentvariable given the values of the independentvariables within this case organization is:

Innovation = 56.198 + .798 (strategic leadership)

TABLE 19Model summary of the multiple regression analysis using both sets of independent variables

Model R Square Adjusted R Square Std. Error of the Estimate

.897 .804 .653 15.31

TABLE 20ANOVA: Organizational creative climate factors, learning organization dimensions with innovation construct

Model

OCC withDLOQfactors


Sum of Squares

21178.2525159.123

26337.375

df

172239

Mean Square

1245.780234.506

F

5.312

Sig.

.000

a Predictors: (Constant), team, overall conflict, overall dynamism, system connection, overall risk taking,overall humour, overall trust, overall freedom, overall idea support, embedded system, overall time,continuous learning, overall challenge, overall debates, leadership, dialogue, empowerment




TABLE 21Coefficients: Relationship between creative climate factors, learning dimensions with innovation

Model

occWithDLOQfactors


(Constant)

total continuous learntotal dialoguetotal embedded systotal empowermenttotal leadertotal team learningtotal system conntotal challengetotal conflicttotal debatetotal freedomtotal idea supp.total idea timetotal livelinesstotal playfulnesstotal risktotal trust

B

48.463

.519-2.9862.301.575

1.9101.0601.1923.448

-4.9431.0462.8352.471

-5.733-.1361.986

-1.8271.072

Std. Error

18.512

1.8161.1021.1461.1821.3041.0571.0962.9463.5471.2761.8431.8632.8841.9321.9571.9162.598


Beta

.052-.630.436.119.422.212.252.242

-.356.112.278.218

-.474-.013.216

-.165.107

t

2.618

.286-2.7092.008

.4871.4641.0021.0881.171

-1.394.820

1.5381.326

-1.988-.0711.015-.953.413

Sig.

.016

.778

.013

.057

.631

.157

.327

.289

.254

.177

.421

.138

.198

.059

.944

.321

.351

.684


Tolerance

.268

.165

.189

.149

.107

.200

.166

.209

.137

.475

.272

.330

.157

.246

.196

.298

.133

VIF

3.7366.0655.2896.7109.3164.9996.0114.7967.3192.1033.6773.0326.3864.0685.0943.3577.493


TABLE 22Model summary of the multiple regression analysis using both sets of independent variables (Stepwise)

Model

1

R

.798

Square

.637

Adjusted R Square

.627

Std. Error of the Estimate

15.87

Predictors: (Constant), total leaderDependent variable: overall innovation

TABLE 23ANOVA: Two sets of independent variables with innovation

Model

OCC withDLOQfactors


Sum of Squares

16766.0229571.353

26337.375

df

13839

Mean Square

16766.022251.878

F

66.564

Sig.

.000

a Predictors: (Constant), total leaderb Dependent Variable: overall innovation

This means that the innovation occurring inthe case organization is a function of the singlelearning factor of 'strategic leadership'.Innovation in this organization is moreinfluenced by the strategic leadership more thanthe rest of the other learning factors or creative

climate factors; which indicates that theleadership of the top and maybe the middlemanagement is the driving force behind anyinnovative activities occurring within theorganization.


Azahari Ismail, Meriam Ismail, Bahaman Abu Samah, Shamsuddin Ahmad, Khairuddin Idris &Jegak Uli

TABLE 24Coefficients of relationship between two sets of independent variables and innovation

Model

OCCWithDLOQ

(Constant)

total leader


B Std. Error

56.198 9.816

3.614 .443


Beta

.798

t

5.725

8.159

Sig.

.000

.000


Tolerance

1.000

VIF

1.000


The results from Table 24 also show thatthe learning dimension Total Leader (Beta=.798)alone has a significantly high predictive poweron innovation construct which answered researchquestion 6.

In answering research question 7, therespondents were grouped into different jobhierarchical levels. Group 1 consisted of top/senior management levels in the organization.Group 2 comprised the middle/lower managersand supervisors and group 3 was the support/administrative staff who were non-executives allof whom have at least 'A' level academicqualification or equivalent. The analysis usedone-way analysis of variance (one-way AN OVA)to determine whether there existed significantdifference on perceptions towards innovation.

The results were shown in Tables 25 and 26.From the results above it could be deduced

that there was no statistically significant differencein perceptions towards innovation by the threedifferent groups (P>.05).

From the results of ANOVA in Table 26, itcan be deduced that the perceptions onorganizational creative climate in theorganization by the three different groups werenot significantly different.

The results from ANOVA analysis in Table27 revealed that there is no statistically significantdifference on the perceptions on organizationallearning from the three groups of employees.For the three different ANOVA analyses above,the Levene's test of homogeneity of variance wasmet.

TABLE 25ANOVA overall innovation

Between Groups

Within GroupsTotal

Between Groups

Within GroupsTotal

(Combined)Linear Term

(Combined)Linear Term

UnweightedWeightedDeviation

Sum of Squares

1408.504940.900

1139.613268.891

24928.87126337.375

TABLE 26ANOVA - overall climate

UnweightedWeightedDeviation

Sum of Squares

251.1745.1368.485E-02

251.0899916.426

10167.600

df

2111

3739

df

2111

3739

Mean Square

704.252940.900

1139.613268.891673.753

Mean Square

125.5875.1368.485E-02

251.089268.012

F

1.0451.3971.691.399

F

.469

.019

.000

.937

Sig.

.362

.245

.201

.531

Sig.

.630

.891

.986

.339



TABLE 27ANOVA- overall learning

Between Groups

Within GroupsTotal

(Combined)Linear Term Unweighted

WeightedDeviation

Sum of Squares

165.80336,73661.039

104.76410985.97211151.775

df

2111

3739

Mean Square

82.90136.73661.039

104.764296.918

F

.279

.124

.206

.353

Sig.

.758

.727

.653

.556

In answering research question 8, ANOVAand independent sample T-Test were used again.All the analyses revealed no significant differencesof the factors on those three perceptions.

DISCUSSIONS AND CONCLUSIONThe rapid changes in the global environment islikely to force organizations to constantlyinnovate by Organizational Development (OD)theory so as to gain sustainable competitiveadvantage (Hitt et al 1999; Porter 1985; Zhengand Das 2000).To innovate, organizations haveto change in various ways and this needs to bedone by having certain creative climates to helpfoster organizational members in facilitating thechange efforts (Amabile 1999; Axtel et al 2000;Ekvall et al 1983; Zain and Rickards 1995). Toinnovate, organization members must also becommitted to learning at a faster rate in orderto succeed over their competitors in the changeprocess (Argyris and Schon 1978; Drucker 1988;Garvin 1993; Nonaka and Takeuchi 1995; Senge1990; Watkins and Marsick 1996a). The successof the learning depends on the structure andstrategies (Donellon 1996) present in theorganizational system which the seven dimensionsof a learning organization can cater for.

The findings from the analysis were crucialfor exploring the relationship betweenorganizational climates for creativity and learningculture on innovation constructs. Variousnumbers of practical implications could be drawnfrom the findings which could be of use for thecase organization. For example, one of thefindings revealed that the organizational creativeclimate in this case organization did significantlycontribute to predicting innovation amongemployees with the factors 'Freedom' and'Liveliness/dynamism' as being good predictors;but the learning culture, particularly one whichwas related to 'Strategic Leadership' being

practised within and outside the case organizationconcerned, on the other hand, contributedtremendously to the innovation as perceived bythe employees of various levels. This couldindicate that this case organization when it cameto innovation was primarily motivated by the topmanagement more than by the employees downthe line.

The findings also implied that other factorsfrom the organizational creative climate withthe exception of climate of freedom and a climateliveliness/dynamism should be given moreemphasis in future to precipitate the innovationto occur. In addition, the other six learningfactors besides "Strategic Leadership" should alsobe given more attention for similar reasons.

In summary, it can be concluded that forthis particular organization, the learningorganization dimension of 'Strategic Leadership'had a high predictive power on innovationactivities occurring within the organization ascompared to the organizational creative climatefactors. It could be concluded also that the caseorganization did to a certain extent inculcatesignificantly a climate of creativity for themembers to innovate and did to a larger extentinculcate a culture of learning among themembers.

Further analyses also showed that there wereno significant differences in members 'perceptions on innovation, creative climate orlearning culture from the three job levels: topmanagement, middle management and the staffdown the line. This meant that almost allmembers have the same perception on thoseideas.

RECOMMENDATIONSFor innovation to occur at a faster andcontinuous rate, the presence of creative climateand a learning culture should be encouraged. In



this regard, the organization should be lookinginto ways of improving its creative climate by:(1) making the climate at work morechallenging/motivating which meant gettingemotional involvement of the members in theorganization's operations and goals; (2) makingthe climate more open and trustworthy throughthe presence of emotional safety in relationships;(3) the management giving more time formembers to elaborate on new ideas; (4) themembers displaying more spontaneity and easein actions; (5) reducing the presence ofemotional tensions (conflicts) duringinteractions; (6) having the management givemore support to new ideas brought up; (7)debating on viewpoints and on ideas forwarded;(8) encouraging members to take risks onopportunities.

Although the learning culture seemed to becontributing substantially towards the innovationin the case organization, the case organizationshould improve its learning on these areas aswell as provide a strong strategic leadership. Theareas are (1) giving more emphasis to individuallearning so that learning can occur at acontinuous basis; (2) by giving emphasis onteam learning; (3) by giving emphasis onorganizational learning (embedded systems andsystems connection) through environmentscanning and networking, and capturing learningon the organization systems; (4) by empoweringits members; and (5) by encouraging dialogueand inquiry to occur among them.

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APPENDIX 1

Results of POST HOC factor analysis of the innovation construct

Items

Technological transfer (assimilation)1. Absorpcap52. Absorpcap63. Absorpcap44. Absorpcap95. Absorpcap26. Absorpcap87. AbsorpcaplO8. Absorpcap39. Absorpcap710. Absorpcapl411. Absorpcapll12. Absorpcapl13. Absorpcapl3Diffusion of innovation14. Diffussion315. Diffussion216. Absorpcapl717. Diffussionl18. Absorpcapl919. Absorpcapl620. Diffussion521. Absorpcapl822. Diffussion423. Absorpcapl224. Absorpcapl5Organizational innovation25. ISO226. ISO327. ISO128. ISO729. ISO630. ISO831. ISO432. ISO5

EigenvalueCumulative percent variance

Technological

Factor 1

.790

.728

.727

.723

.722

.715

.701

.678

.677

.669

.666

.653

.577

.2593.683E-02

.136

.279

.338

.200

.406

.392

.379

.402

.436

.284

.308

.283

.271

.384

.317

.277

.333

17.12153.502

innovation

Factor 2

.204

.265

.377

.396

.2509.207E-02

.392

.184

.311

.285

.2809.702E-02

.486

.786

.780

.751

.744

.642

.624

.614

.607

.585

.566

.548

.264

.216

.305

.209

.201

.277

.349

.437

2.2847.139

Organizational innovation

Factor 3

.230

.358

.109

.197

.347

.301

.160

.387

.325

.322

.256

.416

.323

.1709.114E-02

.242

.239

.294

.192

.346

.238

.363

.225

.255

.823

.819

.794

.791

.776

.759

.749

.520

1.9786.182

N = 259Extraction method: Principal component analysis.Rotation method: Varimax with Kaiser Normalization



Perbandingan Pencapaian Kognitif, Afektif dan Kompetensi Pelajar ProgramKeusahawanan Remaja yang Berlainan Latar Belakang Keluarga

NORASMAH HJ. OTHMAN1 8c ZAIDATOL AKMALIAH LOPE PIHIE2

Universiti Kebangsaan Malaysia43600 UKM Bangi, Selangar, Malaysia

2Universiti Putra Malaysia43400 UPM Serdang, Selangar, Malaysia

Kata kunci: Pencapaian kognitif, afektif, kompetensi pelajar keusahawanan

ABSTRAK

Keadaan persekitaran yang sesuai berkemungkinan besar dapat mengembangkan bakat dankebolehan seseorang ke tahap tinggi dalam bidang-bidang yang diperlukan masyarakat. Persekitaranyang dimaksudkan adalah berkaitan dengan latar belakang seseorang. Banyak kajian menyatakanlatar belakang serta pegangan tradisi seseorang memberi kesan terhadap pembentukan peribadiseseorang. Oleh itu, kajian ini bertujuan meninjau sejauh mana latar belakang berupayamempengaruh pencapaian kognitif, afektif dan kompetensi pelajar dalam bidang keusahawanan.Kajian ini menggunakan kaedah tinjauan sebagai kaedah kajian. Set soal selidik dan ujian telahdigunakan untuk menguji pencapaian kognitif, afektif dan kompetensi. Seterusnya, perbandinganpencapaian kognitif, afektif dan kompetensi pelajar Program Keusahawanan Remaja yang berlainanlatar belakang keluarga telah dibuat melalui ujian MANOVA. Ujian ini telah digunakan dalamusaha mengenal pasti persamaan dan perbezaan yang mungkin wujud dalam pencapaian pelajar.Hasilnya, dapatan menunjukkan tidak terdapat perbezaan signifikan dalam pencapaian pelajaryang mempunyai latar belakang keluarga yang berbeza.

ABSTRACT

A conducive environment may develop one's potential and ability to the needs of the societyaccording to their respective fields. The environment refers to students' background. Studies haveshown that one's background and beliefs (culture) affect the development of one's personality.Thus, the purpose of this research was to determine how student's background may influencetheir cognitive, affective and competency achievement in entrepreneurship. Samples were fromthe Adolescent Entrepreneurship Program. A questionnaire and a test were employed as thesurvey instrument in order to get student's achievement in cognitive, affective and competency.In addition a comparison of student's achievement in cognitive, affective and compentency wereconducted in order to see their similarities and differences. The MANOVA technique wasemployed to gather this information. The results of this research indicated no significantdifferent between types of paternal employment with student's achievement in general.

PENDAHULUANBloom (1985) mengatakan bahawa dalamkeadaan yang sesuai, bakat, kebolehan danpencapaian seseorang berkemungkinan besarberkembang mengikut peluang-peluangpembelajaran yang ditawarkan di persekitarannya.Persekitaran yang dimaksudkan di sini berkaitrapat dengan latar belakang seseorang. Initernyata benar apabila banyak kajian

menunjukkan latar belakang serta pegangantradisi sesebuah keluarga pen ting dalampembentukan peribadi seseorang. Sehubunganitu, ramai berpendapat bahawa seseorang yangmempunyai keluarga terlibat dalam perniagaanatau bekerja sendiri akan lebih terdorong kebidang keusahawanan.

Seterusnya Rexroad (1985), Metcalf (1985),Mann (1990) dan Robiah (1990) didapati

Norasmah Hj. Othman & Zaidatol Akmaliah Lope Pihie

mempunyai pendapat yang selari dengan Bloom(1985). Kesemua mereka berpendapat bahawaperkembangan bakat di kalangan pelajar banyakdipengaruhi oleh latar belakang keluarga,terutama dari segi sikap mereka terhadap sesuatuperkara. Pendeknya, walaupun tidak terlibatsecara langsung dalam sebarang aktiviti yangdisertai anak-anak mereka, golongan ibu bapadikenal pasti sebagai mempunyai pengaruh besarterhadap pencapaian pelajar terutama dalampencapaian akademik. Malah, latar belakangkeluarga mampu memberi persekitaran yangboleh mendorong seseorang mempelajari sesuatuperkara, contohnya urusan perniagaan. Dengankata lain, keluarga terutamanya ibu bapamerupakan pendorong utama kejayaan seseorangdalam menguasai sesuatu perkara.

Kajian Bannock dan Stanworth (1990)mendapati latar belakang keluarga berupayamempengaruhi pelajar. Umpamanya, jika ibubapa pelajar terlibat dalam perniagaan, pelajarjuga akan terdorong kepada bidang perniagaan.Ini jelas apabila dapatan kajian merekamenunjukkan bahawa tahap pencapaiangolongan pelajar yang berlatarbelakangkankeluarga usahawan dalam ujian berkaitankeusahawanan, sama ada dari segi pencapaiankognitif, afektif dan kompetensinya adalah lebihbaik berbanding pelajar yang tidak mempunyailatar belakang keusahawanan.

Selain faktor keluarga, faktor jantina pelajarjuga sering kali dikaitkan dengan tahappencapaian pelajar dalam ujian pencapaiankeusahawanan baik dari aspek kognitif, afektifdan kompetensi. Banyak kajian menunjukkanbahawa terdapat sedikit perbezaan antarapencapaian pelajar lelaki dan pelajar perempuandalam ujian berkaitan keusahawanan. Contohnya,kajian Wee Liang Tan, Siew Lai Kuan, Wei HongTan dan Siow Ching Wong (1995) secaraexploratori yang menguji ciri-ciri keusahawanandi kalangan pelajar di Singapura. Terdapat enamciri keusahawanan yang dikaji, iaitu beranimenanggung risiko, kawalan dalaman diri,inovatif, kepimpinan, berkeyakinan dankeinginan untuk cemerlang. Hasil kajianmenunjukkan 47% daripada responden (n =240 pelajar) memiliki ciri-ciri keusahawanan; danhampir 51% responden tersebut adalah pelajarlelaki. Bagaimanapun, ujian Khi-Kuasa duamenunjukkan tidak terdapat perbezaan yangsignifikan antara pelajar lelaki dan perempuan.

Sementara, kajian Sharifah Kamaliah (1996)terhadap 390 pelajar di Daerah Hulu Langatyang mengukur 13 ciri keusahawanan di kalanganpelajar Tingkatan 4 menunjukkan terdapatperbezaan yang signifikan antara ciri-cirikeusahawanan pelajar lelaki dan pelajarperempuan (ujian-t ^2.49, p<0.05). Dapatan yangsama juga diperoleh dalam kajian ZaidatolAkmaliah, Mohd. Majid, Abd. Rahim danGenevieve (1998). Kajian mereka terhadap 1336pelajar yang dijalankan secara tinjauanmendapati bahawa terdapat perbezaan yangsignifikan antara sikap pelajar lelaki dengan sikappelajar perempuan terhadap keusahawanan(ujian-t =5.09, p<0.05).

Oleh itu, huraian serta dapatan di atasmenunjukkan bahawa secara keseluruhannyajantina dan latar belakang keluarga pelajar adamempunyai kaitan terhadap pencapaian pelajardalam bidang keusahawanan, baik dari segipencapaian kognitif, afektif dan kompetensinya.

TUJUAN KAJIAN

Kajian ini bertujuan untuk meninjau sejauh manafaktor latar belakang pelajar berupayamempengaruhi pencapaian tingkah laku kognitif,afektif dan kompetensi pelajar ProgramUsahawan Muda (PUM) dan Program TunasBistari (PTB) dalam bidang berkaitan keusaha-wanan, Secara terperinci, kajian ini ingin melihatsama ada terdapat atau tidak perbezaanpencapaian tingkah laku kognitif, afektif dankompetensi keusahawanan antara pelajar lelakidengan pelajar perempuan PUM dan PTB.Begitu juga, dengan persamaan dan perbezaanyang mungkin wujud antara pelajar yangmempunyai latar belakang keluarga berbeza.

OBJEKTIF KAJIAN

Secara terperinci, objektif kajian adalah untuk:1. Mengenal pasti perbezaan pencapaian

tingkah laku kognitif, afektif dan kompetensipelajar PUM dan PTB.

2. Mengenal pasti perbezaan pencapaiantingkah laku kognitif, afektif dan kompetensipelajar lelaki dan pelajar perempuan PUMdan PTB.

3. Mengenal pasti perbezaan pencapaiantingkah laku kognitif, afektif dan kompetensipelajar yang mempunyai latar belakangkeluarga yang berbeza.


Perbandingan Pencapaian Kognitif, Afektif dan Kompetensi Pelajar Program Keusahawanan Remaja

Hipotesis Kajian

Ho 1: Tidak terdapat perbezaan yang signifikandalam pencapaian tingkah laku kognitif,afektif dan kompetensi antara pelajarPUM dan PTB.

Ho2: Tidak terdapat perbezaan yang signifikandalam pencapaian tingkah laku kognitif,afektif dan kompetensi antara pelajarlelaki dan pelajar perempuan PUM danPTB.

Ho3: Tidak terdapat perbezaan yang signifikandalam pencapaian tingkah laku kognitif,afektif dan kompetensi antara pelajarPUM dan PTB yang berlainan latarbelakang keluarga.

METODOLOGIKajian ini menggunakan kaedah tinjauan sebagaikaedah kajian. Pilihan terhadap kaedah ini dibuatkerana ia bersesuaian dengan kehendak pengkajiyang ingin mengenal pasti persamaan danperbezaan yang mungkin wujud dalampencapaian tingkah laku kognitif, afektif,kompetensi keusahawanan pelajar PUM dan PTBberdasarkan latar belakang pelajar. Menurut Finkdan Kasecoff (1985), kaedah tinjauan merupakansatu bentuk yang sesuai digunakan dalam kajianyang bertujuan mencari serta mengumpulmaklumat. Tambah mereka lagi, kaedah inisesuai digunakan dalam menerangkan statussesuatu perkara, mempamerkan perubahan danjuga dalam membuat perbandingan.

Instrumen

Kajian ini menggunakan soal selidik dan ujianpencapaian bagi menguji hipotesis kajian. Bagimenguji pencapaian tingkah laku afektif, soalselidik yang diadaptasi daripada ZaidatolAkmaliah et al. (1998) telah digunakan. Soalselidik ini mengkehendaki pelajar menentukansendiri bagaimana perasaan mereka terhadapsesuatu situasi secara jujur, dan skala likert limapoin digunakan untuk menunjukkan persetujuandan sebaliknya bagi setiap pemyataan. Skala likertlima poin itu adalah: 1 = Sangat Tidak Setuju, 2= Tidak Setuju, 3 = Kurang Setuju, 4 = Setuju,dan 5 = Sangat Setuju. Berdasarkan jawapantersebut, dijangka tingkah laku afektif akan dapatdiukur mengikut persepsi pelajar. Seterusnya,tahap pencapaian tingkah laku afektif akandiukur dengan berpandukan kepada jadualinterpretasi skor min seperti jadual berikut.

JADUAL 1Jadual interpretasi skor min dimensi

tingkah laku afektif

Skor min Interpretasi skor min

LOO- 2.002.01 - 3.003.01 - 4.004.01 - 5.00

RendahSederhana rendahSederhana tinggiTinggi

Bagi pencapaian tingkah laku kognitif dankompetensi keusahawanan, instrumen ujiandigunakan oleh pengkaji. Set ujian inimerangkumi semua aspek yang telah dipelajarioleh pelajar sepanjang menyertai program, danmerupakan cara terbaik untuk mengukurpengetahuan dan kefahaman pelajar (Collin1991). Bagi pembinaan ujian tingkah lakukompetensi keusahawanan, senarai kompetensiBettencourt dalam Zaidatol Akmaliah (1992)telah digunakan. Senarai kompetensi ini sesuaidigunakan kerana ia telah dibentuk khas untukpelajar sekolah menengah. Pembinaan ujiantingkah laku kognitif pula adalah berdasarkankepada perkara-perkara yang telah dipelajaripelajar. Untuk tujuan mengenal pasti tahappencapaian tingkah laku kognitif dan kompetensikeusahawanan pelajar, skala permarkahan yangsering digunakan dalam peperiksaan di sekolahdijadikan sebagai panduan. Justeru, skalapemarkahan dari Jabatan Pendidikan NegeriSelangor digunakan sebagai panduan pemberianmarkah lulus atau gagal kepada pelajar. Skalapemarkahan tersebut adalah seperti Jadual 2 dibawah:

JADUAL 2Skala pemarkahan dimensi tingkah laku kognitif

dan kompetensi keusahawanan

Skor markah

40% ke41% -50% -65% -

80% -

bawah49%64%79%100%

Interpretasi peratus skor

GagalLemahSederhanaBaikCemerlang

Sampel Kajian

Secara keseluruhan populasi kajian terdiridaripada ahli lembaga pengarah (ALP) Program



Usahawan Muda (PUM) dan Program TunasBistari (PTB). PUM ialah program keusahawananremaja yang dianjurkan oleh KementerianPembangunan Usahawan dengan kerjasamaKementerian Pendidikan Malaysia. PTB pulamerupakan program keusahawanan remaja yangdianjurkan oleh Institut PembangunanPengurusan Johor, sebuah syarikat dalamPerbadanan Johor dengan kerjasama JabatanPendidikan Negeri Johor.

Penggunaan ALP dibuat kerana tidak semuanegeri memberi kursus keusahawanan kepadasemua ahli programnya, dan kebanyakannyakursus-kursus hanya ditawarkan kepada ALPprogram sahaja. Justeru, daripada jumlah ahliseramai 7,307 orang bagi PUM dan 765 orangbagi PTB, hanya 2050 orang PUM dan 150orang PTB sahaja yang layak menjadi kumpulansasaran (Laporan Tahunan KementerianPembangunan Usahawan dan InstitutPembangunan Pengurusan Johor 1999).

Setelah mengenal pasti kumpulan sasarankajian, barulah pemilihan sampel dilaksanakan.Oleh kerana mempunyai kumpulan sasaran yangramai dan terdapat di serata tempat, prosespemilihan sampel dibuat dalam dua peringkat.Peringkat pertama ialah peringkat di manapemilihan sampel dibuat secara rawak berasaskanpensampelan berkelompok (cluster sampling)iaitu dalam bentuk zon. Dalam peringkat inibeberapa negeri/daerah dikumpulkan mengikutzon seperti zon utara, zon tengah, zon barat,zon timur dan zon selatan. Menurut Reaves(1992) dan Cohen dan Manion (1994),pensampelan secara berkelompok sesuai jikapopulasi besar dan bertaburan di serata tempat.Selain itu, Reaves juga mengatakan bahawapensampelan cara ini dapat menjimatkan masaserta mengurangkan pelbagai masalah. Peringkatkedua ialah peringkat di mana pengkaji akanmembuat pemilihan secara rawak bagi tujuanmengenal pasti negeri/daerah yang akan diambilbagi mewakili setiap zon. Setelah negeri/daerahdikenal pasti, sampel kajian akan diambil darisemua sekolah di negeri/daerah yang terpilihserta terlibat dengan program keusahawananremaja.

Dalam menentukan saiz sampel pula,pengkaji telah menggunakan jadual penentuanReaves (1992) dengan berasaskan jumlahkumpulan sasaran. Berpandukan jadual tersebut,seramai 339 ALP PUM dan 110 ALP PTB telahdipilih sebagai sampel kajian. Namun bagi PTB

ini, pengkaji telah mengambil kesemua ALPnya(150 orang) sebagai sampel kajian kerana jumlahkumpulan sasarannya yang sedikit.

Tata cara Penganalisisan DataData kajian dikumpul mengikut set instrumenseperti soal selidik dan ujian. Setelah semuainstrumen diperoleh, proses pengekodandijalankan untuk memudahkan aktivitimemasukkan data ke dalam program SPSS versi10. Proses penganalisisan data melibatkan duajenis statistik iaitu deskriptif dan inferensi.

Statistik deskriptif yang digunakan ialahperatusan, min dan sisihan piawai. Manakala,statistik inferensi pula digunakan untuk melihatpersamaan dan perbezaan seperti analisis variansberganda (MANOVA).

DAPATAN KAJIAN

Perbandingan pencapaian tingkah laku kognitif,afektif dan kompetensi pelajar (pemboleh ubahbersandar) berdasarkan program (PUM danPTB), jantina (lelaki dan perempuan) dan latarbelakang pekerjaan penjaga (kerajaan, swasta,peniaga, petani dan tidak bekerja) telah dianalisissecara serentak. Program, jantina dan latarbelakang pekerjaan penjaga pelajar merupakanpemboleh ubah tak bersandar kajian. Olehkerana perbandingan dijalankan serentak, makaujian MANOVA digunakan bagi menguji tigahipotesis berikut:Hoi: Tidak terdapat perbezaan yang signifikan

dalam pencapaian tingkah laku kognitif,afektif dan kompetensi antara pelajarPUM dan PTB.

Ho2: Tidak terdapat perbezaan yang signifikandalam pencapaian tingkah laku kognitif,afektif dan kompetensi antara pelajarlelaki dan pelajar perempuan PUM danPTB.

Ho3: Tidak terdapat perbezaan yang signifikandalam pencapaian tingkah laku kognitif,afektif dan kompetensi antara pelajar yangberlainan latar belakang keluarga.

Sebelum ujian MANOVA dijalankan,pengkaji terlebih dahulu menjalankan ujian bagimenentukan kehomogenan varian-kovariandengan menggunakan ujian Box's M (Box's Mtest). Ujian ini penting untuk menentukan samaada varian-kovarian di kalangan pembolehubahbersandar adalah sama atau tidak, merentasisemua pembolehubah tak bersandar. Ini



merupakan prasyarat penting bagi ujianMANOVA. Ujian MANOVA mengandaikanbahawa varian-kovarian di kalangan pemboleh-ubah bersandar adalah sama, merentasi semuapembolehubah bebas. Dalam hal ini, jika nilaiparas kesignifikanan lebih besar dari 0.01, makaini bermakna ujian MANOVA boleh digunakan(Tabachnick dan Fidell 1996).

Jadual 3 menunjukkan hasil ujian Box's Myang menunjukkan tidak terdapat perbezaanyang signifikan di kalangan pembolehubahbersandar untuk semua pembolehubah takbersandar apabila nilai F (96,532) =0.82, p>0.05.

Box's M

147.95

F

0.86

JADUALUjian Box'

dk 1 dk2

96 532

3s M

paras kesignifikanan

0.82

Dalam analisis MANOVA ini, ujian statistikPillai's Trace telah digunakan kerana bilangansampel kajian antara program (PUM dan PTB)didapati tidak sama. Menurut Tabachinck danFidell (1996), Pillai's Trace sesuai digunakanjika perkara-perkara seperti saiz sampel kecil,bilangan sampel tidak sama atau pun tidakmenepati prasyarat (violation of assumptions).

Jadual 4 menunjukkan analisis data yangdiperoleh hasil daripada ujian MANOVA. Dataini menunjukkan sama ada terdapat atau tidakpersamaan atau perbezaan antara pencapaiantingkah laku pelajar berdasarkan program,jantina dan latar belakang pekerjaan penjaga.Hasilnya, Jadual 4 menunjukkan terdapat

perbezaan yang signifikan antara pencapaiantingkah laku pelajar berdasarkan program. Inidapat dilihat dengan jelas apabila nilai Pillai'sTrace = 0.53 dan nilai F (3,379) =7.12, p<0.05.Manakala, tiada perbezaan yang signifikan dalampencapaian tingkah laku pelajar berdasarkanjantina dan latar belakang pekerjaan penjaga.Ini ditunjukkan apabila nilai Pillai's Trace bagijantina ialah 0.13 dengan nilai F (3,379) • 1.71,p>0.05. Begitu juga dengan latar belakangpekerjaan penjaga apabila nilai Pillai's Traceialah 0.02 dengan nilai F(12, 1143) = 0.69, p>0.05.

Bagi kesan interaksi antara program denganjantina, nilai Pillai's Trace yang diterima ialah0.00. Sementara, nilai F (3, 379) = 0.45, p> 0.05.Kesan interaksi antara program dengan latarbelakang pekerjaan penjaga ialah 0.28; nilai F(12, 1143) = 0.89, p>0.05. Interaksi antara jantinadengan latar belakang pekerjaan penjaga pelajarmenunjukkan nilai Pillai's Trace ialah 0.02;dengan nilai F (12, 1143) =0.87, p> 0.05.Manakala, interaksi antara program, jantina danlatar belakang pekerjaan penjaga pulamenunjukkan nilai Pillai's Trace 0.01 dengannilai F (12,1143) =0.26, p> 0.05. Analisis-analisisdata ini menerangkan bahawa tidak terdapatkesan interaksi yang signifikan antara program,jantina dan latar belakang pekerjaan penjagaterhadap pencapaian tingkah laku pelajar.

Lanjutan daripada Jadual 4, analisis ANOVAberganda seperti Jadual 5 dilakukan untukmelihat perbezaan min bagi setiap pembolehubah bersandar berdasarkan program, jantinadan juga latar belakang pekerjaan penjaga.

Berdasarkan Jadual 5, didapati hanyaterdapat satu perbezaan yang signifikan iaitu

Kesan

JADUAL 4Analisis MANOVA: Perbezaan pencapaian tingkah laku pelajar berdasarkan

program, jantina dan latar belakang pekerjaan penjaga pelajar

nilai Pillai's Trace darjah antarakumpulan

darjah dalamkumpulan

paras kesignifikanan

ProgramJantinaKpenjaga3

0.530.130.02

7.121.710.69

3312

3793791143

0.00*0.170.76

Program * JantinaProgram* KpenjagaJantina *KpenjagaProgram* jantina*kpenjaga

0.000.030.020.01

0.450.890.570.26

3121212

379114311431143

0.720.550.870.99

Kpenjaga3 = latar belakang pekerjaan penjaga


Norasmah Hj. Othman 8c Zaidatol Akmaliah Lope Pihie

JADUAL 5Ujian ANOVA berganda: Perbandingan pencapaian tingkah laku kompetensi, kognitif,

afektif berdasarkan program, jantina dan latar belakang pekerjaan penjaga

Kesan

Program

Jantina

Kpenjaga3

Program *Jantina

Program*Kpenjaga

Pemboleh ubahbersandar

KompetensiKognitifAfektif





jkd

16.03181.19

7.81E-02

6.324.200.18

53.5217.507.45E-02

12.120.061.97E-04

56.8927.640.11

dk

11

1

111444

11144

4

mkd

16.03181.19

7.81E-02

6.324.200.18

13.384.371.87E-02

12.120.061.97E-04

14.226.916.52E-02

F

1.7215.08

1.51

0.670.353.481.420.360.36

1.290.000.001.510.560.51

sig.

0.190.00*0.22

0.410.560.060.220.830.84

0.260.950.950.200.680.73

Kpenjaga8 = latar belakang pekerjaan penjaga

pencapaian tingkah laku kognitif antara programdengan nilai F(l,401) =15.08, p<0.05. Ini jelasdapat dilihat dalam Jadual 6 (sila rujuk LampiranA) apabila min dimensi tingkah laku kognitifpelajar PUM ialah 16.22 (s.p =0.27) dan minpelajar PTB pula ialah 14.06 (s.p =0.48). Inibermakna pelajar PUM mempunyai pencapaianyang lebih baik daripada pelajar PTB dalamujian tingkah laku kognitif secara signifikan.Sementara, pencapaian tingkah laku kompetensidan tingkah laku afektif antara pelajar PUM danPTB menunjukkan tidak terdapatnya perbezaanyang signifikan. Ini jelas apabila nilai F( 1,401) =1.72, p>0.05 bagi pencapaian tingkah lakukompetensi. Secara terperinci, min pencapaiantingkah laku kompetensi pelajar PUM ialah 10.56(s.p =0.24) dan min PTB ialah 11.18 (s.p =0.43).Begitu juga dengan pencapaian tingkah lakuafektif apabila nilai F (1,401) =1.51, p>0.05;walau pun min PUM adalah lebih tinggi sedikitdaripada min PTB (min PUM =3.87, s.p =0.02;min PTB =3.78, s.p = 0.03) (sila rujuk Jadual 6 diLampiran A).

Seterusnya, Jadual 5 menunjukkan bahawatidak terdapat perbezaan yang signifikan antarapencapaian tingkah laku kompetensi, kognitifdan afektif antara pelajar lelaki dan pelajarperempuan. Ini jelas ditunjukkan dalam jadualapabila nilai F (1,401) =0.67, p>0.05 bagi tingkah

laku kompetensi; sementara, bagi tingkah lakukognitif nilai F(l,401) = 0.35, p>0.05; dan nilaiF( 1,401) =3.48, p>0.05 bagi tingkah laku afektif.Ini terbukti apabila min pencapaian tingkahlaku kompetensi pelajar lelaki ialah 10.65 (s.p=0.38) dan min pelajar perempuan ialah 11.06(s.p =0.32). Manakala, min pencapaian tingkahlaku kognitif pelajar lelaki ialah 15.30 (s.p =0.43)dan min pelajar perempuan ialah 14.98 (s.p0.36). Begitu juga dengan min tingkah lakuafektif apabila pelajar lelaki menerima 3.77 (s.p= 0.03) dan pelajar perempuan pula ialah 3.84(s.p = 0.02) (sila rujuk Jadual 6 di Lampiran A).

Data Jadual 5 juga menunjukkan bahawatiada perbezaan yang signifikan antarapencapaian tingkah laku kompetensi, kognitif,afektif pelajar berdasarkan latar belakangpekerjaan penjaga mereka. Ini jelas apabila nilaiF (4,401) =1.42, p>0.05 bagi tingkah lakukompetensi. Jadual 6 di Lampiran A menunjukkanmin pencapaian tingkah laku kompetensi bagipelajar yang mempunyai penjaga bekerja dengankerajaan ialah 10.65 (s.p =0.27), swasta = 11.05(s.p =0.39), peniaga = 9,.96 (s.p =0.39), petani =10.93 (s.p =0.59) dan tidak bekerja =11.69 (s.p=0.88).

Bagi pencapaian tingkah laku kognitif, Jadual5 juga menunjukkan tiada terdapat perbezaanyang signifikan antara pencapaian pelajar



berdasarkan latar belakang pekerjaan penjagamereka dengan nilai F(4,401) = 0.36, p>0.05.Penerangan secara terperinci ditunjukkan padaJadual 5 (Lampiran A) iaitu min pencapaiantingkah laku kognitif pelajar yang mempunyaipenjaga bekerja dengan kerajaan ialah 14.77(s.p =0.30), swasta =15.21 (s.p =0.44), peniaga =14.97 (s.p -0.44), petani = 14.92 (s.p =0.67) dantidak bekerja =15.82 (s.p =0.99).

Seterusnya pencapaian tingkah laku afektifpelajar juga tidak menunjukkan perbezaan yangsignifikan berdasarkan latar belakang pekerjaanpenjaga. Nilai F (4,401) = 0.36, p >0.05. Secaraterperinci, min pencapaian tingkah laku afektifpelajar yang mempunyai penjaga bekerja dengankerajaan ialah 3.81 (s.p =0.02), swasta =3.84 (s.p=0.03), peniaga = 3.81 (s.p =0.04) dan tidakbekerja = 3.77 (s.p =0.07).

Sehubungan itu Jadual 4 juga menunjukkantidak terdapat kesan interaksi yang signifikanantara jenis program dan jantina pelajar denganpencapaian tingkah laku kompetensi, kognitifdan afektif. Inijelas apabila nilai F(4,401)= 1.29,p>0.05 bagi tingkah laku kompetensi. Secaraterperinci, min tingkah laku kompetensi pelajarlelaki PUM ialah 10.61 (s.p =0.39) dan pelajarlelaki PTB pula ialah 10.70 (s.p =0.64).Sementara, min tingkah laku kompetensi pelajarperempuan PUM ialah 10.46 (s.p =0.29) danpelajar perempuan PTB pula ialah 11.65 (s.p=0.56) (sila rujuk jadual 7 di Lampiran B).

Nilai F pencapaian tingkah laku kognitifpula ialah F(4,401) =0.00, p>0.05. Secaraterperinci, Jadual 7 di Lampiran B menunjukkanmin pencapaian tingkah laku kognitif pelajarlelaki PUM ialah 16.40 (s.p =0.44) dan pelajarlelaki PTB pula ialah 14.21 (s.p =0.73). Sementaramin tingkah laku kognitif pelajar perempuanPUM ialah 16.03 (s.p = 0.33) dan pelajarperempuan PTB ialah 13.92 (s.p =0.64).

Begitu juga dengan pencapaian tingkah lakuafektif yang menunjukkan tiada perbezaan yangsignifikan antara pencapaian tingkah laku afektifpelajar PUM dan pelajar PTB dengan nilaiF(4,401) = 0.00, p>0.05. Secara terperinci, Jadual7 menunjukkan min tingkah laku afektif pelajarlelaki PUM ialah 3.79 (s.p =0.03) dan pelajarlelaki PTB ialah 3.75 (s.p =0.05). Manakala, mintingkah laku afektif pelajar perempuan PUMialah 3.86 (s.p =0.02) dan pelajar perempuanPTB ialah 3.82 (s.p =0.04) (sila rujuk LampiranB).

Seterusnya, Jadual 5 juga menunjukkanbahawa tiada terdapat perbezaan yang signifikandalam pencapaian tingkah laku kompetensi,kognitif, afektif antara pelajar PUM dan PTByang berlainan latar belakang pekerjaan penjaga.Ini jelas apabila nilai F yang ditunjukkan adalahtidak signifikan iaitu F(4,401) =1.51, p>0.05 bagipencapaian tingkah laku kompetensi. Jadual 7(Lampiran B) menunjukkan min tingkah lakukompetensi pelajar PUM yang mempunyaipenjaga bekerja kerajaan ialah 10.62 (s.p = 030),swasta =10.99 (s.p = 0.44), peniaga = 10.51 (s.p=0.43), petani • 10.36 (s.p =0.49) dan tidakbekerja = 10.13 (s.p =0.87). Manakala, mintingkah laku kompetensi pelajar PTB yangmempunyai penjaga bekerja dengan kerajaanialah 10.62 (s.p =0.44), swasta =11.10 (s.p =0.65),peniaga = 9.41 (s.p =0.66), petani = 11.50 (s.p=1.08) dan tidak bekerja = 13.25 (s.p =1.53).

Begitu juga dengan pencapaian tingkah lakukognitif apabila data menunjukkan tiadaperbezaan antara pelajar PUM dan pelajar PTByang mempunyai latar belakang penjaga yangberbeza. Nilai F yang diterima ialah F (4,401)=0.56, p>0.05. Maklumat jelas dapat dilihat padaJadual 7 iaitu min tingkah laku kognitif pelajarPUM yang mempunyai penjaga bekerja kerajaanialah 15.80 (s.p =0.34), swasta = 16.53 (s.p =0.49),peniaga =16.19 (s.p =0.49), petani =16.63 (s.p=0.55) dan tidak bekerja =15.90 (s.p =0.99).Manakala, min tingkah laku kognitif pelajar PTByang mempunyai penjaga bekerja kerajaan pulaialah 13.74 (s.p = 0.49), swasta = 13.88 (s.p=0.73), peniaga =13.76 (s.p =0.74), petani =13.17 (s.p =1.13) dan tidak bekerja = 15.75 (s.p=1.73) (sila rujuk Lampiran B).

Perbandingan antara pencapaian tingkahlaku afektif antara pelajar PUM dan pelajar PTByang mempunyai latar belakang pekerjaanpenjaga berbeza juga menunjukkan dapatan yangtidak berbeza secara signifikan. Nilai F yangditerima ialah F(4,401) =0.51, p>0.05. Secaraterperinci, data di Jadual 7 di Lampiran Bmenunjukkan bahawa min tingkah laku afektifpelajar PUM yang mempunyai penjaga bekerjakerajaan ialah 3.82 (s.p =0.02), swasta =3.83 (s.p=0.03), peniaga = 3.82 (s.p =0.03), petani =3.81(s.p =0.4) dan tidak bekerja = 3.85 (s.p =0.07).Manakala, min tingkah laku afektif pelajar PTByang mempunyai penjaga bekerja kerajaan ialah3.79 (s.p =0.03), swasta = 3.84 (s.p =0.05), peniaga= 3.80 (s.p = 0.05), petani = 3.82 (s.p = 0.08) dantidak bekerja =3.67 (s.p =0.11).



PERBINCANGAN DAN KESIMPULAN

Secara amnya, dapatan pengkaji melalui analisisujian MANOVA menunjukkan bahawa tiadaterdapat perbezaan yang signifikan dalampencapaian tingkah laku kognitif, afektif dankompetensi pelajar berdasarkan jantina dan latarbelakang pekerjaan penjaga (sila rujukjadual 4,5, 6 dan 7). Ini bermakna skor pencapaiantingkah laku kognitif, kompetensi dan afektifpelajar adalah sama atau hampir sama tanpamengira mereka pelajar lelaki atau pelajarperempuan; pelajar yang mempunyai latarbelakang penjaga peniaga atau pun tidak. Justeru,dapatan pengkaji ini selari dengan dapatanpengkaji-pengkaji terdahulu seperti Hatten(1993), Mohd Amir Sharifuddin Hashim et al.(1994) dan Sharifah Kamaliah Syed Sofian(1996).

Hatten (1993) dalam kajiannya terhadap220 pelajar "Small Busines Industries" dengankaedah kuasi-experimen mendapati bahawa tiadaperbezaan yang signifikan antara tingkah lakuafektif pelajar lelaki dan pelajar perempuan (nilaiPillai's Trace = 0.02; nilai F(4, 145) =0.78,p>0.05); dan antara pelajar yang mempunyailatar belakang usahawan atau pun tidak (nilai F=0.79, p>0.05). Begitujuga dengan dapatan kajiansecara tinjauan oleh Mohd. Amir SharifuddinHashim et al. (1994) terhadap 913 pelajar PUMapabila analisis datanya menunjukkan tiadaperbezaan yang signifikan dalam pencapaianpelajar berdasarkan jantina.

Namun, kajian oleh Sharifah Kamaliah SyedSofian (1996) terhadap 390 pelajar pulamenunjukkan terdapat perbezaan yang signifikanantara ciri-ciri keusahawanan (tingkah lakuafektif) pelajar lelaki dan pelajar perempuan(ujian-t = -2.49, p<0.05) tetapi kajian beliau jugamenunjukkan bahawa tidak terdapat perbezaanyang signifikan antara pelajar yang mempunyailatar belakang pekerjaan penjaga peniaga ataupun tidak (ujian t =-0.59, p > 0.05).

Seterusnya, hasil kajian pengkaji didapatitidak selari dengan hasil beberapa kajianterdahulu seperti kajian Salleh (1994), Flemming(1996) dan Zaidatol Akmaliah Lope Pihie et al.(1998). Contohnya, kajian Salleh (1994) terhadap25 ahli sukan dan 25 usahawan dengan kaedahretrospektif menunjukkan bahawa latar belakangkeluarga mempunyai pengaruh terhadappencapaian anak-anak. Begitujuga dengan kajianFlemming (1996) terhadap 419 peserta program

keusahawanan. Hal yang demikian juga diperolehdalam kajian Zaidatol Akmaliah Lope Pihie et al.(1998) apabila kajian beliau terhadap 1336pelajar menunjukkan terdapat perbezaan yangsignifikan antara pelajar lelaki dan pelajarperempuan (ujian-t = 5.09, p<0.05).

Sebagai kesimpulannya, kajian ini menun-jukkan bahawa tidak terdapat perbezaan yangsignifikan antara pelajar lelaki dan pelajarperempuan yang berlainan latar belakangkeluarga sama ada dari segi pencapaian tingkahlaku kognitif, afektif dan kompetensikeusahawanannya.

RUJUKAN

BANNOCK, G. d a n j . STANWORTH. 1990. The Making of

Entrepreneurs. London: Small Business ResearchTrust.

BL<X)M, B. S. 1956. Taxonomy of Education Objectives:Handbook I Cognitive Domain. London: LongmanGroup Ltd.

COHEN, L. dan L. MANION. 1994. Research Methods in

Education. 4th ed. New York: Routledge.

FINK, A. dan J. KASECOFF. 1985. How to Conduct

Survey. A Step by Step Guide. London: SAGEPublication.

FLEMING, P. 1996. Entrepreneurship education inIreland: a longitudinal study. Academy ofEntrepreneurhip Journal 2(1): 95-119.

HATTEN, T. 1993. Student attitudes towardentrepreneurship as affected by participationin SBI program. Disertasi Ph.D. University ofMissouri-Columbia.

MANN, P. H. 1990. Nontraditional business educationfor black entrepreneurs: observations from asucessful program. Journal of Small BusinessManagement (April); 30-36.

METCALF, R. D. 1985. Producing winners: invariantcharacteristics of talented coaches. DisertasiPh.D. United States International University,San Diego.

MOHD. AMIR SHARIFUDDIN HASHIM, BARJOYAI BARDAI,

ROGAYAH MAT ZAIN dan ZULKIFLI SENTERI. 1994.

Effectiveness of the Young EntrepreneurshipTraining Programme (YEP): A Malaysian Story.Kertas kerja prosiding dibentangkan di ENDECWorld Conference on Entrepreneur. 7-9 Julai.Singapore: Nanyang Institute of Technology.



REAVES, C. C. 1992. Quantitative Research for theBehavioral Sciences, New York: John Wiley danSon, Inc.

RKXROAD, E. F. 1985. Influential factors the musicaldevelopment of outstanding professionalsinger. Disertasi Ph.D. University of IllinoisUrbana -Campaign.

ROBIAH SIDIN. 1990. Pendidikan Bermutu MasyarakatSejahtera. Suara Pendidik 13-14 (3&4): 21-27.

SHARIFAH KAMALIAH SYED SOFIAN. 1996. The

identification of entrepreneurial characteristicsamong secondary school students in the districtof Hulu Langat, Sel. D.E. Disertasi SarjanaPendidikan. Fakulti Pengajian Pendidikan,Universiti Putra Malaysia.

SALLEH HASSAN. 1994. Peranan persekitaranterhadap perkembangan individu ke tahapkecemerlangan: satu kajian menggunakankaedah retrospektif. Tesis Ph.D. FakultiPendidikan, Universiti Kebangsaan Malaysia

TABACHNICK, B. G. dan L. S. FIDELL. 1996. Using

Multivariate Statistic. New York: Harper andRow.

WEE LIAN TAN, LAI KUAN SIEW, WEI HONG dan SIEW

CHING WONG. 1994. Entrepreneurial spiritamong tertiary students in Singapore. Dalam

Proceeding ENDEC on Entrepreneurship. Singapore:Nanyang Technological University.

ZAIDATOL AKMALIAH LOPE PIHIE. 1992. The

importance of business managementcompetencies in preparing students for smallbusiness ownership. Disertasi Ph.D. JabatanPendidikan Vokasional, Universiti SouthernIllinois, Carbondale, USA.

ZAIDATOL AKMALIAH LOPE PIHIE dan HABIBAH ELIAS.

1997. Keusahawanan & Motivasi Diri. Serdang:Penerbit Universiti Putra Malaysia.

ZAIDATOL AKMALIAH LOPE PIHIE, MOHD MAJID KONTING,

AB. RAHIM BAKAR dan GENEVIEVE KIANG ANGKING.

1998. Dasar dan pelaksanaan pendidikankeusahawanan di sekolah menengah (Kertas1). Seminar Pendidikan Keusahawanan Abad 2117 Dis, anjuran Pusat Penyelidikan DasarPendidikan, Fakulti Pengajian Pendidikan,Universiti Putra Malaysia. Kajang, Selangor:WRC Country Villas.

1999. Laporan Tahunan 1999.Kementerian Pembangunan Usahawan.

. 1999. Laporan Tahunan 1999. InstitutPembangunan Pengurusan Johor.

(Diterima: 14 Ogps 2002)



LAMPIRAN A

JADUAL 6Skor min dan sisihan piawai setiap pembolehubah bersandar berdasarkan

program, jantina dan latar belakang pekeijaan penjaga

Pemboleh ubah bersandar Pemboleh ubah tak bersandar s.p

Kompetensi

Kognitif

Afektif

ProgramPUMPTBJantinaLelakiPerempuanPekerjaan penjagaKerajaanSwastaPeniagaPetaniTidak bekerja



10.5411.18

10.6511.06

10.6511.059.96

10.9311.68

16.2214.06

15.0314.97

14.7715.2114.9714.9115.83

3.833.78

3.773.84

3.813.843.813.813.76

0.240.43

0.380.32

0.270.390.390.600.88

0.270.48

0.030.02

0.290.440.440.670.99

0.020.03

0.030.02

0.020.030.030.040.07



LAMPIRAN B

JADUAL 7Skor min dan sisihan piawai setiap pemboleh ubah bersandar berdasarkan

jantina dan latar belakang pekerjaan penjaga bagi setiap program

Pemboleh ubah bersandar Pemboleh ubah tak bersandar s.p

Kompetensi

Kognitif

Afektif

Kompetensi

Kognitif

Afektif

PUM

PTB

PUM

PTB

PUM

PTB

PUM

PTB

PUM

PTB

PUM

PTB

LelakiPerempuanLelakiPerempuanLelakiPerempuanLelakiPerempuanLelakiPerempuanLelakiPerempuanKerajaanSwastaPeniagaPetaniTidak bekerjaKerajaanSwastaPeniagaPetaniTidak bekerjaKerajaanSwastaPeniagaPetaniTidak bekerjaKerajaanSwastaPeniagaPetaniTidak bekerjaKerajaanSwastaPeniagaPetaniTidak bekerjaKerajaanSwastaPeniagaPetaniTidak bekerja

10.6110.4610.7011.6616.4016.0314.2113.923.793.863.753.82

10.6810.9910.5110.3610.1310.6211.109.41

11.5013.2515.8016.5316.1916.6615.9013.7513.8813.7613.1715.753.823.833.823.813.853.793.843.803.823.67

0.390.290.640.560.440.330.730.640.030.020.050.040.300.440.430.490.870.4350.650.661.081.530.340.490.490.550.990.490.730.741.231.730.020.030.030.040.070.030.050.050.800.11



Status Program Pembelajaran di Kalangan Saudara Baru:Satu Kajian Kes di Negeri Melaka

MOHD AZMI MAT SAH1 & MAIMUNAH ISMAIL2

!Institut Al-Quran Melaka34 A, Taman Cempaka 1,

Peringgit, Melaka2Jabatan Pemajuan Profesional dan Pendidikan Lanjutan

Fakulti Pengajian Pendidikan43400 UPM, Serdang, Selangvr, Malaysia

Kata kunci: Saudara baru, pendidikan dewasa, program pembelajaran, Balai Islam

ABSTRAKKajian ini bertujuan mengenal pasti tahap persepsi responden terhadap status programpembelajaran yang mereka ikuti. Kajian melibatkan sejumlah 60 orang saudara baru dan tigaorang pegawai di sebuah di institusi dakwah Islam. Hasil kajian menunjukkan kebanyakanresponden berbangsa Cina dan beragama asal Buddha, purata umur memeluk Islam ialah 25.8tahun dan purata umur sekarang ialah 45.2 tahun. Sejumlah 76% responden adalah wanita.Kajian juga menunjukkan responden berpersepsi bahawa program pembelajaran secara keseluruhanadalah memuaskan. Aspek yang perlu diberi lebih perhatian ialah keselesaan kelas, kemampuanpengajar menggunakan pelbagai bahasa, dan beberapa aspek isi kandungan pelajaran. Tigamasalah pelaksanaan program pembelajaran yang dihadapi oleh Balai Islam ialah anggapanbahawa Balai Islam sebagai tempat mengadu masalah, status pekerjaan pegawai dan kurikulumyang kurang lengkap.

ABSTRACT

The study aimed to identify the perception of respondents on the status of learning program thatthey have undergone. The study involved 60 Muslim converts and three officers of an Islamicinstitution. Results showed that the majority of respondents were of Chinese with Buddhism asthe original religion, converted to Islam at the average age of 25.8 years, and their present agewas at an average of 45.2 years. A total of 76% of respondents were women. As a whole therespondents perceived that the learning program was satisfactory. However, some areas need tobe looked into seriously such as the situations in the class, the capability of teachers in usingmultiple languages in teaching, and several aspects of learning contents. Three problems relatedto learning program for the converts were identified, namely, the perception of respondents thatBalai Islam is the only place to refer to when problems arise, employment status of officers andthe inadequacy of curriculum.

PENGENALAN

Islam adalah suatu agama yang dinamik. Keadaandinamik ini antara lain dapat dilihat melaluipertambahan umat Islam bukan sahaja merekayang lahir daripada keluarga Islam tetapi jugayang baru memeluk Islam atau 'convert' ataujuga dikenali sebagai 'saudara baru'. Fenomenabertukar agama daripada agama lain ke agamaIslam bukan satu perkara baru. la telah bermula

di peringkat awal tamadun Islam di dunia Arab(Shatzmiller 1996) dan di negara-negara AsiaTenggara (Hefner and Horvatich 1997). Hinggakini fenomena ini berlaku di kebanyakan negaradi dunia termasuk Malaysia, dan ini merupakansatu cara menyebabkan berlaku peningkatanjumlah umat Islam di sesebuah negara.Contohnya di negeri Jepun sekarang terdapathampir 50,000 orang penduduk yang memeluk

Mohd Azmi Mat Sah 8c Maimunah Ismail

Islam daripada agama lain dalam tempoh 20tahun yang lalu (Anis 1998). Di Kanada terdapatsejumlah 200,000 orang Islam termasuk merekasebagai imigran lama dan baru yang majoritinyadari Asia dan Afrika dan juga yang memelukIslam daripada agama lain (Azmi 1997).

Kajian pertambahan saudara baru dalamera Malaysia moden adalah kecil, dan analisismenunjukkan ia seiringan dengan gerakandakwah di negara ini (Shamsul 1997). Jumlahsaudara baru sebenar di negara ini sukardiperolehi. Berdasarkan sumber-sumber yangterhad, jumlah mereka di Kuala Lumpur dalamlima tahun antara tahun 1995 hingga 2000 secarapurata ialah lebih kurang 400 orang setahun(Temu bual dengan pegawai PERKIM, KualaLumpur 2001). Begitu juga menurut Mahfuz(1992) jumlah saudara baru di Kuala Lumpurdaripada tahun 1986 hingga 1990 ialah seramai1609 orang atau 0.15% daripada keseluruhanmasyarakat bukan Islamnya.

Melihat perkembangan ini dan pertambahanpopulasi yang ingin memeluk Islam di Malaysiamenyebabkan perlunya satu tugas khusus untukmenjaga hal-ehwal kebajikan termasuk programpembelajaran untuk meningkatkan pemahamandan penghayatan Islam (Siddiq 1998). Institusidakwah di Malaysia seperti YADIM, PERKIM,Balai Islam, MACMA, IOA, dan JIM1 telahbanyak membantu misi dakwah Islamiah yangsedia ada termasuk pembelajaran di kalangansaudara baru.

Balai Islam terdapat hampir di setiap negeridi Malaysia. Balai Islam Negeri Melaka khususnyatelah ditubuhkan pada tahun 1987, dimandatkanuntuk mengendalikan aktiviti pembelajaran dikalangan saudara baru. Setelah sekian lamadijalankan masih banyak tidak diketahui tentangkeberkesanan program pembelajaran tersebutdaripada pelbagai aspek. Oleh yang demikianfokus kajian ini ialah untuk melihat statusprogram pembelajaran di kalangan saudara barukhususnya anjuran Balai Islam. Tambahan pulakajian lepas mengenai pembelajaran di kalangansaudara baru adalah terhad. Kajian yang adahanyalah mengenai permasalahan yang merekahadapi (Simon Peri 1990, Nor Patimah 1990;

Maziah 1995; Mahfuz 1992; Wan Fauziah 1992;Yusoff 1988). Persoalan kajian ialahbagaimanakah pandangan saudara baru tentangpelaksanaan program pembelajaran daripadaaspek kepentingan objektif program, isikandungan pelajaran, suasana pembelajaran,penyampaian dan pengendalian program?Apakah masalah yang dihadapi oleh pihakpelaksana dalam mengendalikan aktivitipembelajaran? Kajian ini akan cuba mencarijawapan kepada persoalan di atas.

Hasil kajian bukan sahaja dapatmeningkatkan korpus pengetahuan mengenaipembelajaran di kalangan saudara baru, tetapiia boleh digunakan oleh Balai Islam dan institusidakwah lain dalam pelaksanaan programnya.Seterusnya hasil kajian diharapkan dapatmembantu usaha untuk mengenai pasti dikalangan saudara baru yang berkebolehan untukdiketengahkan dalam membantu usahapelaksanaan program pembelajaran dan sebagaipendakwah. Penumpuan sesuatu aktivitipembelajaran keislaman yang disusuli denganaktiviti penyelidikan akan cuba menonjolkankepentingan fungsi Balai Islam Melaka sejajardengan falsafah penubuhannya untuk memberikebajikan kepada 'saudara baru' denganmengoperasikan konsep pendidikan.

PENDIDIKAN DEWASA DARI

PERSPEKTIF ISLAM

Pendidikan amat digalakkan dalam Islam tanpamengira sama ada ilmu agama dan ilmu sains.Menurut Mohd Kamal (1988), isi kandunganteologi dan sains dalam Islam tidak bercanggahantara satu sama lain, malah ia saling melengkapidan kedua-duanya lahir daripada pandanganyang satu iaitu Tauhid. Ini amat bertentangandengan konsep dualisrne yang diamalkan diBarat, di mana ilmu keagamaan dipisahkandaripada ilmu sains. Pendidikan tidak formalyang berkait rapat dengan pendidikan dewasamempunyai kepentingan tinggi dalam Islamkerana tempoh seseorang individu mengikutipendidikan formal adalah terbatas.

YADIMPERKIMMACMAIOAJIM

Yayasan Dakwah Islam MalaysiaPertubuhan Kebajikan Islam MalaysiaMuslim Chinese Association of MalaysiaInternational Outreach of ABIM (Malaysian Muslim Youth Movement)Jemaah Islam Malaysia


Status Program Pembelajaran di Kalangan Saudara Baru

Menurut Al-Rawi (1993) beberapa ciripendidikan dewasa menurut Islam ialah:Pertama, pendidikan dewasa merupakan satuproses pembelajaran sepanjang hayat iaitu dari"buaian hingga ke liang lahad". Hanya yangmembataskan pendidikan seseorang ialahkebolehannya untuk belajar kerana individu yangberlainan mempunyai kemampuan yang berbezauntuk belajar. Kedua, pembelajaran yangberulang-ulang merupakan amalan umat Islamyang terdahulu. Ini kerana di awal tamadunIslam, sistem pendidikan formal tidak begitukemas seperti masa kini, yang mana individusering belajar dan bekerja secara tukar gantimengikut kesesuaian masa. Ini kerana dalampembelajaran terdapat kata-kata hikmat seperti"Seseorang tidak sempurna amalnya jika ia tidakbelajar, dan tidak menjadi orang yang terdidikjika ia tidak melakukan sesuatu mengikut apayang dipelajari."

Ketiga, ialah konsep masyarakat berpelajaran(learning society) merupakan satu tuntutandalam Islam. Walaupun konsep ini seringdilaung-laungkan dewasa ini, tetapi mengikutsejarah Islam, dalam era pemerintahan Abbasiahseluruh masyarakat Arab ketika itu telahmengalami transformasi pendidikan iaitumasyarakat tersebut dianggap sebagai satuinstitusi pembelajaran yang besar. Bidang-bidangpendidikan yang telah bertapak ketika itu ialahundang-undang Islam, kenegaraan dan politik.Ulasan di atas menunjukkan bahawa Islam sangatmementingkan umatnya menuntut ilmu bagimenjamin kebahagiaan hidup dunia dan akhirat.Manusia keseluruhannya, termasuk mereka yangbaru memeluk Islam ditugaskan untuk menjadikhalifah atau pengatur kepada alam semesta ini.Oleh itu perkara utama yang mereka mestilaksanakan ialah menuntut ilmu mengenai agamayang baru dianuti. Ini mencadangkan bahawasuatu program pembelajaran khususnya secaratidak formal dibentuk bagi memudahkan merekamenjalani tuntutan hakiki tersebut.

Menyentuh tentang teori pembelajaran,banyak pendapat menyatakan mengapaseseorang dewasa belajar. Seseorang dewasadikatakan bersedia untuk belajar apabila merekaberhadapan dengan situasi yang rumit, yangmenuntut agar mereka belajar bagi memperbaikikualiti hasil kerja atau peringkat kehidupanseharian. Ini termasuk individu sama adaseorang pekerja, suami atau isteri, ibu atau bapa,seorang ketua sesebuah organisasi atau pekerja

dalam organisasi (Knowles 1980; Brazziel 1989;Garelli 1996). Pelajar dewasa lebih sukapembelajaran yang berkaitan dengan pengalamanhidupnya dan ia akan menjadi lebih bermaknaapabila pembelajaran itu boleh diaplikasikandalam menyelesaikan sebarang masalah harianatau masalah-masalah di tempat kerja (Reizen1996; Benshoff 1991).

Dari pandangan Knowles (1984) pula iamengatakan bahawa pada suatu peringkatkehidupan seseorang dewasa, orientasi pembe-lajaran lebih tertumpu kepada keperluan diri,sama ada ia berorientasikan masalah, pekerjaanataupun kehidupan. Sekiranya berkemampuan,ia mahu mengaplikasikan apa sahaja yang telahdipelajarinya secepat mungkin.

Aslanian dan Brickell (1980) seterusnyamenambah bahawa faktor penyebab seseoranguntuk belajar ialah akibat perubahan dalamhidup keluarga seperti perkahwinan, kelahiran,perceraian dan kematian serta faktor-faktor lainseperti penggunaan masa lapang dan mahumencapai kepuasan tugas yang lebih tinggi.Manakala Robinson (1985) pula lebihcenderung kepada idea bahawa pembelajarandewasa berlaku kerana ia adalah suatukeperluan penting pada suatu peringkat dalamkehidupan seseorang.

Dalam konteks kajian ini saudara baru sangatmemerlukan pendidikan. Sebagai anggota barudalam masyarakat Muslim sudah tentu merekamempunyai pelbagai masalah yang perlu diatasi(Ibrahim 1995; Zainurin 1992). Antaranya ialahuntuk mematuhi amalan agama yang barudianuti dan untuk menyesuaikan diri denganumat Islam yang lain, reaksi rakan, majikan dankeluarga. Masalah lain yang berkaitan ialahkerumitan untuk belajar kerana tempat tinggalyangjauh dari tempat belajar, dan jenis pekerjaanyang kurang sesuai setelah memeluk Islam(Ibrahim 1995; Ramli 1993). Justeru ituperancang program pembelajaran kepadasaudara baru haruslah dirancang secarasistematik dengan melihat kepada aspek-aspekpendidikan dewasa.

Seperti yang dilaporkan oleh Mahfuz (1992)sungguhpun mereka dengan sepenuh hatimenerima Islam sebagai satu cara hidup, tetapimereka masih lagi tidak memahami apakahperkara yang tergolong dalam ibadah. Dengandemikian pembelajaran perlu bukan sahaja untukmeningkatkan tahap kognitif tentang Islam tetapijuga amalan yang dituntut. Mereka sedang


Mohd Azmi Mat Sah & Maimunah Ismail

membina persepsi diri mengenai nilai,kepercayaan serta amalan hidup yang belumpernah mereka alami sebelum ini. Dengandemikian proses pembelajaran untuk saudarabaru sangat penting dan perlu dirancang sebaik-baiknya.

Di antara konsep yang selalu disebut dalampelaksanaan sesuatu program pembelajaran ialahpengetahuan pelaksana tentang ciri-ciripembelajaran dewasa, faktor yang menggalakkanpembelajaran dewasa dan penggunaanpengalaman dalam pembelajaran dewasa. KuMd. Ali (1997) melaporkan bahawa ahli psikologiberpendapat bimbingan adalah sebahagiandaripada komponen dalam program pendidikandewasa. Perkhidmatan bimbingan merupakannadi terpenting dalam mempastikan saudara baruuntuk terus kekal di atas dasar Tauhid,menghayati tuntutan agama dan memandu untukmenjalani kehidupan ke jalan yang diredhai sertadibenarkan oleh syariat.

Dalam konteks penghidupan saudara baru,selain pembimbing, 'role model' adalah jugapenting. Mereka sangat memerlukan seseorangyang boleh menjadi contoh seperti fasilitatorkelas agama, ustaz, imam masjid, pegawaiorganisasi dan pemimpin tempatan lain yangberagama Islam serta jiran dan rakan. Inibertepatan dengan teori "Pembelajaran Sosial"(Bandura 1977) yang mana seseorang individubelajar melalui pemerhatian dan interaksidengan anggota sosial lain dalam aktiviti seharian.Oleh itu saudara baru perlu didedahkan denganpengetahuan dan amalan yang betul mengenaiIslam. Ini mencadangkan betapa pentingnyadiwujudkan program pembelajaran khusus untukmereka.

KAJIAN LEPAS YANG BERKAITAN

Kajian-kajian lepas mendapati bahawa masihbanyak ruang yang boleh dipenuhi oleh pelbagaipihak untuk memantapkan program pembelajarandi kalangan saudara baru. Mahfuz (1992)mencadangkan supaya sukatan pelajaranhendaklah bukan sekadar peringkat asas sahaja,tetapi perlu lebih mendalam. Selanjutnya beliaumencadangkan agar dilakukan pengasingan kelasantara mereka yang lama dan yang barumemeluk Islam. Menurut Wan Fauziah (1992)pula hampir 90% daripada saudara baru diMalaysia terdiri daripada golongan yangberpendapatan rendah dan tidak berpendidikantinggi; dan dengan demikian penganjur program

pembelajaran perlu sensitif dengan keadaanprofil sosial mereka yang demikian. Cadanganyang dikemukakan oleh Nor Patimah (1990)amatlah dipersetujui supaya diwujudkanperpustakaan untuk saudara baru, adakan kelaslanjutan dan wujudkan "Islamic InformationCentre" di tengah-tengah sesebuah bandar besarseperti Kuala Lumpur, Johor Bahru dan Melaka.Begitu juga dengan cadangan supaya prosespembelajaran menggunakan alat bantu mengajarseperti audio-video, kursus secara jarak jauh danmengadakan penilaian yang sistematik tentangaktiviti pembelajaran yang diadakan di kalangansaudara baru.

Daripada segi teknik penyampaian olehfasilitator, Maziah (1995) mencadangkan bahawaprogram dakwah perlu dimulakan denganperkara-perkara yang menjadi kegemaran merekadahulu, contohnya kemasyarakatan ataupergaulan sosial kemudian sedikit demi sedikitdikaitkan dengan agama. Fasilitator juga perlumenghalusi percakapan mereka kerana dengandemikian perkara yang dipelajari mudahmeresap ke dalam jiwa seseorang. Fasilitator perlusensitif terhadap sasaran yang dituju. Sebagaicontoh, mereka boleh memulakan sesipembelajaran dengan mengajak memikirkantentang kejadian alam, kehebatan pencipta alamini dan sebagainya. Kajian tersebut jugamencadangkan supaya fasilitator perlu menguasaibeberapa bahasa lain seperti bahasa Inggeris,Cina, Tamil dan bahasa lain selain daripadaBahasa Melayu. Ini kerana saudara baru datangdaripada pelbagai latar belakang etnik danbudaya.

Ulasan di atas menunjukkan bahawaprogram pembelajaran di kalangan saudara barumerupakan satu pembelajaran dewasa secaratidak formal,yang mempunyai kurikulumberdasarkan masalah kehidupan seharian.Objektif dan strategi pengendalian pembelajaranperlu dirancang dengan rapi, bersesuaian denganprofil sosial saudara baru yang mempunyaipelbagai masalah termasuk ekonomi, dan sedangberada pada tahap transisi daripada segipengetahuan dan amalan agama, sertapembelajaran perlu menggunakan prinsip-prinsippendidikan dewasa.

METODOLOGI KAJIAN

Kajian ini merupakan satu kajian penerokaanyang berbentuk deskriptif. la dinamakanpenerokaan sebab kajian tempatan di kalangan



saudara baru sangat terhad dan lebih-lebih lagiberkaitan program pembelajaran yang merekaikuti hampir tiada ditemui sebelum ini. Kajianini bertujuan meninjau pandangan saudara baruterhadap pelaksanaan program pembelajaranyang telah mereka ikuti daripada aspekkepentingan objektif pembelajaran, suasanapembelajaran, isi kandungan pelajaran,penyampaian dan pengendalian programpembelajaran. Kajian juga bertujuan mengenal-pasti masalah yang dihadapi dalam pelaksanaanprogram pembelajaran di kalangan saudara barudaripada perspektif penganjur. Aspek pelaksanaanini perlu diketahui kerana ia mempengaruhitumpuan dan kelancaran program pembelajaranyang dijalankan oleh pegawai Balai Islam.

Instrumentasi Kajian

Instrumen kajian ialah borang soal selidik yangdiisi sendiri oleh responden. Pembentukansoalselidik ini berdasarkan teori-teori pembe-lajaran dewasa terkemuka yang dibentuk olehKnowles (980), Brazziel (1989) dan Garelli(1996). Sebanyak empat komponen programpembelajaran yang dipilih dalam kajian ini iaitukepentingan objektif pembelajaran, suasanapembelajaran, isi kandungan pelajaran,penyampaian dan pengendalian programpembelajaran.

Responden kajian terdiri daripada semua60 orang saudara baru yang telah mengikutiprogram pembelajaran yang dianjurkan olehBalai Islam dalam tahun 2001. Mereka terdiridaripada saudara baru yang berumur antara 18hingga 60 tahun. Kategori umur ini dipilihkerana sesuai dengan hak memilih agama bagiindividu seperti yang tercatat dalam perlem-bagaan Persekutuan perkara 11 (4). Pemilihanresponden dibuat berdasarkan senarai nama yangtelah diambil oleh penyelidik melalui semakanpelajar yang telah mengikuti programpembelajaran anjuran Balai Islam Melaka dalamtahun 2001.

Prauji telah dijalankan di kalangan 10 orangsaudara baru lain yang pernah mengikutiprogram pembelajaran di Melaka yangdikendalikan oleh institusi Islamiah yang lain.Analisis reliabiliti dijalankan dan nilai Cronbachalpha yang diperoleh semasa pra-uji ialah 0.82.Dalam Kajian sebenar nilai Cronbach alpha ialah0.78.

Pengumpulan data kajian telah dijalankandengan mengedarkan sendiri borang soal selidik

melalui individu, sewaktu selesai kelas dijalankandisepanjang bulan Oktober 2001. Semua borangsoal selidik telah dapat dikumpulkan denganbantuan pegawai di Balai Islam dan seterusnyadianalisis. Data tambahan telah diperolehidengan menemubual tiga orang pegawai BalaiIslam untuk memahami masalah yang dihadapisemasa pelaksanaan program pembelajaran.Mereka yang dipilih merupakan pegawai utamaBalai Islam yang menjadi perancang, pelaksanadan pengendali program pembelajaran tersebut.

Kajian status ini menggunakan statistikmudah seperti peratusan, kekerapan dan minuntuk menerangkan profil dan membuatinterpretasi responden terhadap aspek-aspekyang dikaji. Pengukuran item yang menggunakanmin adalah berasaskan ukuran Likert berskala -5 dan interpretasi tentang tahap min adalahberasaskan tiga ketegori iaitu > 3.56 = tinggi,1.33 hingga 3.66 = sederhana, dan < 1.32 =rendah.

HASIL KAJIAN DAN PERBINCANGANPurata umur responden ialah 45.2 tahun, 76.7%terdiri daripada wanita, 75% berbangsa Cinadan 70% berasal daripada agama Buddha.Daripada segi kelayakan akademik pula, 60%adalah hanya berpendidikan sehingga darjahenam dan sebanyak 11.7% memiliki ijazahpertama. Mereka memeluk agama Islam padapurata umur 25.8 tahun dan ini bermakna secarapurata responden telah menganuti Islam selamahampir 20 tahun. Manakala 41.7% di kalanganmereka mempunyai pekerjaan di sektor awamatau swasta, dan 60% telah pun berkahwin.Profil demografi ini ditunjukkan dalam Jadual1.

Bilangan kaum wanita di kalanganresponden jauh melebihi bilangan lelaki. Inidisebabkan oleh beberapa faktor. Pertama, datamenunjukkan jumlah sebenarnya saudara baruwanita di Malaysia jauh melebihi lelaki iaitudengan kadar 70% : 30% (Rosey 1995). Kedua,sebanyak 27.0% daripada responden merupakanibu tunggal yang mempunyai masa terluanguntuk belajar di samping kehadiran merekamendapat sedikit insentif kewangan daripadapihak penganjur program. Ketiga, melaluipemerhatian, wanita lebih terbuka untukmenuntut ilmu atas galakan keluarga atau suamiuntuk menghadiri kelas agama. Nisbah saudarabaru wanita jauh lebih tinggi daripada saudarabaru lelaki juga seperti yang dilaporkan di Jepun



Ciri Demografi

JantinaLelakiPerempuan

Umur (tahun)56 ke atas46-5536-4526- 3525 ke bawahMinSisihan piawai

Status perkahwinanBerkahwinBujangJanda/ibu tunggal

Agama AsalBuddhaHinduKristianLain-lain

JADUAL 1Profil demografi responden (n = 60)

Kekerapan

1446

6271782

45.29.8

368

16

42576

Peratus

23.376.7

10.036.028.413.43.3

60.013.326.9

70.08.3

11.710.0

(wanita 69.7% dan lelaki 30.3%) disebabkanpertukaran ke agama Islam berlaku kerana wanitaJepun mengahwini kaum imigran Islam selepasmereka memeluk Islam (Anis 1998).

Jadual 2 menunjukkan profil sosial danagama responden. Mereka memeluk Islam padapurata umur iaitu 25.8 tahun. Ini bersesuaianakta dalam Perlembagaan Persekutuan yangmana seseorang boleh memeluk agama lain padaumur minimum 18 tahun. Responden dalamkajian ini memberi sebab mereka memeluk Islamatas faktor hidayah Allah. Kajian-kajian lain (NorPatimah 1990; Tusibah 1994; Maziah 1995;Rosmawati 1992) walau bagaimanapunmendapati bahawa sebab-sebab lain sepertiberkahwin, pergaulan dengan kawan beragamaIslam, tarikan kepada Islam juga merupakansebab utama saudara baru memeluk Islam.Hidayah ialah petunjuk kepada jalan kebenarandan terbuka hati untuk menerima Islam sebagaicara hidup. Menurut Teh (1990) majoriti yangterlibat dalam pengislaman akhir-akhir ini adalahdi kalangan pekerja yang tahap pendapatanrendah disebabkan taraf pendidikan yangrendah, dan sebanyak sebanyak 60% respondendalam kajian ini mempunyai pendidikansehingga Darjah 6 sahaja. Namun demikianterdapat mereka yang mempunyai tahappendidikan yang tinggi iaitu ijazah pertama

(11.7%) dan mempunyai pekerjaan yang tetapseperti guru dan kakitangan kerajaan (20%).Kebanyakan responden adalah berbangsa Cinadan 70% adalah berasal daripada agama Buddha.Kajian lepas (Rosey 1999) juga menunjukkanbahawa sebahagian besar saudara baru diMalaysia ialah berbangsa Cina yang beragamaasal Buddha (Teh 1990). Lebih-lebih lagi diNegeri Melaka terdapat kelompok masyarakatCina peranakan (Baba) yang telah berasimilasidengan kebudayaan Melayu sejak sekian lama.Menurut Teh (1990) lagi melalui analisisnya diAsia Tenggara, dua perkara yang berharga yangjarang terdapat di kalangan imigran Cina padawaktu penghijrahan dahulu adalah wanita danstatus sosial yang tinggi, dan untukmendapatkannya orang Cina rela pindah keagama Islam melalui perkahwinan dengan wanitaIslam. Analisis Teh (1990) seterusnyamenyatakan, salah satu keuntungan jangkapendek dari pengislaman adalah dengan adanyabantuan kewangan, membantu mencarikanpekerjaan kepada saudara baru yang diberikanoleh PERKIM dan Jabatan Agama di peringkatnegeri.

Jadual 3 pula menunjukkan taburanresponden berdasarkan kehadiran dalam aktivitipembelajaran dalam tahun 2001. Datamendapati bahawa aktiviti kelas fardhu ain



JADUAL 2Profil sosial dan agama (n • 60)

Ciri Sosial Dan Agama Kekerapan Peratus

Umur Memeluk Islam (tahun)10 Ke bawah11 - 2021 - 3031 - 4 041 Ke atasMinSisihan piawai

BangsaCinaIndiaLain-lain

Sebab Masuk IslamHidayah AllahBerkahwinDorongan kawan

Kelulusan AkademikDarjah enamSRP/PMRSPM/ MCESTPM/STUIjazah

PekerjaanKerajaanSwastaSurirumahLain-lain

930867

25.812.6

45510

4875

3661017

12132312

15.049.913.410.111.6

75.08

16.7

80.011.78.3

60.010.016.7

1.711.7

20.021.738.320.0

JADUAL 3Taburan responden mengikut aktiviti pembelajaran yang pernah

dihadiri pada tahun 2001 (n - 60)

Aktiviti Pembelajaran Kekerapan Peratus Kedudukan

Kelas fardhu ainMajlis perayaanCeramah agamaKuliah mingguanKursusDiskusi bersama rakanForum agamaSimposium

606056546453426

10010093.390.076.775.056.743.3

12345678

merupakan aktiviti pembelajaran yang sangattinggi kehadirannya. Ini diikuti pula denganceramah agama (93.3%), kuliah mingguan(90.0%), kursus (76.7%) seperti kursus jenazahdan perkahwinan. Majlis keraian seperti perayaanMaulidur Rasul dan Hari Raya adalah aktivitiyang sangat tinggi kehadiran responden (100%).Kelas fardhu ain yang dianjurkan oleh BalaiIslam sangat mendapat sambutan. Kelas ini

merupakan satu-satunya program yang bolehresponden ikuti setiap minggu iaitu pada hariSabtu dan Ahad. Manakala program ceramahagama dan majlis perayaan pula biasanyadiadakan secara besar-besaran mengikut waktutertentu. Menurut mereka di sinilah tempatmereka bersosialisasi dengan pemimpin dansaudara baru yang lain.



Jadual 4 menunjukkan persepsi respondenterhadap kepentingan objektif programpembelajaran. Secara keseluruhan respondenberpendapat bahawa kepentingan objektifpembelajaran yang mereka ikuti adalah tinggi(min • 4.47). Program pembelajaran yang telahmereka ikuti dikatakan telah dapat memberipanduan dalam mengurus kehidupanberlandaskan ajaran Islam (min = 4.57)meningkatkan kesungguhan belajar (min = 4.53)dan dapat meningkatkan lagi kemahiran sertapengetahuan tentang agama Islam (min = 4.53).

Responden sangat berminat untuk belajarmendalami ajaran Islam. Ini bertepatan dengantujuan pembelajaran dewasa seperti yangdinyatakan oleh Knowles (1984) dan Robinson(1985) bahawa pada suatu peringkat kehidupanseseorang dewasa, orientasi pembelajaran lebihtertumpu kepada keperluan diri, sama ada iaberorientasikan masalah, pekerjaan ataupunkehidupan. Aslanian dan Brickell (1980) sertaGarelli (1996) menambah lagi bahawa faktorpenyebab seseorang untuk belajar ialah akibat

perubahan dalam hidup. Data yang terhasil jelasmenunjukkan bahawa saudara baru yang dikajiamat memerlukan program pembelajaranmengenai ilmu dan amalan Islam yang dianuti.

Data dalam Jadual 5, secara keseluruhanmenunjukkan persepsi responden terhadapsuasana pembelajaran dalam kelas adalahmemuaskan (min = 4.09). Namun begituresponden beranggapan bahawa guru merekaperlu lebih berkemampuan untuk menguasaipelbagai bahasa (min • 3.51, iaitu sederhana)kerana responden terdiri daripada pelbagai kaumdan kebudayaan. Responden juga berpendapatsupaya pengendalian sesi soal jawab dalam kelasdiperkemaskan (min = 3.88) dan keselesaankelas dalam keadaan kurang memuaskan (min •3.90). Ini disebabkan kelas mereka seringdiadakan pada hujung minggu iaitu pada hariSabtu dan Ahad atau pada hari cuti umum, yangmana beberapa aktiviti lain seperti majlis keraiandan program kebudayaan dijalankan serentakberhampiran di mana pembelajaran diadakan.

JADUAL 4Persepsi responden terhadap kepentingan objektif program pembelajaran saudara baru ( n = 60 )

Kenya taan

Mengurus kehidupanKesungguhan belajarMeningkat kemahiranMeningkat pengetahuanKekuatan diriSikap positifMemudah kehidupanTanggungjawab diri

Min Keseluruhan : 4.47, Sisihan Piawai

Min

4.574.534.534.524.484.454.424.27

: 0.68

Sisihan Piawai

.67

.68

.67

.67

.71

.77

.59

.66

Kedudukan

12345678

JADUAL 5Persepsi responden terhadap suasana pembelajaran di dalam kelas (n • 60)

Kenyataan

Hubungan guru- pelajar baikTunjuk ajar yang menarikAktiviti pembelajaran yang berkesanBahan rujukan sesuaiPeluang memberi ideaKelas selesa dan sesuaiSoal jawab dalam kelasKemampuan guru dalam pelbagai bahasa

Min

4.404.384.304.274.053.903.883.51

Sisihan Piawai

.76

.58

.81

.63

.751.04

.80

.89

Kedudukan

12345678

Min Keseluruhan : 4.09, Sisihan Piawai : 0.7



Satu lagi aspek yang menjadi persoalandalam kajian ialah mengenai isi kandunganpelajaran seperti ditunjukkan dalam Jadual 6.Secara keseluruhan responden mengatakanbahawa isi kandungan pelajaran berada padatahap sederhana (min = 3.22). Secara khusus,responden mengatakan isi kandungan pelajarantelah mencapai tujuan belajar mereka (min =4.00) kerana pelajaran tersebut adalahmempunyai aspek teori dan amali (min =4.00). Walau bagaimanapun ada kalanya isikandungan pelajaran tidak dapat menepatikehendak responden (min = 2.62), isipelajaran tidak menentu (min = 2.65) danpelajar tidak tahu isi kandungan untukkelas berikutnya (min = 2.60).

Persepsi responden yang kurang memuaskanini terhadap beberapa aspek isi kandunganpelajaran adalah berkemungkinan disebabkankurangnya penelitian dijalankan oleh penganjurtentang keperluan isi kandungan pembelajaranuntuk saudara baru. Begitu juga tahappenerimaan pelajar yang berbeza meman-dangkan latar belakang pendidikan mereka yangsebahagiannya berada ditahap yang rendah dantempoh mereka selepas memeluk Islam yangtidak sama. Ini kerana menurut Wan Fauziah(1992), hampir 90% daripada saudara baru diMalaysia terdiri daripada golongan yangberpendapatan rendah dan tidak mempunyaikelulusan yang tinggi. Responden jugamenyatakan bahawa mereka tidak dapatmemahami sesuatu pelajaran dengan baik keranaterlalu banyak perkara yang dipelajari pada setiapsesi kelas. Ada kalanya responden masih kurangfaham tujuan mereka belajar untuk sesuatu sesi,apa yang seharusnya dipelajari lebih dahuludan daripada mana hendak bermula mengikutipembelajaran. Kajian Wan Fauziah juga

menunjukkan kurikulum pembelajaran saudarabaru ada kalanya dijalankan secara ad hoc tanpamenetapkan profil pelajar yang menghadirisesuatu sesi pembelajaran. Seperti kajian Maziah(1995) mencadangkan supaya program dakwahperlu dimulakan dengan perkara-perkara yangmenjadi kegemaran mereka dahulu, contohnyahal kemasyarakatan dan sosial kemudian sedikitdemi sedikit dikaitkan dengan agama. Dikalangan responden juga terdapat mereka yangkurang memahami bahasa Malaysia dengan baik.Faktor ini juga menjadi penghalang untukmereka memahami dengan baik isi pelajaranyang disampaikan.

Jadual 7 menunjukkan data yang diperolehdari aspek penyampaian dan pengendalian yangkeseluruhan memuaskan (min = 3.79). Walaubagaimanapun data menunjukkan tahap persepsiyang berbeza mengikut pelbagai aspekpengendalian. Mereka beranggapan bahawapenyampaian guru adalah baik (min = 4.33),begitu juga pengajar memberi peluangberinteraksi (min = 4.17), peruntukan masa yangcukup (min = 4.16), penjelasanjawapan kepadapelajar (min = 4.10). Namun demikian ada aspekpengendalian pembelajaran yang dianggap masihsederhana oleh responden seperti pembelajaranyang hanya menggunakan bahasa Melayu sahaja(min = 2.78).

Fasilitator yang mengajar di kalanganresponden dapat menyampaikan ilmu danberinteraksi dengan baik. Ini kerana guru yangmembimbing mereka mempunyai pengalamanlebih 10 tahun dalam memberi pendidikankepada saudara baru. Demikian juga hubunganantara guru dan murid adalah memuaskan bukanhanya di dalam kelas sahaja, tetapi juga di luarkelas. Responden bersetuju tentang masa yangdiperuntukkan bagi sesuatu sesi kelas iaitu 2

JADUAL 6Persepsi responden terhadap isi kandungan pelajaran dalam program pembelajaran (n • 60)

Kenyataan

Mencapai tujuan belajarMempunyai teori dan amaliDiajar berulang-ulangIsi kandungannya umumIsi kandungan tidak menentuTidak menepati kehendak sayaTidak tahu jadual hari berikut

Min

4.004.003.483.472.652.622.60

Sisihan Piawai

.88

.971.031.051.041.071.12

Kedudukan

1

234678

Min Keseluruhan : 3.22, Sisihan Piawai : 1.03



JADUAL 7Persepsi responden terhadap penyampaian dan pengendalian program pembelajaran (n = 60 )

Kenyataan

Penyampaian guruPeluang berinteraksiPeruntukan masaPenjelasan jawapanPerbincangan melalui bengkelPenggunaan ABMKaedah kuliah sahajaBahasa selain bahasa Melayu

Min Keseluruhan : 3.79 , Sisihan Piawai

Min

4.334.174.164.103.773.653.402.78

: 0.82

Sisihan Piawai

47.61.78.71.811.09.981.12

Kedudukan

12345678

jam. Penyampaian pelajaran yang hanyamenggunakan bahasa Melayu sahaja merupakansatu kelemahan program kerana jumlah guruyang bertugas adalah terhad dan mereka tidakberkemampuan berbahasa lain seperti bahasaCina dan Tamil kecuali Inggeris. Respondenterdiri daripada pelbagai bangsa seperti Cina,India, Portugis, Iban, dan Orang Asli. Merekadikumpulkan di dalam kelas yang sama. KajianMaziah (1995) menyokong kebenaran perlunyafasilitator untuk menguasai beberapa bahasa lainseperti bahasa Inggeris, Cina, Tamil dansebagainya. Data kajian ini juga menunjukkanbahawa responden bersetuju supaya gurumenggunakan pelbagai alat bantuan mengajarseperti slaid, video dan sebagainya. Mereka jugamenghendaki guru menggunakan kaedahmengajar yang pelbagai, tidak hanyamenggunakan teknik ceramah sahaja di dalamkelas.

TANGGAPAN PEGAWAI TENTANGMASALAH PELAKSANAAN PROGRAM

PEMBELAJARAN

Transkripsi data daripada temu bual dengantiga pegawai Balai Islam dianalisis denganmenggunakan teknik 'constant-comparative'.Hasil analisis menunjukkan bahawa programpembelajaran menghadapi tiga masalah utamaiaitu pertama, Balai Islam dianggap sebagaitempat mengadu masalah; kedua, statuspekerjaan pegawai di Balai Islam; ketiga,kurikulum yang kurang lengkap. Setiap satumasalah ini diterangkan dan disokong dengankenyataan verbatim daripada responden. Namaresponden yang digunakan dalam setiapkenyataan verbatim bukanlah nama sebenar atastujuan kerahsiaan.

Balai Islam Dianggap sebagai Tempat MengaduMasalah

Ketiga-tiga pegawai hampir sebulat suaramengaiakan bahawa ramai saudara baru yangmereka temui di Balai Islam sering meluahkanpelbagai permasalahan kehidupan yang merekahadapi selepas memeluk Islam. Seperti kata UstazAhmad:

Kami di sini seolah-olah dianggap sebagai tempatmengadu hal. Mereka datang pada bila-bila masadan bercakap tentang apa sahaja terutamanyamasalah yang mereka hadapi. Ada kalanya merekamengadu tentang buku sekolah anak-anak, anggotakeluarga sakit, masalah tempat tinggal dan pelbagaibayaran biL

Masalah saudara baru yang lebih ketaraadalah berkaitan kemiskinan. Secara keseluru-hannya saudara baru di negara ini merupakangolongan miskin (Teh 1990) dan kemiskinantelah mereka hadapi sebelum memeluk Islamlagi. Ada yang beranggapan bahawa cara mudahmengatasi kemiskinan ialah dengan memelukIslam kerana saudara baru diberi perhatianoleh pelbagai pihak termasuk Balai Islam. Seiringdengan keadaan ini responden lain yang ditemubual mengatakan:

Saudara baru faham yang dalam Islam kita adamemberi zakat kepada orang miskin saudara barudi sepanjang masa. Ada daripada mereka yangdatang ke sini (Balai Islam) meminta hakmereka.... Bantuan zakat bermacam-macamantaranya makanan seperti beras, pakaian danalat untuk bekerja seperti mesinjahit, mesin tebudan Iain-lain (Ustaz Amin).

Ada yang datang hanya untuk mendapatkan wanginsentif kehadiran mengikuti kursus sebanyak RM5sahaja. Dulu mereka dapat RM10, sejak masalah



ekonomi melanda negara wang tersebutdikurangkan kepada RM5 dan itu pun merekasanggup datang untuk mendapatkannya. Jikalausepuluh kali sudah berjumlah RM50 (UstazahAfifah).

Selain itu, hampir semua saudara barumenghadapi masalah dengan keluarga asalmereka selepas memeluk Islam. Situasi pelajaryang terganggu aspek psikologi inimempengaruhi keberkesanan pembelajaranmereka. Ada di kalangan mereka yang diancamdan diusir keluarga menyebabkan timbulmasalah tempat tinggal, malah ada yang terpaksatinggal dengan orang yang bersimpati atauterpaksa menyewa sendiri. Keadaan ini semakinburuk kerana faktor kemiskinan seperti yangdilaporkan oleh Ustaz Amin:

Pihak kami di Balai Islam ada menyediakan kedaipanel untuk saudara baru yang miskin supayamereka mengambil barang keperluan harian disitu dan memang ditetapkan had jumlah hargabarang yang dibenarkan diambil pada setiap bulan.Tetapi masalahnya ialah kadang-kadang merekapergi ke kedai untuk mendapatkan wang dari tuankedai, bukannya barang keperluan harian.

Masalah saudara baru yang lebih sukarmereka atasi ialah pandangan serong orangMelayu terhadap pengislaman mereka. Iniberkaitan dengan anggapan orang Melayubahawa saudara baru mempunyai niat 'ada udangdi sebalik batu' dan tidak ikhlas memeluk Islam.Malah ada orang Melayu yang mengatakan masukIslam bermakna menjadi orang Melayu, yangsituasi ini dinafikan oleh saudara baru keranamereka tidak semestinya mengikuti kebudayaandan cara hidup orang Melayu selepas memelukIslam seperti apabila bersembahyang mestimemakai baju Melayu dan kain pelikat sepertidinyatakan dalam kata-kata berikut:

Orang Melayu khususnya di kampung seringmenganggap saudara baru mesti ikut adat orangMelayu seperti berbaju Melayu dan berkain pelikatbila bersembahyang ke masjid. Perkara ini bukansenang hendak diubah dalam masa sehari duaselepas memeluk Islam. Bayangkan berapa lamadia sudah terbiasa dengan cara hidupnya, tiba-tiba disuruh tukar dalam sekelip mata (UstazAhmad).

Terdapat kes kononnya saudara baru telah murtad.Seorang lelaki Melayu telah membuat laporanmelalui telefon ke Pejabat ini, bahawa saudarabaru telah murtad. Perkara ini berlaku apabila

mereka melihat saudara baru balik ke rumah asalmereka untuk menziarahi keluarga mereka. Tanpausul periksa terlebih dahulu masyarakatmenganggap mereka telah murtad. Dari situtimbullah persoalan ikhlas atau tidak merekamemeluk Islam. Mereka juga sering ditakutkandengan pertanyaan seperti sanggupkah nantiberpuasa sebulan, solat lima waktu, bersunat dansebagainya. Malahan ada yang bertanya pada bakalisteri (saudara baru) sanggupkah berpoligaminanti? (Ustazah Afifah).

Status Pekerjaan Pegawai di Balai IslamAnalisis transkripsi mendapati permasalahanprogram pembelajaran yang dihadapi olehsaudara baru mempunyai kaitan denganpermasalahan yang dihadapi oleh pegawai BalaiIslam dalam pelaksanaan program pembelajaran.Masalah ini dapat diterangkan daripada tigaaspek iaitu jumlah pegawai, status jawatan dankepakaran yang dimiliki.

Jumlah pegawai yang bertugas di Balai Islamialah seramai enam orang. Jumlah ini dikatakanadalah kecil berbandingjumlah pelanggan atausaudara baru yang mereka layani hampir 20orang sehari, yang setiap seorang mengemukakanpelbagai jenis masalah yang sukar untukdiselesaikan dengan segera. Tambahan pulapegawai mengakui kepakaran yang mereka milikiadalah terbatas, khususnya dalam aspekkaunseling, memberi kefahaman tentang Islamkepada saudara baru yang terdiri daripadapelbagai bangsa dan budaya. Di kalangan pegawaiyang ditemu bual mengatakan jawatan merekamempunyai status kontrak, sementara atausukarela. Hanya seorang daripada merekamempunyai kelulusan peringkat ijazah, seoranglagi merupakan bekas tentera dan yang ketigamempunyai kelulusan Sijil Pelajaran Malaysia(SPM). Manakala dua daripada mereka adalah

juga merupakan saudara baru yang telahmemeluk Islam setiap seorangnya pada 27 tahundan 13 tahun yang lalu. Status jawatan sedemikiandisebabkan Jabatan Agama Negeri tidak melihatkeperluan meningkatkan jumlah pegawai di BalaiIslam. Fakta di atas disokong melalui kenyataanverbatim berikut :

Pegawai di sini sebenarnya diambil daripadapelbagai bangsa seperti Cina, India, Sikh dan OrangAsli. Diharapkan dengan adanya mereka di sinidapat membantu memberi kefahaman kepadasaudara baru yang sama bahasa dan latarbelakang budaya. Tetapi sekarang yang tinggalhanyalah pegawai Cina dan India sahaja danseorang Melayu. Tambahan pula mereka tidak



kekal di sini sebab status jawatan bersifatkontrak. Saya sendiri juga berjawatan kontrak.Selepas dua tahun sekali kita memperbaharuikontrak. Jadi keberkesanan kerja terpulang padausaha kita sendiri (Ustaz Ahmad).

Pegawai kita perlu diberi kursus atau latihanmengikut perubahan sesuai dengan perkembanganterkini. Balai Islam sendiri ada menghantar pelajaryang berpotensi di kalangan saudara kita untukmenyambung pelajaran di luar negara supayamenjadi pendakwah dan dapat membantu BalaiIslam pada masa akan datang. Itu pun buat masasekarang cuma ada seorang sahaja. Atau pihakJabatan Agama boleh memberi cuti bergaji kepadapegawai untuk menghadiri kursus ini. Memangkita akui kita kurang terlatih dan mempunyaikelemahan untuk mengendalikan pembelajaran dikalangan saudara baru (Ustaz Amin).

Kurikulum yang Kurang LengkapAnalisis daripada transkripsi data jugamenunjukkan bahawa kurikulum pembelajaransaudara baru telah disediakan oleh pihak JAKIM(Jabatan Kemajuan Islam Malaysia). Namunpegawai mendapati modul yang ada terlaluumum dan tidak mengambil kira profil terperincipelajar yang dikatakan mempunyai latar belakangdan masalah yang berbeza dan rumit. Oleh ituguru terpaksa menggunakan buku yangdiperoleh di pasaran yang memerlukan tahapkebolehan pemahaman yang tinggi. Bukutersebut sering digunakan oleh guru-guru agamayang lain di masjid-masjid. Buku tersebutselalunya menggunakan tulisan jawi yang sudahtentu sukar difahami oleh saudara baru. Masalahini dapat dikesan melalui kenyataan-kenyataanberikut:

Sebenarnya ada kurikulum yang disediakan olehJAKIM, tetapi ada beberapa perkara yang kurangsesuai bila hendak dilaksanakan kepada mualafdi sini. Di kalangan mereka ada yang buta huruf,tidak faham bahasa Melayu dan sebagainya, makakami (Balai Islam) terpaksa mencari sumber laindi pasaran dan berbincang dengan guru yangmengajar mengikut kesesuaian penerimaan pelajar(Ustaz Ahmad).

Buku panduan ini saya dapat daripada kawan sayadi Singapura. Sungguhpun buku ini ditulis dalambahasa Inggeris, nampaknya susunan isi kandunganpelajarannya lebih mudah untuk difahami dansesuai kepada semua peringkat termasuk kita yangtelah lama memeluk Islam sekalipun. Jadi sayagunakan buku ini untuk mengajar (Ustaz Amin).

Pelajar suka bertanya di dalam kelas bila adaperkara yang tidak difahami. Selalunya mereka

banyak bertanya tidak mengira topik dan tujuansesuatu jadual belajar. Apabila ditambah denganpenerangan yang diberikan oleh ustaz terhadapsesuatu pertanyaan pelajar, ini menyebabkan isipelajaran kadang-kadang nampak terlalu banyakuntuk difahami pada sesuatu masa (Ustazah Afifah).

KESIMPULAN DAN CADANGANPerubahan yang terjadi dalam hidup sebagaisaudara baru tidak semudah seperti yang dilihat.Sungguhpun mereka menerima Islam dengansepenuh hati sebagai satu cara hidup, tetapimereka masih kurang memahami apakah perkarayang tergolong sebagai ibadah. Ini memberiimplikasi kepada pembentukan programpembelajaran di kalangan saudara baru.

Purata umur responden iaitu 45.2 tahunmenunjukkan bahawa mereka terdiri daripadagolongan yang dewasa. Secara umum individudewasa mempunyai keunikan tersendiri daripadasegi pembelajaran yang perlu diikuti secara tidakformal. Tambahan pula mereka merupakansaudara baru yang mempunyai pelbagai latarbelakang bahasa, bangsa dan budaya.

Di kalangan saudara baru yang dikaji,golongan wanita merupakan kumpulan yanglebih aktif dalam mengikuti programpembelajaran berbanding lelaki. Ini disebabkanmereka terdiri daripada ibu tunggal ataujandadan mempunyai masa terluang dan jumlahsaudara baru wanita memang jauh melebihijumlah lelaki. Berdasarkan pengalamanpenyelidik, didapati bahawa secara keseluruhankaum wanita pada masa kini lebih berminatmendalami ilmu agama secara tidak formalberbanding lelaki.

Faktor kemiskinan merupakan masalahutama yang dihadapi oleh saudara baru danmereka sentiasa mengharapkan bantuan dariBalai Islam. Lebih separuh daripada respondenmempunyai tahap pendidikan yang rendah. Halini menyebabkan mereka sukar mendapatpekerjaan tetap bagi menjamin masa depanmereka. Pihak Balai Islam amat mengambil beratperkara ini dengan menghulurkan apa sahajabantuan yang termampu kepada saudara baru.Faktor ini merupakan antara sebab melambatkanpencapaian matlamat program pembelajaranyang dilaksanakan. Tambahan pula di kalanganmereka mempunyai pelbagai masalah peribadiyang lain.

Agama Islam bersifat terbuka untukmenerima sesiapa sahaja menjadi penganutnya.Bangsa Cina yang berasal daripada agama



Buddha merupakan golongan yang paling ramaimemeluk Islam. Oleh itu gerakan dakwah kepadamasyarakat Cina perlu diperluas memandangkanmereka merupakan golongan terbesar yangmemeluk Islam di Malaysia berbanding bangsalain. Pandangan negatif segelintir masyarakatMelayu terhadap saudara baru perlu dikikiskerana ia memberi implikasi besar kepada imejumat Islam di negara ini.

Kehadiran pelajar amat memuaskan sewaktudiadakan kelas fardu ain dan ceramah agama.Wang insentif kehadiran sebanyak RM5 mungkinturut mempengaruhi kedatangan mereka kekelas. Pelajar menunjukkan minat yangmendalam untuk mempelajari ilmu danmenerima Islam sebagai cara hidup. NamunBalai Islam masih belum mendapat bahanpelajaran yang dianggap sesuai untuk dijadikanmodul kepada pelajar bagi memudahkanpelaksanaan program pembelajaran. Guru-guruserta pegawai di Balai Islam kurang didedahkandengan latihan atau kursus yang bersesuaian kearah mencapai keberkesanan programpembelajaran.

Daripada empat komponen yang dikajidalam pelaksanaan program pembelajaran dikalangan saudara baru menurut persepsi mereka,satu daripadanya menunjukkan purata skor yangsederhana. Walau bagaimanapun terdapatbeberapa ciri yang masih dianggap lemahtermasuk, suasana persekitaran kelas, isikandungan, dan teknik penyampaian yang perludiberi penekanan oleh Balai Islam dalammelaksanakan sesuatu program pembelajaran.

Daripada persepsi pegawai yang ditemu bual,kajian mendapati mereka menghadapi beberapamasalah dalam pelaksanaan programpembelajaran tersebut. Ini merangkumi tigamasalah utama. Pertama, Balai Islam sebagaitempat mengadu segala hal; kedua, masalahstatus pekerjaan pegawai di Balai Islam danketiga, kurikulum yang kurang mantap. Jumlahpegawai di Balai Islam tidak mencukupiberbanding khidmat yang diperlukan untuksemua saudara baru. Tambahan pula pegawaikurang mempunyai kepakaran dalam kaedahpenyelesaian masalah, kaunseling dan memberikefahaman kepada saudara baru yang terdiridaripada pelbagai bahasa, bangsa dan budaya.Status jawatan kontrak, sementara dan sukarelapegawai dan guru yang bertugas di Balai Islammenunjukkan kurang kepekaan pihak JabatanAgama terhadap kepentingan dan keperluan

dakwah secara bersungguh-sungguh kepadasaudara baru.

Kesimpulan terakhir ialah kajian mendapatipelaksanaan program pembelajaran di BalaiIslam amat penting diberi perhatian yangbersungguh-sungguh bagi memberi kefahamanke arah pengamalan yang lebih baik kepadasaudara baru. Hal ini melibatkan semua pihakdi Balai Islam, Jabatan Agama Islam dan MajlisAgama Islam Negeri. Berdasarkan kesimpulandi atas, beberapa cadangan bagi memper-tingkatkan pelaksanaan program pembelajarandi kalangan saudara baru berdasarkan kontekskajian ini ialah seperti berikut:i) Pihak yang merangka kurikulum program

pembelajaran saudara baru perlu mengkajisecara terperinci mengenai latar belakangpelajar terlebih dahulu. Keadaan ini akanmewujudkan suasana pembelajaran yanglebih baik sesuai dengan sifat pelajar dewasayang sedang melalui proses transisi. Isipelajaran yang baik termasuk teknikmengajar, menggunakan alat bantuanmengajar yang terkini dan sesuai dengankemampuan pelajar menerima pembelajaran.

ii) Mengadakan Islamic Information Centre1,perpustakaan di tempat-tempat strategikseperti di tengah bandar untuk mendidikorang ramai terutama mereka yang barumemeluk Islam dan mereka yang berminatdengan Islam supaya dapat memahamiagama tersebut dengan lebih mudah. Inijuga akan dapat mendidik masyarakat Melayudengan moral yang tinggi supaya menerimasaudara baru sebagai saudara seaqidah tanpamempersoal keikhlasan mereka.

iii) Pegawai-pegawai syarak seperti imam, bilal,ustaz dan ahli Jawatankuasa KeselamatanKampung (JKKK) boleh memainkanperanan penting dengan mengambil saudarabaru sebagai keluarga angkat supaya merekamudah membuat rujukan terdekat untukmenyelesaikan masalah yang dihadapi.

iv) Jabatan Agama Islam Melaka (JAIM) perlumewujudkan rangkaian kerjasama dengansyarikat-syarikat swasta bagi mencaripekerjaan yang sesuai untuk saudara baruatau menjalinkan kerjasama dengan bankbagi mendapatkan kemudahan pinjamankewangan untuk memulakan perniagaankecil dan Iain-lain yang berkaitan. Iniberdasarkan fakta bahawa kebanyakan



saudara baru mempunyai kedudukanekonomi yang rendah.

v) Kajian akan datang dicadangkan supayamenumpukan kepada kaedah pembelajaranyang berkesan di kalangan saudara baruyang bertaraf profesional seperti doktor,peguam, jurutera, saintis dan sebagainya.Kajian akan datang juga boleh ditumpukankepada peranan saudara baru sebagaipemangkin dalam gerakan Islamiah diMalaysia.

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(Diterima: 27 November 2002)



Impact of Credit Risk on Farm Planning in Chiang Mai Valley, Thailand

ZAINAL ABIDIN MOHAMED1, PICHIT THANI2

8c EDDIE CHIEW FOOK CHONG1

1 Department of Agricultural Economics,Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor, Malaysia

2 Department of Agricultural Economics,Chiang Mai University, Chiang Mai Thailand

Keywords: Risk, credit, portfolio, risk-efficient, risk-programming, aversion and E-V frontier

ABSTRAK

Unsur risiko yang dihadapi di dalam usaha perladangan bukan sahaja mempengaruhi strategipengeluaran tetapi juga melibatkan pembuatan keputusan oleh peminjam untuk melabur dankesanggupan pemberi pinjaman memberikan kredit. Risiko yang dikaitkan dengan kos dankemudahan kredit merupakan unsur tambahan di dalam portfolio risiko petani yang akanmempengaruhi penggunaan pinjaman dan struktur pengagihan kapital. Teori portfoliomencadangkan bahawa model risiko-cekap penyelesaian optimum tanpa risiko kredit mempunyaiaktiviti pertanian campuran yang padat. Mengambil kira risiko akan menyebabkan anjakan yangtak selari akan gugusan yang cekap kepada satu tahap varians yang tinggi bagi setiap jangkaannilai fungsi objektif. Kajian ini adalah bertujuan untuk mengukur keperluan kredit dalamkeadaan berisiko di dalam operasi ladang dan kesannya terhadap petani pengelak risiko denganmengguna model pemprograman risiko berbilang masa. Model ini menekankan kaitan di antararisiko kredit dan pendapatan perladangan dan digunakan untuk mengenal pasti perancanganperladangan yang cekap di Chiang Mai Valley. Keputusan pemprograman risiko mendapati ianyabertetapan dengan tindak balas yang dijangkakan. Memasukkan risiko kredit mecerminkankeseluruhan keadaan risiko petani. Apabila tahap pengelak risiko ditingkatkan mengikut peratusanjumlah pinjaman kapital dan operasi, tiada pinjaman kapital dibuat di tahap pengelakan-risikoyang tinggi, dan ini menyebabkan kesemua rizab kredit tidak digunakan, Satu gugusan yangmerangkumi 13 portfolio yang cekap di atas bahagian pertengahan sempadan E-V jugadiwujudkan daripada model pemprograman risiko.

ABSTRACT

The risk elements inherent in farming not only influence production strategies but alsoborrowers decision to invest capital and the willingness of lenders to supply capital Riskassociated with costs and availability of credit is an added element of farmers' portfolio risk,which can influence debt use and the resulting capital structure. Portfolio theory suggests that themodel farm's risk-efficient optimal solutions, derived without credit risk, have a concentrated mixof activities. Incorporation of risk will cause a nonparallel shift of the efficient set towards highervariances for each expected value of the objective function. This study was undertaken tomeasure credit availability in response to risk in farm operations and its impact on risk-aversefarmers by utilising a multiperiod risk-programming model. The model emphasises the relationshipsbetween credit risks and farm income risk and is used to generate risk-efficient farm plans forrepresentative farms in Chiang Mai Valley. The risk-programming results obtained are consistentwith anticipated responses. The inclusion of credit risk takes a fuller account of the overall riskpositions of farmers. As risk-aversion increases as a percentage of total for both capital andoperating loans, no capital loans occur at the highest risk-aversion level, leaving intact the entirereserve of capital credit. A set of 13 efficient portfolios in the intermediate portion of the E-Vfrontier was also generated from the risk-programming model.

Zainal Abidin Mohamed, Pichit Thani & Eddie Chiew Fook Chong

INTRODUCTIONThailand, being a developing country, has 63%of its population engaged in the agriculturalsector. Agriculture not only serves as the majorsource of food and fibres, but is also the mainsource of foreign exchange earnings. Thus, inconsideration of the strategic importance andstrong contribution of agriculture to the wellbeing of the country, the Royal Thai Governmenthas given serious attention to agriculturaldevelopment and production.

Like any other developing country,agricultural production in Thailand facesuncertainties in output namely yield and pricerisks. As such, risk-averse farmers have preferredto adopt less risky crop production strategiesrather than optimise for a profit maximisationstrategy.

The risk elements inherent in farming notonly influence the production strategies but alsoinfluence the decision of borrowers to investcapital and the willingness of lenders to supplycapital. Other things being equal, the greaterthe degree of risk and uncertainty involved in agiven investment, the greater the degree of riskand uncertainty to the person who advancescredit.

A study by Barry et. al (1981) concluded thatrisks associated with costs and availability ofcredit are an added element of farmers' portfoliorisk that influence debt use and the capitalstructure for risk- averse farmers. Hence, it isappropriate to include the effects of credit riskin farm firm analysis in order to evaluate itseffects on farmers' portfolios.

Portfolio theory led us to anticipate that themodel farm's risk-efficient set, derived withoutcredit risk, should have a concentrated mix ofactivities at the peak of the frontier. This resultsin maximum resource utilization and farmgrowth. The risk will also be the highest amongthe risk-efficient solutions. Movements to lowerrisk on the efficient set should show slowergrowth, less use of production capacity, greaterdiversification, lower leverage, larger creditreserves and other risk response factors.

Including credit risk will cause a non-parallelshift of the risk-efficient set toward highervariance for each expected value of the objectivefunction. The effects on an optimal portfoliowill depend on how the decision maker's riskaversion (/) remains constant and the optimalportfolio will have a lower expected value and

variance (Robison and Barry 1977). Still lowerrisk and returns would occur for decreasingabsolute risk aversion. Solution should have somecombination of slower growth of net wealth, lessuse of production capacity, greater diversification,or greater reserves compared to the absence ofcredit risks. Most of the differences should occurin rates of investment and firm growth and inholding of credit reserves.

Thus, the objectives of this paper are twofold:first to develop a procedure to measure creditavailability in response to risk in farm operations,and second to analyse the results and drawimplications of behaviour for risk averse farmersby utilizing a multiperiod risk-programmingmodel which emphasises the relationshipsbetween credit risks and farm income risk, tocome up with risk efficient farm plans for arepresentative farm in the Chiang Mai Valley.In general, farmers in Chiang Mai Valley areconservative due not only to the losses, whichthey may have to incur if losses occur, but alsoby the higher price, which they have to pay forthe loans. In view of the above, problems facedby both farmers and lenders in financing areclosely associated with the risks and uncertaintiesin agriculture.

THE THEORETICAL FRAMEWORKAND METHODOLOGY

The mean-variance approach or portfolio theoryis well known and much debated, especiallyabout the limited generality of its assumptions.However, its widespread use (Robison and Brake1979), its explicit measures of risk, and rigorousdemonstration of its usefulness as an approximatemethod for portfolio selection help make it anacceptable model for showing the portfolioeffects of credit risk (Tsiang 1972; Levy andMarkowitz 1979). Portfolio theory defines arisk-efficient set as the combinations of riskyassets that minimize variance for expectedreturns. In empirical analysis, the risk coefficientset is subject to other specific resource constraintsand business requirements.

Barry et al. (1983) consider a risk-aversefarmer as those who must choose a level of debt(D) with which to leverage equity (£) in financingrisky production with total farm assets (A).Expected returns before interest and consumptionand variance from investment in risky farm assetsare designated rand tr2 respectively. When creditis specified only in deterministic terms, cost of



using credit in borrowing is expressed as rate i =ib + i? with both components having zero variance.Component ih is the interest rate paid to thelender, and liquidity premium if is the farmer'svalue of credit reserve. When credit is treated asa random variable, the cost of using credit inborrowing is expressed as expected rate t, withvariance <T2, and covariance a with return from

i n

risky farm assets. Hence, risk is treated inprobabilistic terms with variance used to measurelikelihood of events occurring that produce lessthan expected results.

To show a closed-form solution, let thefarmer's utility function be approximated by thenegative exponential,

E(U{n)) - E(rA- iD) - (<T2A2) (5)

U{n) = (1)

where n is the degree of risk aversion(T> 0), and t is the level of income. Freund(1956) has shown that maximizing the expectedvalue of a negative exponential integrated overa normal density function, as is assumed for rand i is equivalent to maximizing

E[U(n)] = E(n) - to* (2)

Notation E{n) and (fn now represent theexpected profits and variance, respectively, ofthe farmer's portfolio. Expected profits aredefined as the returns to assets (rA) less the costof borrowing (iD)

n = rA- iD

Portfolio variance is

a2 = a2 A2

(3)

(4a)

where cost of borrowing is deterministicand a random variable

= a2A2 + ofl? - 2ADan, (4b)

Thus, expression (4b) is variance of thedifference between two random variables. Hence,the covariance term has a negative sign precedingit, indicating that the lower (higher) is thecorrelation between r and i, the greater is theincrease (reduction) in total portfolio variance(Fama 1976).

For the deterministic credit case, substitutingthe expressions in equation (3) and (4a) intoequation (2) yields

Substituting D + E = A and considering thelevel of debt (D) as a decision variable, thefirst-order condition for an expectedutility-maximizing level IT is

dU(n)/dD = T- i - 2r a2D- 2ro;E = 0,

which gives optimal debt of

IT = ( 7 - 7 - 2r<T2£)/(2or*)

(6)

(7)

Differentiating (7) with respect to r, i, t, o"-',and E shows the following comparative statisticproperties;

dDVdr =dDVdi =dD*/dE =dDVdr =dDVda2

1/(2TCT2) >- l / (2ra 2) <-1 < 0,(-r-i) / (!

= (-r + 0 /

0,: 0,

2^a2) <(2ra l)

c 0,< 0.

(8a)(8b)(8c)(8d)(8e)

Optimum debt is positively related tochanges in expected returns on farm assets andinversely related to changes in costs of borrowing,equity, variance of returns, and risk aversion. Inthe latter two cases, the inverse relationshipshold as long as expected return on farm assets isgreater than the cost of borrowing.

When credit risks are introduced, theexpression for the expected utility maximizationbecomes

E(U(n)) = E(rA- iD} - r(O?A* + aftf - 2ADaJ. (9)

Again, substituting D + E= A and consideringthe level of credit as the decision variable, thefirst-order condition for an expectedutility-maximizing level Df is

^c/(^) / dD= r- i2TO2D + 4rDa.+ 2r 7icr • 6, (10)

i n n

which gives optimal debt D** of

(y-g-ttffo-o,))= 2r(^+CTf-2an) ( 1 1 )



Comparison of expressions for optimal debtin equations (7) and (11) indicates that theaddition of risk measures for credit will mostlywarrant lower use of debt, although the resultdepends strongly on the level of covariance cr.If, for example, the covariance is zero, then theoptimal debt is clearly less in expression (11).However, if covariance is strongly positive, thenoptimal debt could be higher in expression(11). This is shown by setting equations (7) and(11) equal to each other and solving for o\. Theresult is

(12)

As long as the actual ov is less than a 2,optimal debt in equation (11) will be less thanoptimal debt in equation (7). Comparativestatistic properties for equation (11) are:-

dD*/dr = -1

dD*/di = -

dD*/dr = -

(13a)

(13b)

(13c)

( 1 3 d )

(13e)

(130

dD*/dari = -

These results are more ambiguous than inexpression (8a) through (8e). In all cases, thedenominator values are nonnegative. However,only (13a) and (13b) have definitive numeratorvalue. Debt use is positively related to changes infarm asset returns and inversely related toborrowing costs. The relationship between debtand risk aversion is also inverse if expected farmasset returns exceed borrowing costs. Debtresponses to changes in other parameters cannotbe fully evaluated without knowing their values.

It is important to recall that although theresults obtained in the comparative statisticanalysis appear consistent with intuitivejudgement about financial structure and credituse, they depend on the assumption of expectedutility maximization, normality about r and i,and the choice of utility function. However,these assumptions will be kept throughout theanalysis. These are maximization of expectedutility with an exponential utility function, alinear profit function, and normally distributedprofits. This is equivalent to minimizing theexponent of the expected utility function, whichis a quadratic expression (Freund 1956). Theexponential utility function has the advantageover the quadratic utility function of not implyingincreasing absolute risk aversion (Buccolar andFrench 1978).

A better understanding of the effect ofstochastic credit on expected utility maximizinglevel of debt is needed for effective liquiditymanagement. The importance of credit is clearin the growth process, but the existence ofstochastic environmental variables causes creditto be a random variable. Hence an additionalelement of risk enters the decision process thatmay further influence farmers' production,marketing and financial decisions.

However, the task of measuring credit risk ishampered by the lack of explicit risk pricing onloans by lenders to reflect their judgementsabout farmer's credit worthiness and availabilityof credit funds. Lenders' risk responses arereflected in non-price results that includediffering loan limits among borrowers, anddifferences in security requirements, loanmaturities, loan supervision and documentation,and other means of credit administration(Robison and Barry 1977).

In order to measure credit risk, estimatesare needed on how the lender's non-priceresponses are related to farm income risks and



farm loan demands. Those estimators must thenrelate to the farmer's cost of borrowing. Someapproaches that account for the liquiditypremium on a credit reserve (Barry et aL 1981)show the relationship between the farmer's costof borrowing and lender's non-price creditresponses to risk. The liquidity premium onmaintaining the credit reserve signifies theliquidity risk component of the farmer's totalportfolio risk and is determined by the level ofrisk aversion. Variations in lenders' non-priceresponses in the form of variations of creditlimits, for example, are directly related to afarmer's cost of credit.

MATERIALS AND METHODS

Risk Programming Analysis

The effects of credit risk are evaluated with amulti-period quadratic-programming model,which derives risk-efficient growth plans forvarious levels of risk aversion. Risk-efficient plansare first derived without including credit risk.Then credit risks, based on the lender survey,are introduced to evaluate their effects onselected risk-efficient plans. The decisioncriterion reflects the farmer's preferences as anegative exponential function with normalprobability distributions and a linear profitfunction.

The model used here is a general decisionmodel based on the Markowitz E-V ormean-variance efficiency criterion. It is amodified version of the model employed earlierby Baker et aL (1983). Crop diversification isadded to the original version. It is a multiperiod(four-year), quadratic (QP) model of portfolioselection. The optimization procedure uses thealgorithm "GINO (General InterativeOptimizer)" software, developed by Liebman etaL (1986).

The conventional notation for the QP modelcan be writtten as follows:

Max: r' x -

subject to

A X< b

X, T < 0

where X = (X,, ,XJ; ti =

(14)

(15)

(16)

A);

and Q =

where r is a n x 1 vector of net income assignedto the n x 1 vector of activities X, to evaluatefinal net wealth, which is presented by the linearportion of the objective function. Q variance-covariance matrix, provides an estimate of thepotential variation of outcomes around theexpected value of the portfolio. The matrix A isan (m x n) matrix of technical coefficientsequivalent to the input of a linear programmingmodel. There are m linear constraints (AX) whichmay be equalities or inequalities, and which arerestricted by m right-hand side vector b.

The linear portion of the objective functionmeasures the farm's terminal net worth plus thesum of annual consumption expenditures. Theobjective function entries are equally weightedand expressed in end of horizon baths. Theopportunity cost of money is modelled as a non-farm investment having a risk-free annual yield.This formulation is a future value model withthe opportunity rate of reinvestment on earningsrepresented by the yield on the non-farminvestment.

The quadratic entries in the objectivefunction are the annual variance of gross marginon the production activities and, the varianceand covariance of operating and capital creditwhen credit risk is included. The expected grossmargins and variance-covariance matrix wereestimated from time-series data of yields, pricesand production costs.

Table 1 summarizes the relationships amongborrowing activities, credit constraints, riskmeasures, and other model components. Themeasures of credit availability and risk camefrom Thani's (1988) results. They are brieflyreviewed here. The historical data series offarmer's income and supply of credit wereelicited from individual borrower record keepingand approved loan request forms. Farmers wereclassified into the following six groups: severeloss, moderate loss, average conditions, moderategain, and favourable gain, based on their farmincome experienced by the farmer in thepreceding year. The percentage of loan requestsactually granted was then correlated with thecorresponding levels of farm income. Resultsindicated that the supply of available credit is


oto

f9?X

I

TABLE 1Summary of production and financial components for year one of the programming model

Constraint Produce Borrow Borrow Lease Purchase Hired Non-farm Consume Transfer cashand sell operating capital land machines labour investment and tax

1 2

ObjectiveBeginning cashEnding cashFinance requirementOperating creditCapital creditLandLease limitFamily labourHired labourMachineryAccounung equality

Variance-covarianceProduce and sellOperating creditCapital credit

A-A

-A

1

A

A-A

r2r

r n o

r .

-1l+i0

AA

r2.

rC

-CAd

A

-A-11

AA

-A

-1

1•d+I)

Cn

Ac 1-1

Relation-ship

=<=

.<=< •

< =

< =

< =

< =

< *_

Leve

MaxB00BBBBBBB0

E1

o

I

1

S1

oQo

OP


positively correlated with changes in farmincome. The correlation was stronger for capitalcredit than operating credit. A positivecorrelation between supply of credit and farmincome implies negative correlation betweenborrowing cost and farm income. This adds tothe model farm's total risk.

Data, Farm Resources and ConstraintThe model and data needs are based on a farmrepresentative in the Chiang Mai Valley (Thani1988). The data used in this study were obtainedfrom both primary and secondary sources. Thehistorical data series of farmers' income andsupply of credit were elicited from lender'srecord keeping.

The design of the model is similar to otherrisk analysis models (Barry and Willmann 1976),except that it is modified to include credit risk.Financial components are emphasised, withproduction and post-harvest sales combined intoa single annual activity over the model's horizon.Product diversification and marketing responsesto risk are also considered.

The beginning farm has 10 rais (1 rai = 0.16hectare) of cropland. A land leasing activityallows expansion beyond lOrai. The modelsummary in Table 1 shows that leasing landrequires additional machinery purchase with cashor credit financing. Borrowing activities formachinery have four and five year maturities.Short-term borrowing to supplement the annualcash flow is for one year. Average propensities toconsume, tax, and save from net income are0.50, 0.25, and 0.25, respectively. Each year hastwo cash sub-periods. Maximums are set forleasing in any year, credit for operating andcapital loans, and machinery capacity. Accounting

equ?lities assure that depreciation charges, cashtransfers between periods, and tax andconsumption requirement are met.

The model used in this study requiresestimates of the variances and covariance's ofgross margins of production activities andborrowing cost of credit activities. This part isthe quadratic portion of the objective functionof the model.

The measures of covariance of productionactivities and borrowing cost are derived fromfrom the method of Baker et al (1983). Theyhypothesised that farmers' credit is positivelycorrelated with farm income. The use of averageloan granted as percentages of original loanrequested is preferred over the use of absolutevalue of loan granted. According to Thani (1993),analysis of variance (ANOVA) is conducted tofind out how the amounts of credit granted by aparticular lender vary with changes in farmincome. The variation in credit responsesattributable to the block variable "lenders" issubtracted from the total sum of squares. Theproportion of the remaining total variance thatis due to income treatments is then the partialcoefficient of determination, and the squareroot of that coefficient is a proxy for the partialcorrelation of credit on past income. We areunable to reject the hypothesis tested at the fivepercent level. The results of the ANOVA testimply that credit availability is a source of risk infarm plans, and that it is related to past farmincome. In other words, credit risk contributesto the total portfolio risk in a significant manner.Table 2 shows the variance-covariance matrix ofgross returns for crop activities, while Table 3shows the covariance of gross margins ofproduction activities.

TABLE 2Variance-govariance matrix of gross returns for crop activities

Rice (XI) Soybean (X2)Mung Bean (X3) Peanut (X4) Garlic (X5) Second Rice(X6)

Rice (XI) 8.638E04*Soybean (X2)Mungbean (X3)Peanut (X4)Garlic (X5)Second Rice (X6)

7.84E041.30E03

1.509E041.85E04

5.200E03

5.49E043.34E041.23E045.70E04

4.68E051.41E05

6.205E042.67E055.73E06

7.82E045.16E044.70E044.70E046.32E051.81E05

*E04 - Indicates 4 decimal points to the right similarly, E03,E05 and E06 are 3,5 and 6 decimal points to theright respectively.



TABLE 3Covariance of gross margins of production activities and borrowing cost of credit activities

XIX2X3X4X5X6STBIB4IB5

STB

2.440.94.0591.989.912.850.12

Year 1

IB4

6.372.471.565.1751.927.45

.363

IBS

6.372.471.565.1751.927.45

.363

STB

2.560.990.622.0820.9

30.12

Year 2

IB4

6.692.591.645.4354.517.82

.363

IB5

6.692.591.645.4354.517.82

.363

STB

2.681.040.652.1821.893.140.12

Year3

IB4

7.012.711.715.6957.18.19

.363

IB5

7.012.711.715.6957.18.19

.363

STB

2.811.080.682.2822.893.280.12

Year4

IB4

7.332.841.795.9559.78.56

.363

IBS

7.332.841.795.9559.78.56

.363

STB = short term borrowing activityIB4 • Intermediate term borrowing, at 4th yearIBS • Intermediate term borrowing, at 5th year

RESULTS AND DISCUSSIONPortfolio theory leads us to anticipate that themodel farm's risk-efficient set, derived withoutcredit risk, should have a concentrated mix ofactivities at the peak of the frontier. This resultsin maximum resource utilization and farmgrowth. The risk will also be the highest amongthe risk- efficient solutions. Movements to lowerrisk on the efficient set should show slowergrowth, less use of production capacity, greaterdiversification, lower leverage, larger creditreserves, and more use of other risk responses.

The risk-programming results obtained areconsistent with those anticipated responses. Athirteen risk-aversion level for risk-efficient setwas derived with and without credit risks. Modelresults with and without credit risk are contrasted.Including credit, risk takes fuller account of theoverall risk position of farmers. As risk aversionincreases, the principal responses involve greaterliquid reserves and slower growth. Credit reservesgenerally increase as a percentage of total creditfor both capital and operating loans. No capitalloans occur at the highest risk-aversion level,leaving intact the entire reserve of capital credit.Land leasing declines with increasing riskaversion until no more acerage is leased andpart of the original land is idled. Taxable income,objective function values, and standard deviationsalso increase as risk aversion increases.

A set of 13 efficient portfolios in theintermediate portion of the E-V frontier wasgenerated from the QP model for the case ofwith txedit risk. These portfolios are expected

utility maximizing solutions for risk aversioncoefficient within the range of 0.20 > x > 0.0001.When the risk coefficient is higher than 0.20,the initial point of the E-V frontier maximizesutility. When ris equal or lower then 0.0001, thelinear programming solution is the expectedutility maximizing solution (see Table 4).

The results show that for risk coefficients inthe range 0.20 > T > 0.0001, including credit riskto the analysis is likely to imply a moreconservative strategy in order to maximizeexpected utility than the one adopted whencredit risk is ignored.

Including credit risk in the multi-period QPmodel produces a shift of the E-V frontier andpossible changes in the composition of the riskefficient portfolios. Fig. 1 shows the E-V frontierscorresponding to each one of the two cases.That shift may imply changes in the optimalplans for risk adverse decision-makers.

Similarly, a set of 13 efficient portfolios inthe intermediate portion of the E-V frontier thatwas provided by the model contain optimalsolution for values of risk aversion coefficientthat range from 0.4 > T > 0.001 generated fromthe QP model for the case of without credit risk.Values of risk aversion above 0.40 imply that adecision maker would maximize expected utilityat the lowest feasible point of the E-V frontier(the one with lowest E and lowest V). Values ofthe risk aversion coefficients under 0.001 implythat wealth maximizing (or linear programming)solution maxamizes expected utility. This solutionis also the optimal one for a risk neutral investor.



TABLE 4Composition of the objective function for expected utility maximizing plans on

the E-V frontier under selected risk aversion coefficients

Risk Aversion

0.00010,00050.0010.010.0150.020.040.0450.050.100.150.20.4

*LP solution** Initial Solution

ath

CD•o

c

OU

S5

H

ome

Inc

;ted

iXUJ

140

120

100

80

60

40

20

0

Without Credit Risk

Standard Deviation

7976979769797696898657625482974212830472261362058115883101559668

A Point A

Final Wealth

118869*118869*118869*1149271137631127641043679232883748644365278934426

33226**

_-.—....,....

r Point

:—„

—__ ^—-1—.„

= Initial Solution

With Credit Risk

Standard Deviation

98637874287150563829554734551339614315732669519927161341002211235

.;;.- B ..;. .XM~~——-»^—"

•

Final Wealth

118869*114754110453104219100467984979024681235772456188651221

33226**33226**

cBand C = LP"Solution

> • • • ' • • • •' • ' " • • —

20 40 60 80Standard Deviation (Thousand Bath)

100 120

Fig. 1:

- ^ - Without Credit Risk - # - With Credit Risk

Efficient mean variance frontier for a farmer operator without and with credit risk

CONCLUSION

When credit risks are included in the model andthe solution compared at the same levels of riskaversion, the growth measures and performancedecline and credit reserves increase. Solutionwith high-risk aversion shows little growth infarms size and partial idling of productioncapacity. Moreover, the effects of greaterreliability for capital credit relative to operating

credit are evident as risk aversion increases; thesolutions show a stronger tendency to conserveriskier capital credit by restricting investmentand firm growth, at least until capital loans nolonger occur. Then, further building of creditresolve requires fewer operating loans, whichcan cause idle production capacity.

The stronger portfolio responses by farmerswith increasing absolute risk aversion are


Zainal Abidin Mohamed, Pichit Thani 8c Eddie Chiew Fook Chong

illustrated by comparing solutions obtainedwithout credit risks to solutions with credit risksfor higher risk aversion coefficients.

To conclude, when credit risk is included inthe analysis: (i) the average level of the creditreserve increases faster, and the use of capitalcredit and expansion and expansion of farmgrowth are more rapidly eliminated from optimalplans as the risk aversion coefficient increases,and (ii) for a given level of risk aversion, theaverage level of the credit reserves for bothcredit lines are generally much higher. Hence,these results are consistent with the hypothesisthat more credit risk brings slower growth,greater credit reserves, and some idling ofresources. These results support that credit riskshould be taken into account in farmmanagement decisions.

REFERENCESBAKER, C. B., P. J. BARRY and L R. SANINT. 1983.

Programming analysis of farmers' credit risk.American Journal of Agricultural Economics65: 321-325.

BARRY, P. J. and C. B. BAKER. 1971. Reservationprices on credit uses: a measure of response touncertainty. American Journal of AgriculturalEconomics 53: 222-227.

BARRY, P. J., C. B. BAKER and L. R. SANINT. 1981.

Farmers' credit risks and liquidity management.American Journal of Agricultural Economics63: 216-227.

BARRY, P. J. and D. R. WILLMANN. 1976. A riskprogramming analysis of forward contractingwith credit constraints. American Journal ofAgricultural Economics 58: 62-70.

BUCCOLAR, S. T. and B. L. FRENCH. 1978. Estimatingexponential utility functions. AgriculturalEconomic Research. 30: 37-43.

FAMA, E. F. 1976. Foundation of Finance. New York:Basic Books.

FREUND, R. J. 1956. Introduction of risk in to a riskprogramming model. Econometrica 24: 253-263.

LEVY, H. and H. M. MARKOWITZ. 1979, Approximatingexpected utility by a function of mean andvariance. American Economics Review 69:158-164.

LIEBMAN, J., L. LASDOM, L. SCHRAGE and A. WAREN.

1986. Modeling and Optimization with GINO.New York: The Scientitlc Press.

MARKOWITZ, H. M. 1959. Portfolio Selection-Efficient

Diversification of Investments. New York: JohnWiley and Sons, Inc.

ROBISON, L. J. andj. R. BRAKE. 1979. Application ofportfolio theory to farmer and lender behavior.American Journal of Agricultural EconomicsFebruary: 158-164.

ROBISON, L. J. and P. J. BARRY. 1977. Portfolioadjustments: An application to rural banking.American Journal of Agricultural Economics59: 311-320.

THANI, P. 1988. Socio-economic survey in the ChiangMai Valley. Research Report. Chiang MaiThailand: Faculty of Agriculture, Chiang MaiUniversity.

THANI, P. 1993. Impact of credit risk farm planningin the Chiang Mai Valley, Thailand: amultiperiod risk programming analysis of creditreserve. Unpublished Ph.D Thesis, UniversitiPertanian Malaysia, Serdang, Selangor.

TSIANG, S. C. 1972. The rational of themean-standard deviation analysis, skewnesspreference, and the demand for money.American Economics Review 62: 354-371.

(Received: 14 September 1996)


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Pertanika Journal of Social Science & Humanities

Volume 11 Number 1 (March) 2003

Contents

Residential Satisfaction and Social Integration in Public Low Cost 1Housing in Malaysia - Ahmad Hariza Hashim

Kreativiti Guru Pendidikan Seni - Chua Van Ptaw, Sharifah Md. Nar, 11Nairn b. Mohd & Wan Zah Wan Alt

Ekonomi Negeri Kelantan dari Perspektif Analisis Shift-Share Wilayah 19- Zakariah Abdul Rashid

Predictability of ASEAN-5 Exchange Rates in the Post-Crisis Era - Liew 33Khim Sen & Ahmad Zubaidi Baharamshah

Is MYR/USD a Random Walk? New Evidence from the BBS Test - Kl 41Lim, M Azali & H.A.

Organizational Creative Climate 8c Learning Organization* Factors 51Contributing Towards Innovation Within an Organization - AzahariIsmail, Meriam Ismail, Bohemian Abu Samah, ShamKhairuddin Idris & Jegak llli

Perbandingan Pencapaian Kognitif, Afektif dan Kompetensi Pelajar 69Program Keusahawanan Remaja yang Berlainan Latar BelakangKeluarga - Norasmah Hj. Othman a? Zaidatol Akmatiah Lope Pihte

Status Program Penibelajaran di Kalangan Saudara Baru: Satu Kajian 81Kes di Negeri Melaka - Mohd Azmi Mat Sah & Maimunah Ismail

Impact of Credict Risk on Farm Planning in Chiang Mai Vall< 97Thailand - Zainal Abidin Mohamed, Pichit Thani & I :v FookChang

jssh vol. 11 (1) mar. 2003

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