a study about the influence of ‘recommended seller’ as perceived value towards purchase...

The Influence of ‘Recommended Seller’ as perceived value towards purchase intention of Kaskus’ Community

Fajar Sidik Prasetya

THE INFLUENCE OF ‘RECOMMENDED SELLER’ AS PERCEIVED

VALUE TOWARDS PURCHASE INTENTION OF KASKUS’ COMMUNITY

By

FAJAR SIDIK PRASETYA

1-6109-013

A THESIS SUBMITTED TO THE FACULTY OF

BUSINESS ADMINISTRATION AND HUMANITIES

In Partial Fulfillment of The Requirements

For the

BACHELOR’S DEGREE

In

COMMUNICATION AND PUBLIC RELATIONS

Swiss German University

Edu-Town BSD City

Tangerang 15339

JULY 2013

Revision after thesis defense on 24th July 2013



STATEMENT BY THE AUTHOR

I hereby declare that this submission is my own work and to the best of my

knowledge, contains no material previously published or written by another person,

nor material which to a substantial extent has been accepted for the award of any

other degree or diploma at any educational institution, except where due

acknowledgement is made in the thesis.


______________________________________ ________________

Student Date

Approved by:

Loina. L. K Perangin-perangain, MSi

________________________________________ __________________

Advisor Date

Parhimpunan Simatupang, MBA

______________________________________ _________________

Dean Date



ABSTRACT

The Influence of ‘Recommended Seller’ as Perceived Value Towards

Purchase Intention of Kaskus’ community

By:


SWISS GERMAN UNIVERSITY

Edu-Town BSD City

Loina L.K Perangin-angin, Advisor

The purpose of this research is to analyze how much the influence of recommended

seller as perceived value towards the purchase intention and also find out the factors

that involved in influencing the customers’ purchase intention. This research uses

Pearson correlation to find the level of influence of recommended seller as perceived

value and factor analysis to find the factors that involved in recommended seller as

perceived value. The results of this research proved that the recommended seller as

perceived value as highly influential in determining purchase intention of customers,

which is the kaskus’ community. Furthermore, this research also proves that there are

three factors of recommended seller as perceived value that affect purchase intention

of Kaskus’ community, which are: the good communication between seller and buyer,

the emotional or trust level of customers, and the price offered.

Keywords: Perceived Value, Purchase Intention, Online Trading Forum



© Copyright 2013

by Fajar Sidik Prasetya

All rights reserved



DEDICATION

I dedicate my thesis to my family and many friends. A special feeling of gratitude to

my loving parents, my sisters and my brother who have never left my side and are

very special. I also dedicate this bachelor thesis to my many friends who have

supported me throughout the process; I will always appreciate all they have done.



ACKNOWLEDGMENTS

It would not have been possible to write this thesis without the help and support of the

kind people around me, to only some of whom it is possible to give particular mention

here.

Above all, I would like to thank my family, especially my parents for their personal

support and great patience at all times. My parents, brother and sister have given me

their unequivocal support throughout, as always, for which my mere expression of

thanks likewise does not suffice. And I am also very grateful to my related-family,

which are Agung, Bagus, Mamiq, Mama’, and Angger who always be the reminder-

machine of the goodness and accepted me as I am.

I would like to express my deepest gratitude to my advisor, Mrs. Loina L. K.

Perangin-Angin, Msi, for her excellent guidance, caring, patience, and providing me

with an excellent atmosphere for doing research. And also very grateful to all people

in Communication and Public relations department of SGU (Pak Matthias, Bu Ezmi,

Bu Sofie, Pak Munir, and Ms. Anis who have helped me in giving a lot of inputs)

Finally, I would like to thank my best friends (Dira, Via, Thepi, Ivy, Linda, pipit, Titi,

Rhea, Szy-szy, Lala, Kazu, Bidary, Edo, and Joseph) was always there cheering me

up and stood by me through the good times and bad.



TABLE OF CONTENTS

STATEMENT BY THE AUTHOR……………………………………………. i

ABSTRACT…………………………………………………………………………........................... ii

DEDICATION…………………………………………….......……………………………………… ii

ACKNOWLEDGMENT…………………………………………….......................................... iv

CHAPTER 1 – INTRODUCTION……………………………………….................... 1

1.1 BACKGROUND……………………………………………………………. 1

1.2 RESEARCH PROBLEM……………………………………………………… 5

1.3 RESEARCH QUESTIONS…………………………………………………… 5

1.4 RESEARCH PURPOSE……………………………………………………….. 5

1.5 SIGNIFICANT OF STUDY…………………………………………………… 6

1.6 SCOPES AND LIMITATIONS……………………………………………. 6

CHAPTER 2 – LITERATURE REVIEW………….………………………………........... 8

2.1 THEORETICAL FRAMEWORK………………………………………….. 8

2.2 MARKETING COMMUNICATION……………………………………… 8

2.3 ONLINE MARKETING………………………………………………………. 11

2.4 VALUE……………………………………………………………………………. 13

2.5 PERCEIVED VALUE………………………………………………………….. 13

2.6 PURCHASE INTENTION……………………………………………………. 16

2.7 THEORETICAL HYPOTHESIS……………………………………………. 10



CHAPTER 3 – METHODOLOGY……………………………………………..................... 21

3.1 TYPE OF STUDY……………………………………………………………… 21

3.2 UNIT OF ANALYSIS…………………………………………………………. 22

3.3 POPULATION AND SAMPLE…………………………………………….. 23

3.4 DATA COLLECTING TECHNIQUE………………………………………. 24

3.5 DATA ANALYSIS TECHNIQUE…………………………………………… 24

CHAPTER 4 – ANALYSIS & DISCUSSIONS…………………………………………… 29

4.1 KASKUS BACKGROUND……………………………………………………. 29

4.2 RESEARCH RESULTS………………………………………………………. 31

4.3 VALIDITY AND RELIABILITY TEST…………………………………… 47

4.4 NORMALITY TEST…………………………………………………………… 51

4.5 CORRELATION TEST OF VARIABLE X TOWARDS

VARIABLE Y…………………………………………………………………….. 54

4.6 FACTOR ANALYSIS………………………………………………………….. 55

CHAPTER 5 – CONCLUSION AND RECOMMENDATION………………………… 62

5.1 CONCLUSION………………………………………………………………….. 62

5.2 RECOMMENDATION. ……………………………………………………….. 63

REFERENCES…………………………………………….......………………………………………. 66

APPENDINCES……………………………………………………………………………………… 70

CURRICULUM VITAE……………………………………………………………………………… 100



LIST OF TABLES

1.1 RANKING OF WEBSITE IN INDONESIA …………………………………………….. 2

3.1 CONCEPT OERATION………………………………………………………………………… 25

4.1 SEX RESPONDENTS OUTPUT……………………………………………………………... 32

4.2 RESPONDENTS AGE OUTPUT…………………………………………………………….. 33

4.4 DURATION AS REGISTERED-‐MEMBERS……………………………………………. 34

4.5 BUYING FREQUENCIES…………………………………………………………………….. 35

4.6 VARIABLE X ITEM1 DESCRIPTIVE OUTPUT……………………………………….. 36

4.7 VARIABLE X ITEM2 DESCRIPTIVE OUTPUT……………………………………….. 37

4.8 VARIABLE X ITEM3 DESCRIPTIVE OUTPUT………………………………………. 37

4.9 VARIABLE X ITEM 4 DESCRIPTIVE OUTPUT……………………………………… 38

4.10 VARIABLE X ITEM 5 DESCRIPTIVE OUTPUT…………………………………….. 38



4.13 VARIABLE X ITEM 8 DESCRIPTIVE OUTPUT…………………………………… 40

4.14 VARIABLE X ITEM 9 DESCRIPTIVE OUTPUT…………………………………… 41

4.15 VARIABLE X ITEM 10 DESCRIPTIVE OUTPUT………………………………….. 42

4.16 VARIABLE Y ITEM 1 DESCRIPTIVE OUTPUT……………………………………. 43

4.17 VARIABLE Y ITEM 2 DESCRIPTIVE OUTPUT…………………………………….. 43









4.24 VALIDITY OF VARIABLE X OUTPUT…………………………………………………. 48

4.25 VALIDITY OF VARIABLE Y OUTPUT………………………………………………… 49

4.26 RELIABILITY OF VARIABLE X OUPUT……………………………………………… 50

4.27 RELIABILITY OF VARIABLE Y OUTPUT……………………………………………. 50

4.28 NORMALITY TEST OF VARIABLE X OUTPUT…………………………………….. 51

4.29 NORMALITY TEST OF VARIABLE Y OUTPUT……………………………………. 52

4.30 CORRELATIONS OUPUT. ……………………………………………………………….. 54

4.31 1st KMO AND BARLETT’S TEST OUTPUT………………………………………… 55

4.32 1st ANTI IMAGE MATRIX OUTPUT………………………………………………….. 5 5

4.33 1st COMPONENT MATRIX OUTPUT………………………………………………….. 56

4.34 2nd KMO AND BARLETT’S TEST OUTPUT………………………………………… 57

4.35 2nd ANTI IMAGE MATRIX OUTPUT…………………………………………………. 57

4.36 2nd COMPONENT MATRIX OUTPUR…………………………………………………. 58

4.37 3rd KMO AND BARLETT’S TEST OUTPUT…………………………………………. 59

4.38 3rd ANTI IMAGE MATRIX OUTPUT…………………………………………………… 59

4.39 3rd COMPONENT MATRIX……………………………………………………………….. 60

4.40 3rd TOTAL VARIANCE EXPLAINED OUTPUT…………………………………….. 60



LIST OF FIGURES

1.1 COMPARISON OF KASKUS TOWRDS OTHERS…………………………………….. 2

2.1 THEORETICAL FRAMEWORK……………………………………………………………. 8

3.1 THE ASSOCIATIVE CORRELATION…………………………………………………….. 21

3.2 THE CALCULATION OF SAMPLE SIZE………………………………………………… 23

4.1 PERCEIVED VALUE NORMALITY PLOT OUTPUT………………………………… 52

4.2 PURCHASE INTENTION NORMALITY PLOT OUTPUT…………………………. 53



LIST APPENDICES

APPENDIX A – SURVEY QUESTIONNAIRE ………………………………………………. 71

APPENDIX B – DATA OF RESPONDENTS…………………………………………………. 74

APPENDIC C – SPSS 21.0 FOR MAC…………………………………………………………... 79



Chapter 1 Introduction

1.1 BACKGROUND

Communication activities are basically one of the most important applications in daily

life, and applicative has many forms. Nowadays, the impact of technology

development communication has evolved and changed its shape. Communication

media is more advanced and able to provide services and the functions more effective

and efficient in communicating. One of those medias that have a possibility to

conduct effective and efficient communicating is the computer. Because of the

computer, individuals are now having a possibility to access the Internet. Basically,

Internet is a network that allows individuals to interact and make contact through the

computer. Internet can overcome barriers of distance and time, especially in

communication between individuals, even the other things.

As direct communication, it is assumed that communication through the Internet is

also influenced by some factors, such as individual factors. From various sources, also

found out that there are factors of anonymity, equality, and anxiety associated with

perceived personal communications over the Internet. As a communication activity,

basically, communication through the Internet also has a lot of purposes in their

applications. (Singgih: 2011)

Based to the explanation above, the researcher can be concluded that the Internet has

a high possibility to help the communication activities in many ways, such as mass

communication. Nowadays there are a lot of types of mass communication, for

instance; TV, Radio, newspapers, and the Internet forums. Essentially, the Internet

forum is one the most common mass communication on Internet, which has a lot of

companies or individuals conducting their marketing strategies. Nowadays, in

Indonesia there are many Internet forums, but the most Internet forums frequented or

used by the Internet users is www.kaskus.co.id. It can be seen from the top 10 ranked

websites frequently visited in Indonesia, which www.kaskus.co.id the only ones

online forum that falls into the ranking.



Table 1.1. Ranking of website in Indonesia

No Website

1. Google (www.google.com)

2 Facebook (www.Facebook.com)

3. Blogspot (www.blogspot.com)

4. Youtube (www.youtube.com)

5. Google Indonesia (www.google.co.id)

6. Yahoo (www.yahoo.com)

7. Detik (www.detik.com)

8. Kaskus (www.kaskus.co.id)

9. Wordpress (www.wordpress.com)

10. Twitter (www.twitter.com)

Source: www.alexa.com

From the data above, it can be seen that the traffic of www.kaskus.co.id is located at a

very high level; even they beat one of the world’s largest social media, which is

Twitter.

Figure 1.1 Comparison of Kaskus towards another online forum.

Source: www.alexa.com



Furthermore, if we take a look at the comparison of the traffic’s level above,

www.kaskus.co.id is very far away from their competitors such as

www.modifikasi.com, and www.malesbanget.com.

Kaskus is the largest virtual community forum site in Indonesia and the forum users

on that site are called “Kaskuser”. Kaskus was born on November 6th, 1999 by the

three young men from Indonesia, namely Andrew Darwish, Ronald Stephanus, and

Budi Darmawan, who are currently studying in Seattle. Along their development,

today this site is managed by PT Darta Media Indonesia and Currently Kaskus has

more than 4,1 million registered members. Kakus’ member generally comes from the

teenagers to adults who are domiciled in Indonesia even outside of Indonesia. The

Kaskus itself stands for “Kasak-Kusuk”, and started from a hobby of a small

community, which later evolved to the present. The Kaskus site at least had been

visited by 900 thousand people, with more than 15 million page views per day.

Initially, Kaskus’ more discussed about the underground things and more smelling

about immoral. But it changed after there was a Indonesian government regulation on

the use of Internet. So Kaskus threw away all about the negative things on their site,

and it made the level of mass communication on wwww.kaskus.co.id became so well

and also created a lot of positive things. Because of these things, enabled the users of

www.kaskus.co.id to utilized Kaskus as the media in economic transactions such as

buying and selling forum. Therefore Kaskus today is facilitated their users in freely

and openly argued, allows a person to sell and buy goods from the int4ernet and also a

nice place to get backlinks.

Today, Kaskus has two parts; those are the lounge forum and trading forum, which is

in the lounge forum more about discussion, sharing and community. Conversely, their

buying and selling or trading forum is a place or online platform where economic

transactions, which everyone on that forum has a possibility to sell or buy the items

that they want to. On the kaskus’ trading forum basically there are more than 30

categories of products and services traded, starting from the music to the video game

devices. And the trading forum also displays the products or services most sought

after and also the best-selling products are sold. Hand phone and PDA category is the



one of categories that have a lot of sellers’ thread, which there are 476.314 sellers’

thread. So it could be said, there are about 470.00 products in terms of hand phone

and PDA are offered on that category.

To be concluded, this study is more focused on the kaskus’ trading forum. Which is in

each month on the trading forum can make the transactions of money up to Rp 575

billion (www.kompas.com: 2012). And also Kaskus’ trading forum has made a

significant impact on Internet traffic of www.kaskus.co.id. The high revenue earned

from the kaskus’ trading forum is the impact of mass communication and good

quality between the sellers and buyers. On the kaskus’ trading forum, the good sellers

often referred to as “recommended seller”, which recommended seller is

characterized by the number of valid testimonials, a valid username, the join date

which can be seen, whether they are a newbie or not, and the last is the total number

of posts, and also the implementation about the price.

In such case, the seller sends a value to the customers where the customers who

captures it into a perceived value. Basically, there are two types of perceived value in

customers’ view, which are positive and negative. According to Komulainen,

Mainela, Tahtinen, and Ulkuniemi in Alsheikhand and Bojei (2012) revealed that

Perceived value consist of benefits and sacrifices. The studies based on the thought

that benefits and sacrifices are sometimes not equal. The difference could be positive

or negative. Usually, the positive result will build a customer perceived value, and the

result will be negative customer perceived worthlessness.

On trading forum of www.kaskus.co.id the seller basically trying to send the positive

perceived value to the customers. In positive terms, the customer will see “the

recommended seller” from the seller thread on www.kaskus.co.id as something that

can or influence their purchase intention against a product or service offered.

And also in the journal “Factors that influence customers buying intention on

shopping online” from Yulihasri, Aimnul and David (2011) revealed among all the

students proposed differences factors, compatibility and usefulness have been found

as the most significant to influence attitude for shopping on the internet and attitude,



normative-belief have been found as the most significant to influence students’

intention for shopping on the internet. From that journal can be concluded that the

trustiness of the seller can make buying intention from the customers. Which on

trading forum of www.kaskus.co.id, beliefs itself arises from the factors of

recommended seller.

From the description above, this research will be continued in order to determine the

relationship between purchasing intentions towards the seller’s quality, and this study

will be titled “the influence of ‘recommended seller’ as perceived value towards

purchase intention of Kaskus’ community”.

1.2 RESEARCH PROBLEM

Based on the background above, specifically issues such study formulated the

problem as follows:

• Today, there are a lot people in Indonesia conducted a transaction or trading

on the kaskus’ trading forum and usually on www.kaskus.co.id the potential

buyers take a look at the recommendation on the thread of the sellers before

making a purchasing.

• How far the “recommended seller”, which was given to quality seller and will

build a perceived value can influence the purchase intention of customers.

1.3 RESEARCH QUESTION

1. How are the influences of “recommended seller” to increase purchase

intention from the potential buyers?

2. What factors are involved in influencing the customers purchase intention?

1.4 RESEARCH PURPOSE

Based in the background and research problem of this research, the purposes of

this research are:



• Analyze the influence of “recommended seller” as perceived value, from the

qualified sellers on Kaskus’ trading forum towards purchase intention of

Kaskus community.

• Analyze the factors that involved in influencing the customers’ purchase

intention.

1.5 SIGNIFICANT OF STUDY

1.5.1 ACADEMIC SIGNIFICANT

This study is expected to clarify the influence of sending-values or

messages qualities on online trading forum towards the purchase intention

of potential customers, which is the community on the online platform.

This study is also expects to be used as scientific study for academic

interest and further research.

1.5.2 PRATICAL SIGNIFICANT

This study is expected to be material information for the company or

specifically for the online shopping website in setting up the strategic

policies with concern to the influence of the seller’s quality towards buying

intention of the customers.

1.6 SCOPE AND LIMITATIONS

This research will analyze relationship between buying intentions towards the

seller’s quality among adolescents and young adults in Indonesia who are active

and knowing about Kaskus.co.id. This limitation is determined because one

reasons, those are:

• Registered member of www.kaskus.co.id.

• People who have shopping-experienced on www.kaskus.co.id.



Chapter 2 Literature Review 2.1 THEORETICAL FRAMEWORK

Figure 2.1 theoretical frameworks

2.2 MARKKETING COMMUNICATION Basically, communication is a process in which thought and understanding delivered

between the organization and the individual. The other hand, marketing basically is a

set of activities in which companies and other organizations to transfer the values that

they have been made to the customers. So if it combined, marketing communications

represent the combination of all the elements in the marketing mix that facilitate the

exchange to create a meaning that is distributed to customers (Terence and Shimp

2003: 4).

According to Kottler and Keller (2006: 496) marketing communication is the way of

the company to inform, persuade and remind consumers directly or indirectly about

their goods and services.

According to Arens in Alifahmi (2005: 14), marketing communication is the process

to establish and strengthen mutually beneficial relationship with employees,

customers, and all stakeholders to develop and coordinate strategic communications

programs to enable them to undertake constructive contract with the company or

brand of products through various media.

Recommended Seller as Perceived Value (Variable X) -‐ Emotional -‐ Social -‐ Quality -‐ Price

Sweeney and Soutar in Aakouk, 2006)

Purchase Intention (Variable Y)

-‐ Likely -‐ Definitely Would -‐ Probable

Churchill and Iacobucci (2005)



Based on definitions above, it can be concluded that in conducting marketing

activities, communication activities should be carried out to deliver a message or a

positive value of the products or services offered by the company to the public

through a series of promotional activities and also through various available channels.

2.2.1 MARKETING MIX

Marketing mix defined as a set of tactical marketing tools and a combined from the

company to produce the desired response the target market. (Kotler & Armstrong,

2001: 71). Basically, marketing mix is the tool of marketing, which consists of 4

elements, are better known as the 4Ps. The marketing mix consists of everything the

firm can do to influence or persuade the demand fro goods or services. 4Ps elements

that have been popularized by E. J McCarthy divided into 4 parts; those are Product,

Price, Place and Promotion. ( Arachchige, 2002: 6)

-‐ Product

Product basically is the first element or component in the marketing mix, and

they could be as a tangible or an intangible.

According to Kotler and Assael (2013) Products and services divided into four

major group and it based on the products and services, which are preferred to be

offered, and what products and services that serve as a means support.

a. Pure product

The tangible goods that have a tangible manifestation of a physical, palpable,

smell and so on. For example coffee, hand sanitizer or soap, which generally

makes unsupported and does not require the services.

b. Product Related Services.

Usually accompanied by warranties of merchantability, for instance:

smartphone, cars, computers and other electronic goods. Product related

services are tangible goods that have a tangible manifestation of physically

supported services to add the appearance to customers.



c. Equipment Intensive Service.

The intensity of service offered is greater that the previously mentioned.

However, to produce the services offered to customers needed support from

tangible goods. For instance: in lodging services (hotels), where in additional

to offering lodging services also offers restaurants, fitness facilities and others.

d. Pure Services.

Generally, this is absolutely pure services which is in the production process

does not use and do not require the existence of tangible goods. For example:

PR firms or agencies and lawyers and others.

Based on the explanation above, the researcher has a possibility to conclude

that the product categories offered by www.kaskus.co.id is the pure services

and also it offered for free, which in kaskus.oc.id everyone can be a member

and doing an online-trading for free.

-‐ Place.

Physical distribution is the delivery of goods at the right time and at the right

place of customers. And basically, place is the location where a product can be

purchased. This is usually often referred to distribution channels, which include

any physical store as well as virtual stores on the Internet.

-‐ Promotion.

The activities of promotional are necessary for the huge scale marketing and also

for facing market competition effectively. Such activities are varied in nature and

are useful for establishing reasonably good rapport with the target market or

customers. Here, usually www.kaskus.co.id do the marketing from the published

books about online-trading forum by Kaskus or FJB Kaskus, and

www.kaskus.co.id also suggested to the seller on their platform to asking a good

testimony from the seller’s customers.



-‐ Price.

This is the critical component of the marketing mix. Basically, this is determined

by a number of factors including market share, competition, material costs,

product identity and the customers’ value perceived. An attempted to increasing

the price of products, if others selling at the same products.

It can be conclude that this research only focused on one of the marketing mix, that is

promotion and it can be called as a marketing communication. Basically, promotion is

an activity that communicates about the advantages of product or service, and also

persuades the target market or customers to interesting to buy those products or

services.

2.3 ONLINE MARKETING

According to Chaffey (2006: 6) online marketing is the related activities to achieve a

marketing purpose and/or support the modern marketing concepts through the Internet

as media.

Kotler and Armstrong (2004: 40) revealed that the online marketing is a activity

through the internet that conducted by the company or individual with the aims to

inform, communicate, promote and selling the products and services.

According to Bandyo and Padhyay (2003: 6) Online marketing is the use of network

as the tool to reach customers. Online marketing activities generally include the

matters relating to the manufacture of product ads, buyers searching, and copywriting-

making.

To be concluded that online marketing is an activity from the company or individual

to promote, communicate, inform and selling its products in the form of goods and

services through the internet as the media and also putting an unique or exciting

copywriting or symbols.



2.3.1 THE BENEFIT OF ONLINE MARKETING

According to Kotler and Amstrong (2001: 260) stated the benefit of online marketing

is divided into two, those are: for buyers and the marketers or sellers

1. Online marketing benefits for the customers are:

a. Comfortable; Customers do not need to wrestle with traffic, finding a

parking spot, and walk from store-to-store and aisle-to-aisle seemingly

calculated to locate and inspect the product. Consumers have possibility to

compare the brands, check the process out, and ordering the products or

services in 24 hours from anywhere.

b. Easy and personality; the customers will find out fewer squabbles when

buying and do not have to deal with salespeople or provide an opportunity

to be persuaded.

c. Informative; Customers have a possibility to obtain more comparative

information about the companies and the products.

d. Interactive and immediate; Consumers can find the desired product

information, and ordering information or keep it in place.

2. Online marketing benefits for the marketers or sellers

a. Customer relationship development; this relationship makes the company

and its customer are more familiar. Companies can interact with customers

to learn more about the needs and desires of customers are special, and to

build data-center of customers.

b. Reduce costs and improve efficiency; online marketers avoid spending to

care for and store leases, insurance coasts, and electricity and so. Because

customers can make a deal directly with the seller, online marketing often

result in lower costs and increased efficiency for distribution and logistics

functions such as order processing, handling the preparation, submission,

and trade promotion.

c. Getting better in flexibility; which make marketers have a possibility make

adjustments to ongoing programs on offering and biding.



2.4 VALUE

Value of a product can be defined as the ration between what consumers get and what

consumers give. A consumer gets the benefits of a product and gives costs. Intended

beneficiaries including the functional usage and also the usability emotional. While

the cost is included in the monetary cost, the cost of time, labor costs, physical cost

(Kotler, 2001).

A company may want to increase the value of their offering to consumers in several

ways as follows:

a. Increase the usefulness or benefit

b. Reduce costs

c. Improve usability is greater than the increased cost

Beside that, According to Kertajaya in his book of Marketing Plus (2002) defined that

the ratio is between the value and the quality of the product price.

2.5 PERCEIVED VALUE

According to Cronin, Brady and Hult (2002), the perceived value is the overall

assessment of the customers of the utility goods based on the perception of what is

acceptable and what is given. And also according to Sweeney and Soutar (2001),

defines customer value as perceived customer preference for and evaluation, product

attributes, performance attributes, and consequences in terms of the customer’s goals

and objectives. Perceptions of value also vary according to the situation of use

(Anckar and D’Incau, 2002).

It can be conclude that perceived value is benefits received by the customer in relation

to the total cost (including the price has been paid and also other costs associated with

purchase). Usually, perceived value is also used by consumers to consider various

aspects of the service compared with the cost of relatively few providers that offer

products or services in their competition. Thus, perceived value can be viewed as a



relative measurement of the cost and financial aspects of a company’s services in

comparison with existing competitors.

Currently, customers are faced with an abundance of products and options, price,

brand, and a lot of marketing tricks. Customers will have a fact that they (company or

individuals) still offering the highest value (Kotler, 2001). Basically, customers will

form an expectation of value and act to get what they should have been obtained. At

the end, it will affect customer satisfaction and repurchase opportunities by customer

(Kotler, 2001). Value obtained is about relating to the perception and assessment of

the customer, not related to the monetary price that has been paid.

Basically, strategy of increasing value will have an impact on increasing the perceived

benefits, perceived reduce costs, or both together. Money is on of several costs that a

customer of online shopping is usually sacrificed. It can be said that actually a lot of

evidence that customers are willing to make a deal with their money against other

strains in the cost of a benefit.

They would prefer shopping online which gives more pressure on themselves,

compared to traditional shopping, for instance like going to the store to looking for a

mobile phone, where in the store they will not get more personal pressure, such as

they worried about being cheated or other fraud. However, in traditional way, they

have to incur additional costs, such as time and effort. While on shopping online, they

will certainly get a greater pressure, but the sacrifices of time and energy or effort that

they waste will quite efficient.

It can be conclude that the online marketers trying as much as possible to sending a

positive value to influence the customer. As done by the seller on www.kaskus.co.id,

they basically make the recommended seller as the perceived value.

2.5.1 PERCEIVED VALUE SCALE

Perceived value scale is a measure of the perceived value that applied to measure the

tangible product. Wahyuningsih (2004: 8) developed a model of the components of

customer value that consists of benefits and sacrifices. Loyalty formation can be done



by the creation of customer value received is the difference between the evaluation of

prospective customers for those benefits and all costs and offer some alternatives that

thought (Kotler 2007: 173). It can be seen in the following equation:

The intention is:

V: Value

B: Perceived value (product, marketing activities, image)

C: Sacrifices (money, time, and energy)

Total customer value is a set of benefits received from the customer specific products

or services are consumed. Total cost of sacrifices is a set of customers who sacrificed

customers in evaluating, obtaining, using and disposing of a product and service. The

perceived benefits customers consist of the benefits of products, services, marketing

activities, as well as image the company or individuals. While the sacrifices by the

customer are monetary and non-monetary, such as; time, energy, and psychological

aspects.

Benefits associated with product reliability, durability, performance and resale value

of the product or service being offered. Service benefits is the extent to which a

particular product or service that offered in conjunction with delivering, trusting, and

the maintenance

2.5.2 DIMENSIONS OF PERCEIVED VALUE

According to Sweeney and Soutar in Aakouk and Mostafa (2006), there are four main

aspects of perceived value dimension, those are:



1. Emotional value

The utility derived from the feeling or affective states that a product generates.

2. Social value

The utility derived from the product’s ability to enhance social self-concept.

3. Quality or performance value

The utility derived from the perceived quality and expected performance of

the product.

4. Price or value for money

The utility derived from the product due to the reduction of its perceived shot

term and longer-term costs.

2.6 PURCHASE INTENTION The marketing activities will be successful if it delivers right value and satisfaction to

the target market or buyer. Usually, buyers will choose among a wide range of

marketing activities which bids are considered to provide the most value. Value can

be seen through the dimensions of perceived value itself.

Purchase intention is part of the component behavior in consuming attitude.

According to Kinnear and Taylor (1995: 306), purchase intention is the tendency of

consumers to the stage to make an action before purchase decision is really

implemented. Basically, intention to buy can be defined as the probability when the

buyer intends to purchase the product (Doods, Monroe and Grewal in Smith and

Natesan 1999). Those things being equal, purchase intention is positively related to

the overall perception of the acquisition and transaction value (Yaseen, Mariam

Tahira, Gulzar and Anwar 2011).

The consumer has consumed a product or service, if the product or service has been

decided by the consumer to buy. The decision to buy influenced by value of product

that evaluated. When the benefit is greater than the sacrifice to have it, then the urge

to buy will be higher. Conversely, if the benefits are smaller than sacrifice, then the



buyer will usually refuse to buy and generally switched evaluate other similar

products or services.

Commonly, the consumer buying behavior is often preceded and influenced by a

number of stimuli from the outside their selves, in the form of marketing stimuli and

the environmental stimuli. After that, the stimulus will be processed in accordance

with the characteristics of personal self, before finally taken the purchase decision.

Personal characteristic of consumers that are used to process the stimuli are basically

very complex, and one of them is consumer motivation to buy.

According to Keller (1998: 93), consumer intention is how likely consumers buy a

brand or how likely consumers to switch from one brand to another brand. While

Mittal in Chen, Huang and Chou (2008) stated that the function of the interest of

consumer intention is a function of the product and service quality.

According to Samu in Navarone (2003; 114), an indicator that a product is successful

or not in the market is the extent to which consumer’ growing the intention in

purchasing the product or service.

According to Howard in Bagozzi, Baumgartner, and YI (1989), Intention to buy is

defined as statements relating to plans that reflect the inner of the buyer to purchase a

particular brand within a specific time period.

And also in journal from Lestari (2012) about “Pengaruh Iklan, Brand Trust, dan

Brand Image terhadap minat beli konsumen WiGo 4G Wimax “ (the influences of

ads, brand trust, and brand image towards the purchase intention of consumers), stated

that the impact of the symbol of a product gives consumers the sense in decision

making because the symbols and images are important in advertising and have an

influence in the interest to buy.



2.6.1 FACTORS THAT INFLUENCES THE CUSTOMERS’ PURCHASE

INTENTION

According to Berman and Evans (2002: 202), there are several elements that cause the

consumers to buy a product or service, those are:

1. Stimulus

Stimulation will occur when an area will reach one’s sense acceptance nerve

or it can be called as the sensory receptors.

2. Awareness

To get the attention of one’s consciousness, after reaching one’s senses

reception area of the nerve (sensory receptors), then the next stimulus should

be thrilling sensory nerves and cause an immediate response in the brain, for

example: when a person feels more interested in knowing more about the

activities of an online-forum trading.

3. Looking for the information

A. Information intern: Sourced from the consumer’s memory to choose goods

or services that refracts.

B. External Information: Information involving advertising

C. Ascertain the nature in choosing the option: Consumers in collecting

information related to the characteristics of the choosing an option, after

understanding about that option, consumer usually will decide the goods or

services to be purchased.

D. Alternatives selection: After all the information related to the desired

product has been obtained, then the consumer will move further.



E. Purchase: Purchasing is the stage where the consumer has been through

the options and ready to issue the cash in exchange for goods or services.

In the previous stage, the consumers have to determine the best decision

first among the brand products that have been collected in brain. Besides

the consumer has had the decision and the tendency of a product

independently, there are two factors that help consumers in determine the

purchase intention and after that decision, that is the attitude of others and

unexpected situational factors.

F. The place where to buy: The point of purchase is one of the considerations

in the store and even online where consumers will buy products or

services. A traditional shop or online that has a good image or trustiness

will stimulate consumer to make a transactions, except consumers become

accustomed to buying in the same place.

2.6.2 DIMENSION OF PURCHASE INTENTION

According to Churchill and Iacobucci (2005) explained there are three dimensions in

measuring of purchase intention:

1. Likely.

Consumer plans in buying a product.

2. Definitely Would.

Referring to consumer certainty in a product.

3. Probable.

Referring to the possibility of consumer will buy a product.

2.6 THE CORRELATION BETWEEN PERCEIVED VALUES TO

PURCHASE INTENTION

Previous studies have shown that perceived value positively influenced customer

satisfaction. In other words, higher perceived value can lead to higher customer

satisfaction. Perceived value and customer satisfaction directly and positively



influenced post-purchase intention, where the effect of perceived value was the

largest, followed by that of customer satisfaction. (Ying-Feng Kuo, Chi-Ming Wu,

and Wei-Jaw Deng, 2009).

Beside that, in a journal “the influences of perceived value on consumer purchase

intention” from Hsinkuang, Chien, and Tsai (2011), stated that the higher perceived

value is the higher purchase intention is. Consumer can obtain trustworthy perceived

value through advertising endorser’s recommendation and endorsement and a

company can therefore increase its competiveness. The influence of advertising

endorser on consumers is through an idol or a celebrity to market a product.

Advertising endorser can connect product value by deepening consumers’.

And also Swait and Sweeney (2001) in “consumer perceived value: the development

of a multiple item scale” used logic models to analyze the influence of customer

perceived value on consumer purchase intention in retailing industry and found that

different perceived value customers have different purchase behavior.

2.7 THEORETICAL HYPOTHESIS

This research attempted to investigate the role of values and purchase intentions.

After reviewing the relevant literature, the hypothesis for this study was constricted: “

more ‘recommended seller’ as perceived positive value of www.kaskus.co.id, more

customers purchase intention”



CHAPTER 3 - METHODOLOGY

3.1. TYPE OF STUDY

In this study, the researcher will conduct quantitative method. According to Arikunto

(2006) explained that quantitative research is a study that uses the number at the

beginning of data collection, data interpretation, and the result appearance. And also

Anwar (2007) stated that research emphasizes quantitative analysis on numerical data

that though statistical methods.

Based on the definition above, it can be concluded that quantitative method is one of

researches that based on a measuring instrument so the calculation can be effectively

done.

Beside that, Sugiyono (2009: 5) also revealed that associative research is as follows:

"Associative research is research that aims to determine the relationship between two

or more variables". Which means, the associative research is a study to determine the

relationship between two variables or even more, and the relationship between the

variables in this research will be analyzed using measures of relevant statistics on the

data to test the hypothesis.

In this research, to considering the affect between recommended seller as perceived

value (X) towards purchase intention (Y), the researcher basically will adopt the

SPSS program 21.0 with correlation method.

Figure 3.1. The Associative Correlation

Variable X: Recommended Seller as Perceived Value

Variable Y: Purchase Intention

Variable X Variable Y



3.2. UNIT OF ANALYSIS

According to Hamidi (2005: 75-76) revealed, “the unit of analysis is divided into

three parts, those are:

- Individuals

- Groups

- Objects or Background of social events, for instance: the activities of

individual or groups as a research subject.

According Efferin in “Metode Penelitian untuk Akuntansi” stated about definition of

unit analysis, which is “The unit of analysis is the smallest unit of the desired object

of study by researchers as the classification of data collection "(2004: 55). Whereas

the definition of unit analysis according Uma Sekaran (2006: 248), unit of analyze is

the level of data collection for the analysis of data collected.

From the description above, it can be concluded that unit analysis is an object with

smallest measurement from an objective of research and used as classification in data

collection phase. Unit analysis is the based of data processing phase that used to

achieve an answer from a research.

In this research, unit analysis will be focused to individual, that in consumers of

trading forum of www.Kaskus.co.id. The reason of using this unit analysis is because

the researcher would like to figures the influence level of “recommended seller”,

which is as the perceived value towards purchase intention of potential customers, and

the data sources can be find only from the people who have visited the trading forum

of www.kaskus.co.id

3.3. POPULATION AND SAMPLE

3.3.1. POPULATION

Population is a generalization region consisting of the objects / subjects that have

certain qualities and characteristics that set by the researchers to be studied and then

drawn the research conclusions. (Sugiyono, 2009:61).



In this research, the population that will become the object of research is the

community of www.kaskus.co.id who have experienced in purchasing a mobile

phone.

3.3.3. SAMPLING TECHNIQUE

There are two techniques in regarding the sample of research. Those are probability

and non-probability. Probability technique is sampling technique that provides equal

opportunities to every element or member of the population to be selected as sample,

otherwise non-probability technique, which selected the population by not giving the

same opportunities to members of the population. (Hikmat, 2011: 62)

Based on the definition above, the researcher chooses the probability technique. And

also it will be focused on the simple random sampling, which it is the part of

probability technique. According to Hikmat (2011: 63), simple random sampling is

choosing the sample randomly without regard to existing strata in the population, and

basically it is for homogeny population.

3.3.4. SAMPLE SIZE

Figure 3.2. The calculation of sample size

In this research, the sampling sizes basically there are 84 people in minimum required

(www.danielsoper.com) who have experienced purchasing in hand phone and PDA

from www.kaskus.co.id trading-forum. However, to avoid the errors in some samples,

the researcher will makes the sample size to 100 people.



Where µ is the mean, σ is the standard deviation, and erf is the error function.

3.4. DATA COLLECTING TECHNIQUE

The primary data source is a source of research data obtained directly from the

original source (not through an intermediary medium). Specifically, in primary data,

the researcher will be collected the questioner from the samples to help the researcher

solve the research problem. Basically, questionnaire is the media used for data

collection by making writing and submitted questions to the respondents, which are

the samples of this research will be the customers of www.kaskus.com who have

experienced purchasing in Hand phone and PDA category of www.kaskus.co.id

trading forum.

The secondary data source is a source of research data obtained from the documentary

studies and also library research as reference.

3.4.1 RESEARCH PLACE AND TIME

This research will be placed on www.kaskus.co.id and the time of this research will

be held from May 2013 to the end of June 2013.



3.5. DATA ANALYSIS TECHNIQUE

3.5.1. VALIDITY AND RELIABILITY TEST

Technically, to test the validity in this research, the researcher will use the Pearson

correlation. Which is by calculating the correlation coefficient between each of the

values in question by the total number of the question number

(http://www.statstutor.ac.uk)

Further correlation coefficient “r” obtained could still be tasted significance using “t”

test or compare it with “r: table. And when t count bigger than “t” table or “r”

counting bigger than the “r” label, then the questioner is a valid.

In the reliability test, the researcher will be conducted a Cronbach Alpha method.

According to Ghozali (2004), instrument could be said reliable if the cronbach alpha

score is greater than 0,6. Cronbach Alpha technic is an interpretation of reliability

coefficient that focused on intercorrelation questions. The formula of Cronbach Alpha

is:

Alpha = ( )(1- )

Explanation:

K = total item/test questions

S = total of the whole questions

St = Total score’s variance

St2 = Interpretation variances toward test questions

And for the used variances formula is:

S2 =

3.5.2. CONCEPT OPERATIONALIZATION

Table 3.1. Concept Operation

Variable Dimension Indicator Scale



Recommended Seller as Perceived Value

(Sweeney and Soutar in Aakouk, 2006)

Emotional 1. Trust towards

online trading

forum.

2. Online trading

forum is very

enjoyable.

Likert

Social 1. The influence

of reference

group

2. Online trading

forum helps to

adjust to the

social

environment.

Likert

Quality 1.

Communication

is going so well

on online trading

forum

2. Clear

information

about the seller

identity.

Likert

Price 1. Competitive

number of price.

2.The prices are

comparable to

what is delivered.

Likert

Purchase

Intention

(Churchill and Iacobucci,

Likely 1. Consumer

plans in buying a

product.

2. Consumer

Likert



2005)

interested in

buying a product.

Definitely

Would

1.Reffering to

consumer

certainty in a

product.

2. Seriousness to

consider

purchasing a

product or

service on an

online trading

forum

Likert

Probable 1. Referring to

the possibility of

consumer will

buy a product

2.The possibility

to choose

specific online

trading forum as

the place to

spending money

than others in the

future.

Likert

3.5.4. ANALYSIS OF CORRELATION

Pearson r correlation is used to determine the relationship of the two variables. This

method requires the normal data distribution.

The formula of Pearson r correlation is:



Rxy =

Explanation:

R = Pearson r correlation coefficient

N = Total Sample

3.5.5 FACTOR ANALYSIS

The purpose of using the factor analysis in this research due to the dimensions of

variable X or the independent variable in this research cannot be measured directly,

those are: emotional, social, quality and price.

Factor analysis is an analysis that aims to find the main factors that most influence to

dependent variable of a series of tests conducted on a set of independent variables as

factors. Basically, factor analysis is one of the analytical dependence

(interdependence) between variables. The basic principle of factor analysis is to

extract a number of factors together or common factor of the cluster of origin

variables X1, X2 and so.

3.5.5.1 STEPS IN FACTOR ANALYSIS

According to Khelifa (2010) in www.slashdocs.com, factor analysis usually proceeds

in four steps:

1st Step: the correlation matrix for all variables is computed

2nd Step: Factor extraction

3rd Step: Factor rotation

4th Step: Make final decisions about the number of underlying factors



Chapter 4 Results and Discussion

4.1 KASKUS BACKGROUND

Kaskus is a forum for discussion and Indonesia's largest trading. Usually, Kaskus is

the home for anyone to find everything what they need or looking for. Nowadays,

millions of people uses Kaskus to search for information, knowledge, join the new

community, to buying and selling all types of goods and services at the best price.

Technically, Kaskus divided into two parts, which are: Lounge Forum & FJB or

Online trading forum of www.kaskus.co.id. Lounge forum is the place to discuss all

matters. FJB is a platform to transact the sale and purchase all kinds of products and

even services. Kaskus lounge forum can be called as discussion forums, and it often

post information that cannot be found in other news portals. Beside that, Kaskus

trading forum proven to be the most complete platform to find all kinds of products

and services.

Generally, on Kaskus platform also created jargon and buzzwords that eventually

became culturally typical Internet users in Indonesia. Some of them are Skipper,

Pertamax, Rekber, COD, and many other terms.

4.1.2 KASKUS HISTORY

KASKUS established on 6 November 1999 by three young men from Indonesia who

is currently studying in Seattle, USA. Firstly, Andrew Dervish, Ronald, and Budi

make Kaskus to fulfill their coursework. Kaskus itself aims to cure homesickness

Indonesian students abroad to Indonesia through the Indonesian news translated. In

2008, Andrew Dervish and Ken Dean Lawadinata decided to manage Kaskus

professionally. Kaskus sites, personnel and related infrastructure eventually brought

to Indonesia this year.



In Indonesia, the first Kaskus office located in Mangga Besar area, who assisted with

2 professionals. Under the auspices of PT. Darta Media Indonesia, the first step is

conducted a rebranding of Kaskus. Since 2009, KASKUS become an important player

in the online realm Indonesia. Kaskus has got many awards including "The Best

Innovation in Marketing" and "The Best Market Driving Company" by Marketing

Magazine, and "The Greatest Brand of the Decade" (2009-2010) by Mark Plus Inc.

Kaskus is proud to be ranked first in the category of community sites, and the number

one local site in Indonesia.

In 2011, Kaskus begin its partnership with Global Digital Prima, an Indonesian

company that focuses on developing local content and digital industry in Indonesia.

The partnership encourages to growth Kaskus greater, both in terms of infrastructure,

professional and business networking sites in an effort to become the number 1 in

Indonesia as well as a global player in the online world. Compensate for expansion,

Kaskus was moving its main office to Palma Tower in Kuningan, Jakarta and named

it as Kaskus Playground.

As a company because of its large, Kaskus always strive to continue to improve

comfort Kaskuser or Kaskus registered-member. Dated May 26, 2012 to witness

Kaskus trip where Kaskus re-use addresses and kaskus.co.id kaskus.com official

website, this is done to re-invigorate Kaskus image as a global visionary site but still

have Indonesian identity.

In 2012, Kaskus also launched a new version 2.0 that occurred Kaskus improvement

on the display, navigation, search feature, trading online forum (FJB), as well as

adding a server to accommodate the needs of members Kaskus, which has reached

more than 4.5 million members.

4.1.3 ONLINE TRADING FORUM OF KASKUS

Online trading forum is a website that provides an online meeting place or platform

between the seller and buyer. Kaskus never pull any of transaction costs and

installation information about the transactions of selling. Kaskus apply the donation



system, which is by paying a membership that has been determined, it will have some

advantages, such as free access without banners and faster than ordinary members.

The advantages like being able to use the quick reply, greater capacity inbox, the user

also can see provide Good Reputation Points (GRP) or Bad Reputation Point (BRP),

greater access Kaskus, gain access to special forums donors.

For sellers to sell items with registration to Kaskus.us/register.php and offering

appropriate product category that has been provided by www.kaskus.co.id. The way

of transaction, in this case Kaskus totally not participate. Prospective buyers will

usually make a contact to the seller, negotiating and how payment is discussed in

private transactions between sellers and buyers. Buyers usually look for sellers who

have a good reputation of high although this is not a recommended seller. Since the

number of scams, www.kaskus.co.id not guarantee the quality of goods or services or

honesty seller in the transaction. When it comes to cases of fraud then the buyer can

report the case to the "Pos ronda FJB". Then, Kaskus will make a list of the seller

with a bad reputation.

4.2 RESEARCH RESULT

Actually, based on the counting the number of samples size in chapter 3 that used the

calculation of www.danielsoper.com revealed that minimal sample should be obtained

in this research were 84 respondents to prove the influences of recommended seller as

perceived value towards purchase intention of Kaskus’ community. As already

explained earlier that this research is better conducted through the Internet or online,

because the population of this research was selected from registered members on

www.kaskus.co.id.

Therefore, it is not difficult for the researcher to found out the registered-members,

because the researcher seeks clarification within the questionnaire of respondents

whether they are registered member or not. Researcher has received 109 respondents,

who filled out the questionnaires. From 109 received-respondents, the researcher only

took 100 respondents in accordance with the sample criteria in this research.

Researcher has to take 9 respondents out, because the sample is not in accordance

with the criteria.



Actually, 109 respondents in this research obtained for 9 days, started from June 10th,

2013 to June 19th 2013 at 5:16:42. And the third day (June 13th 2013) was the day

where the researcher got a lot of respondents, which were 23 respondents.

In data analysis the researcher basically will use the Pearson correlation to get the

answer of first research question and also factor analysis to answer the second

research question.

4.2.1 CHARACTERISTIC OF RESPONDENTS

a. Sex

Table 4.1. Total of Respondents sex

Sex Frequency Percent Valid Percent Cumulative

Percent

Valid Men 71 71.0 71.0 71.0 Women 29 29.0 29.0 100.0 Total 100 100.0 100.0

In conducting this research, the researcher have got 100 respondents, previously in

chapter 3 the researcher explained that this research only need 100 respondents to

completed this research. The composition of the 100 respondents, who had obtained,

stated that 71 people (71%) are male respondents, 29 people (29%) are female, and

also there is a respondent did not fill the sex column. Based on this data, it showed

that the numbers of men are more than women in terms of using or visiting

www.kaskus.co.id.

Beside the table 4.1 above, it still has more explanations why men are dominant as

users of www.kaskus.co.id. Firstly, according to the social news site, which are Digg,

Reddit, and Slashdot in Pindom (2009) that significantly there is more male users than

female. And also in book of Enhancing enterprise competitiveness: (marketing,

people, IT and entrepreneurship) authored by Gupta,Jain and Dhar (2007: 160) stated

that from the population of 125 million that provided a solid base of an estimated 4.8



million experienced online shoppers. Amongst, the male are 52% and 48% are

female.

Another reason that men are the most on www.kaskus.co.id because the history of

www.kaskus.co.id itself. Which www.kaskus.co.id started their platform with the

content about negative smell such as: pornographic and underground discussion.

Which is on www.oprah.com revealed that men often consume more and more porn.

The last reason is about psychological factor; on www.she-conomy.com (2009)

revealed statistically 79% have to try the product before making a transaction. It

means that women are more love to shopping, if they can make physical contact to the

objects or goods that will be purchased.

b. Age

Table 4.2 Ages of Respondents Age

Frequency Percent Valid Percent Cumulative Percent

Valid

> 26 Years Old 31 31.0 31.0 31.0 20 - 22 Years Old 31 31.0 31.0 62.0 23 - 25 Years Old 25 25.0 25.0 87.0 17 - 19 Years Old 13 13.0 13.0 100.0 Total 100 100.0 100.0

From the 100 respondents obtained, shows that the age of 20-22 is the most dominant that is 31% or 31 respondents, and the second stage is the respondents age over 26 that is 30% or 30 respondents, third ranked is the average age of 23 - 25 is 25% or 25 respondents, and the last ranked is the age of 17-19 is 14% or 14 respondents. Based on the results from the table, it can be said that the age of 20-22 and more than 26 years old are the most-visited of www.kaskus.co.id Based on the output of table 4.2 above, that there is no significant mistake, which

is according to “Life Online” which has been conducting a research on Europe to

know the average age of Internet users started from 2005 to 2011, and they

revealed that 26-‐34 years old is more dominant than people in 17-‐25 years old.

Not only that, also the data from www.pewinternet.com in 2010 revealed that



the most dominant internet user, especially social media are people in 23-‐35

years old.

c. Occupation

Based on the data collected from 100 respondents, shows the top three rankings, those

are: students, privates’ employees and entrepreneurs. Which the total numbers of

students are 45 respondents (45%), there are 17 respondents (17%) of private

employees, and entrepreneurs are 13 respondents (13%). It can be concluded that the

average buyers have an experienced in buying a hand phone on trading forum of

www.kaskus.co.id are students.

Table 4.3 Occupations of Respondents

Occupations Frequency Percent Valid

Percent Cumulative

Percent

Valid

Students 45 45.0 45.0 45.0 Private Employees 17 17.0 17.0 62.0 Entrepreneurs 13 13.0 13.0 75.0 Employee 6 6.0 6.0 81.0 Civic Servants 3 3.0 3.0 84.0 Broker 2 2.0 2.0 86.0 Teacher 2 2.0 2.0 88.0 Security 2 2.0 2.0 90.0 Assistant Manager 1 1.0 1.0 91.0 Creative Designer 1 1.0 1.0 92.0 Doctor 1 1.0 1.0 93.0 Freelance 1 1.0 1.0 94.0 IT 1 1.0 1.0 95.0 Junior Trader 1 1.0 1.0 96.0 Musician 1 1.0 1.0 97.0 Unemployed 1 1.0 1.0 98.0 Driver 1 1.0 1.0 99.0 Store Manager 1 1.0 1.0 100.0 Total 100 100.0 100.0

d. Duration as Registered Member



Table 4.4. Duration as registered member of respondents

Frequency Percent Valid Percent Cumulative

Percent

Valid

> 2 Years old 61 61.0 61.0 61.0

2 Years old 39 39.0 39.0 100.0

100 100.0 100.0

Based the table above, the researcher can be concluded that most of respondents has

been a registered member for more than 2 years, that is 61 respondents (61%). And

the rest of respondents are has been experienced as Kaskus registered members are 39

respondents.

e. Buying Frequency

Table 4.5 Buying Frequencies


Valid

1 52 52.0 52.0 52.0 2 25 25.0 25.0 77.0 3 7 7.0 7.0 84.0 4 4 4.0 4.0 88.0 5 4 4.0 4.0 92.0 6 3 3.0 3.0 95.0 > 10 2 2.0 2.0 97.0 >30 1 1.0 1.0 98.0 10 1 1.0 1.0 99.0 17 1 1.0 1.0 100.0 Total 100 100.0 100.0

Based on the table of the frequency of purchase from the respondent above, it can be

concluded that most respondents doing single transaction in the purchase of mobile

phones on trading forum of www.kaskus.co.id, that is 52 respondents (52%) or it can

be said more than half of the respondents were obtained. And also surprised that there

is a respondent has bought a hand phone more than 30 times.



4.2.2 DESCRIPTIVE EACH ITEM IN VARIABLE X

Basically, in this research the recommended seller as perceived value is the variable X

or independent variable. Theoretically, the variable X or independent in this research

has four dimensions to be tested. Those are: Emotional, Social, Quality and Price

(Sweeney and Soutar in Aakouk (2006). To find out the influence of this variable X

towards variable Y, the researcher has created two questions in minimum for each

explained dimensions.

1. Emotional Dimensions

In this dimension basically there are three items or questions on the questioner

and the result from the data analysis processing are:

- First item of emotional dimension

Table 4.6 Variable X items descriptive

PV1emotional Frequency Percent Valid Percent Cumulative

Percent

Valid

1.0 2 2.0 2.0 2.0 2.0 10 10.0 10.0 12.0 3.0 21 21.0 21.0 33.0 4.0 51 51.0 51.0 84.0 5.0 16 16.0 16.0 100.0

Total 100 100.0 100.0

Based on the table above, which the question is Saya merasakan nilai atau pesan

positif untuk membeli secara online sebuah produk yang dimaksud oleh penjual di

forum jual beli Kaskus (I’ve felt the positive value or message to buy a goods in

online way, which is intended by the seller on the trading forum of Kaskus) can be

concluded that Kaskus’ user said they are agreed and felt about positive value or

message from the seller.

- Second item of emotional dimension

The question of the table 4.7 is Saya memiliki rasa percaya untuk melakukan

transaksi, seperti membeli sebuah hand phone di forum jual beli kaskus (I do believe



in making a transactions, such as buy a hand phone in the trading forum of kaskus),

which the result shown us that most respondent or 40% respondents more said it

neutral and second percentage (34%) is disagreed about this item.



Percent

Valid

2.0 16 16.0 16.0 16.0 3.0 34 34.0 34.0 50.0 4.0 40 40.0 40.0 90.0 5.0 10 10.0 10.0 100.0 Total 100 100.0 100.0

- Third item of emotional dimension



Percent

Valid

1.0 2 2.0 2.0 2.0 2.0 15 15.0 15.0 17.0 3.0 30 30.0 30.0 47.0 4.0 42 42.0 42.0 89.0 5.0 11 11.0 11.0 100.0 Total 100 100.0 100.0

Based on the table above, which the question is Forum Jual beli Kaskus membuat

saya nyaman untuk pembelian sebuah hand phone secara online (Kaskus’ trading

forum makes me feel the comfortable atmospheres in purchasing an hand phone

through online) can be concluded that there are 43% of respondent as registered-

member said they are agreed and feel the comfortable atmospheres in buying a hand

phone through online, even though 33% respondents revealed they are disagreed

about this item.



2. Social Dimension Item

In this dimension basically there are two items or questions on the questioner and the

result from the data analysis processing are:

- First item of social dimension


PV4social Frequency Percent Valid Percent Cumulative

Percent

Valid

1.0 1 1.0 1.0 1.0 2.0 4 4.0 4.0 5.0 3.0 18 18.0 18.0 23.0 4.0 44 44.0 44.0 67.0 5.0 33 33.0 33.0 100.0 Total 100 100.0 100.0

From 100 respondents revealed that 44% respondents are agreed and 30% of them are

strongly agreed about this item, which the question is Saya mencari informasi tentang

sebuah produk, terutama hand phone di forum jual beli kaskus (I am looking for the

information about goods, particularly an hand phone in the trading forum of Kaskus).

So it can be concluded that most of them looking for the information about a hand

phone on trading forum of www.kaskus.co.id and it might be the information about

the prices or specification of the hand phone itself.

- Second item of social dimension

Table 4.10 Variable X item descriptive

PV5social Frequency Percent Valid Percent Cumulative

Percent

Valid

2.0 7 7.0 7.0 7.0 3.0 13 13.0 13.0 20.0 4.0 39 39.0 39.0 59.0 5.0 41 41.0 41.0 100.0



Total 100 100.0 100.0 The question of the table above is Komunitas dari Kaskus membantu saya percaya

untuk mempertibangkan membeli sebuah produk terutama hand phone secara online

(Kaskus’ community helps me building the trust in consider buy a goods, especially

hand phone in online way). It shown us that almost half of respondents said strongly

agreed (41% respondents) and 39% of respondents are agreed. So it can be concluded

that the community on www.kaskus.co.id have a possibility to help the customer build

a trust and make positive consideration when the customers will buy a hand phone.

3. Quality Dimension Items



- First item of quality dimension


PV6quality Frequency Percent Valid Percent Cumulative

Percent

Valid

1.0 2 2.0 2.0 2.0 2.0 16 16.0 16.0 18.0 3.0 27 27.0 27.0 45.0 4.0 36 36.0 36.0 81.0 5.0 19 19.0 19.0 100.0 Total 100 100.0 100.0

Based in the table above, which the question is Komunikasi antara penjual dan

pembeli di forum jual beli kaskus sangat baik (The communication level between the

seller and buyer in trading forum of Kaskus is going well). Most respondents’ chose

agreed that is 36%, and 27% respondents stand in neutral. Although some of the

respondents said strongly disagreed about the communication on www.kaskus.co.id is

going well.

This is possible because the seller is also being active in providing information about

the products’ knowledgement. Whereas according to Prakash (2008) “purpose of



online platform is to inform your prospects, customers and visitors interested to know

more about your company, about you, and your products among others”. So it can be

concluded that if the company website or individual online platform provide clearly

information to the target market, it will make the communication in terms of making

transaction going well.

- Second item of quality dimension

Table 4.12 Variable X items descriptive PV7quality


Valid

1.0 15 15.0 15.0 15.0 2.0 26 26.0 26.0 41.0 3.0 33 33.0 33.0 74.0 4.0 18 18.0 18.0 92.0 5.0 8 8.0 8.0 100.0 Total 100 100.0 100.0

The question of this item is Informasi tentang identitas penjual di forum jual beli

kaskus jelas (The identity of the seller on www.kaskus.co.id trading forum is cleared).

The result from data analysis that conducted by the researcher stated that most

respondents stand in neutral, which is 33% or 33 of 100 out respondents, and 26 of

100 out respondents said disagreed and also the total of strongly disagreed is more

than strongly agreed. It can be concluded, it happened because most the sellers on

www.kaskus.co.id using pseudonym as their user name or display name on their

online thread.

4. Price Dimension Items



After conducted data analysis, in this item there is a respondents did not make a

clearly answer, it revealed from the data processing table bottom. As the conclusion

about the eighth item from price dimension, which the question is Harga hand phone

di forum jual beli kaskus lebih baik dari pada online-shopping lain (Kaskus’ trading



forum has better price than other online-shopping in terms of hand phone), that it can

be said most respondent are agreed about the price on www.kaskus.co.id is more

inexpensive than other online shopping. Where half of respondents or 56%

respondents revealed they are agreed about that and 24% respondents are strongly

agreed.

- First item of price dimension Table 4.13 Variable X items descriptive

PV8price Frequency Percent Valid Percent Cumulative

Percent

Valid

2.0 7 7.0 7.1 7.1 3.0 12 12.0 12.1 19.2 4.0 56 56.0 56.6 75.8 5.0 24 24.0 24.2 100.0 Total 99 99.0 100.0

Missing System 1 1.0 Total 100 100.0

- Second item of Price dimension



Percent

Valid

2.0 3 3.0 3.0 3.0 3.0 11 11.0 11.0 14.0 4.0 33 33.0 33.0 47.0 5.0 53 53.0 53.0 100.0 Total 100 100.0 100.0

Basically, the researcher put Harga hand phone di forum jual beli kaskus lebih

kompetitif dibandingkan dengan harga toko (The hand phone prices on the trading

forum of Kaskus is more competitive than the shops) on the questioner as item of

price dimension. After conducted data analysis processing. 53% respondents or half

of respondents revealed that they are strongly agreed that the price on

www.kaskus.co.id is more inexpensive than traditional way or shop.



- Third item of Price dimension

The distance of number between agreed scale and neutral scale from the table above

is quite short, which is 44 (44%) respondents’ feet in agreed and 36 (36%)

respondents said neutral. Where is the question of this item is Harga yang ditawarkan

oleh penjual sesuai dengan manfaat yang ditawarkan (Seller offers the price in

accordance with the benefit offered)



Percent

Valid

2.0 5 5.0 5.0 5.0 3.0 36 36.0 36.0 41.0 4.0 44 44.0 44.0 85.0 5.0 15 15.0 15.0 100.0 Total 100 100.0 100.0

4.2.3 DESCRIPTIVE EACH ITEM IN VARIABLE Y

Basically, in this research the purchase intention is the variable y or dependent

variable. Theoretically, the variable Y or dependent in this research has 3 dimensions

to be tested. Those are: Likely, Definitely would, and Probable. Actually, the

researcher has created two questions in minimum for each explained dimensions.

1. Likely Dimension Items

Generally, there are three items from this dimension to be tested to respondents on

www.kaskus.co.id and specifically, these items has been spreading in Hand phone and

PDA, those are:

- First item of Likely dimension

The question on the questioner of this item is Saya berencana untuk membeli sebuah

hand phone di forum jual beli Kaskus (I am planning to buy a hand phone on

www.kaskus.co.id trading forum). Based on the table 4.16 below it can be concluded



that 40 of 100 out or 40 respondents were agreed that they have a planning to buy a

hand phone on Kaskus’ trading forum, and quarter of respondents or 25% respondents

stand in neutral, it happened might be because the respondents do not need to buy a

hand phone on www.kaskus.co.id in the near future. There is only 3 of 100 out

respondents said that they are strongly disagreed, it might they have not good

experienced when they made the first transaction on Kaskus’ trading forum.

Table 4.16 Variable Y item descriptive

PI1likely Frequency Percent Valid Percent Cumulative

Percent

Valid

1.0 3 3.0 3.0 3.0 2.0 15 15.0 15.0 18.0 3.0 25 25.0 25.0 43.0 4.0 40 40.0 40.0 83.0 5.0 17 17.0 17.0 100.0 Total 100 100.0 100.0

- Second item of Likely dimension



Percent

Valid

1.0 5 5.0 5.0 5.0 2.0 7 7.0 7.0 12.0 3.0 13 13.0 13.0 25.0 4.0 45 45.0 45.0 70.0 5.0 30 30.0 30.0 100.0 Total 100 100.0 100.0

After conducted data analysis processing using the SPSS 21.0 for the question of

second item from the likey dimension, which the question is Recommended seller di

thread penjual hand phone menarik perhatian saya (Recommended seller in the thread

of seller’s phone caught my attention). And the results are most respondents attracted

by the recommended seller in terms of intention to buy a hand phone. 45% or 45 of

100 out respondents said agreed, more than quarter of respondents said strongly

agreed, and 12 of 100 out respondents revealed that recommended seller on the



sellers’ thread do not change their attitudes.

- Third item of Likely dimension

The question for the table 4.18 below is Penyampaian pesan yang baik membuat

saya tertarik untuk membeli handphone di forum jual beli kaskus (Good

communication in terms of sending a messages make me interested to purchase hand

phone on www.kaskus.co.id trading forum). From the table 4.18 the researcher can

make a conclusion that most respondents which is 47% are agreed about the good

communication can increase their intention towards a hand phone. 33% or 33 of 100

out respondents stand in strongly agreed and 12 of 100 out respondents are neutral.



Percent

Valid

1.0 1 1.0 1.0 1.0 2.0 7 7.0 7.0 8.0 3.0 12 12.0 12.0 20.0 4.0 47 47.0 47.0 67.0 5.0 33 33.0 33.0 100.0 Total 100 100.0 100.0

2. Definitely would dimension items

Generally, there are three items from this dimension to be tested to respondents on

www.kaskus.co.id and specifically, these items has been spreading in Hand phone and

PDA, those are:

- First item of Definitely Would dimension

Based on the table 4.19 below, 55% or 55 of 100 out respondents revealed clearly

information is one of the factor can increase the purchase intention. And there are

only 8 of 100 out respondents said they are not agreed with that. Which the question

of this item is Pengarahan ke sebuah produk yang tidak bertele-tele membuat saya



tertarik. (Straight to a product clearly makes me interested).


PI4DW Frequency Percent Valid Percent Cumulative

Percent

Valid

1.0 1 1.0 1.0 1.0 2.0 7 7.0 7.0 8.0 3.0 13 13.0 13.0 21.0 4.0 55 55.0 55.0 76.0 5.0 24 24.0 24.0 100.0 Total 100 100.0 100.0

- Second item of Definitely Would dimension

The question of this item is Saya memiliki keseriusan untuk membeli sebuah

handphone atau produk di forum jual beli Kaskus (I have seriousness to buy a hand

phone or product on Kaskus’ trading forum). After the data processing in descriptive,

the researcher can be concluded that most registered member of www.kaskus.co.id

has the level of serious in buying a hand phone, which is the number from the table

4.21 below shown 52% respondents said agreed and 19% strongly agreed.


PI5DW Frequency Percent Valid Percent Cumulative

Percent

Valid

1.0 3 3.0 3.0 3.0 2.0 9 9.0 9.0 12.0 3.0 17 17.0 17.0 29.0 4.0 52 52.0 52.0 81.0 5.0 19 19.0 19.0 100.0 Total 100 100.0 100.0



4. Probable Dimension Items

- First item of Probable dimensions From 100 respondents of Kaskus registered member, 47% or 47 of 100 out

respondents revealed they are agreed that they have considering to make a transaction

on www.kaskus.co.id, And 30 of 100 out respondents are strongly agreed about that.

Even though 23 of 100 out respondents are most neutral and disagreed or strongly

disagreed. The question of this item on the questioner is Saya mempertimbangkan

untuk membeli handphone di forum jual beli kaskus (I am considering to buy a hand

phone on Kaskus’ trading forum).


PI6probable Frequency Percent Valid Percent Cumulative

Percent

Valid

1.0 4 4.0 4.0 4.0 2.0 8 8.0 8.0 12.0 3.0 11 11.0 11.0 23.0 4.0 47 47.0 47.0 70.0 5.0 30 30.0 30.0 100.0 Total 100 100.0 100.0

- Second item of Probable dimension



Percent

Valid

1.0 2 2.0 2.0 2.0 2.0 15 15.0 15.0 17.0 3.0 22 22.0 22.0 39.0 4.0 36 36.0 36.0 75.0 5.0 25 25.0 25.0 100.0 Total 100 100.0 100.0

Basically, the question for this item is Saya memilih forum jual beli Kaskus dalam

setiap pembelian hand phone (I chose the kaskus’ trading forum in every purchasing



hand phone) and the result after the data processing shown that 41 of 100 out

respondents revealed they choose www.kaskus.co.id to buy a hand phone. It might

be because they are Kaskus registered members, which is they should be have well

understanding about the Kaskus atmosphere. However, 22% or 22 of 100 out

respondents are more neutral about this case.

- Third item of Probable dimension

38% or 38 of 100 out respondets which is they are Kaskus registered members said

agreed and 29% or 29 of 100 out respondents stand in strongly agreed that they make

good suggestion to others about buying a hand phone on www.kaskus.co.id. Which

the question of this is Saya menyarankan kepada orang lain untuk membeli sebuah

hand phone di forum jual beli Kaskus (I give recommendation to others to buy a hand

phone on kaskus’ trading forum). However, still 23% or 23 of 100 out respondents

said they are neutral and 10 of 100 out respondents did not take it seriously.



Percent

Valid

1.0 2 2.0 2.0 2.0 2.0 8 8.0 8.0 10.0 3.0 23 23.0 23.0 33.0 4.0 38 38.0 38.0 71.0 5.0 29 29.0 29.0 100.0 Total 100 100.0 100.0

4.3 VALIDITY AND RELIABILITY TEST

Before to the next stage of analysis, in this data processing researcher has to examine

that the data are valid and reliable.

4.3.1 VALIDITY TEST

The validity test purpose is to show the size the exact measures what will be

measured. So this research can say the higher the validity of a test tool, the test

tool is increasingly on the target, or show what it should be measured.



a. Validity test of Variable X

Table 4.24. Validity of Variable X

Item-Total Statistics Scale Mean if

Item Deleted Scale

Variance if Item Deleted

Corrected Item-Total Correlation

Squared Multiple

Correlation

Cronbach's Alpha if

Item Deleted 1. PV1 33.860 32.344 .553 .409 .865 2. PV2 33.990 31.707 .701 .612 .854 3. PV3 34.020 31.091 .714 .620 .852 4. PV4 33.470 33.686 .485 .311 .870 5. PV5 33.470 32.292 .563 .453 .864 6. PV6 33.880 30.470 .723 .671 .851 7. PV7 34.630 30.175 .648 .580 .858 8. PV8 33.540 33.645 .529 .544 .867 9. PV9 33.200 34.949 .367 .580 .878 10. PV10 33.800 32.606 .692 .593 .856

Based on the above data all the data obtained in the variable x can be said a valid data,

because the results of the corrected item-total correlation (r Count) greater than "r

table"

Hypothesis

H0 = the data are normally valid

Ha = the data are not normally valid

Decision-making

r Table r Count, Ho accepted, Ha rejected

r Table < r Count, Ho rejected, Ha accepted

Result

r Table = 0.17

Because t Table < r Count, so the Ho are accepted. So it can be concluded that the

data of variable X are valid.



b. Validity Test of Purchase Intention

Table 4.25 Validity of Variable Y Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if

Item Deleted

Corrected Item-Total

Correlation

Squared Multiple

Correlation

Cronbach's Alpha if Item

Deleted 1. PI1 27.059 29.284 .698 .591 .880 2. PI2 26.657 29.812 .648 .516 .885 3. PI3 26.529 31.083 .625 .531 .887 4. PI4 26.588 31.314 .665 .561 .884 5. PI5 26.843 29.044 .797 .709 .871 6. PI6 26.657 29.851 .666 .555 .884 7. PI7 26.951 29.413 .677 .568 .883 8. PI8 26.765 30.657 .649 .487 .885

Same as the variable X, the variable Y also valid, because the results of the corrected

item-total correlation (r Count) greater than "r table" thou.

Hypothesis

H0 = the data are normally valid

Ha = the data are not normally valid

Decision-making

r Table r Count, Ho accepted, Ha rejected

r Table < r Count, Ho rejected, Ha accepted

Result

r Table = 0.17

Because t Table < r Count, so the Ho are accepted. So it can be concluded that the

data of variable Y are valid.

4.3.2 REALIBILITY TEST

Reliability is a measure of internal consistency of the indicators which show the

degree to which the produces latent constructs or the common latent. High reliability

provides the basis for the level of confidence that each indicator is consistent in its

measurement. Boundary value reliability by using Cronbach’s Alpha is usually

accepted is 0.600 (Malhotra 2005)



a. Reliability Test of Perceived Value

Table 4.26 Reliability Statistics of Perceived Value Cronbach's

Alpha Cronbach's

Alpha Based on Standardized

Items

N of Items

.874 .875 10

Based on the table above, it can be concluded that results of the table is quite

satisfactory. The number in table 4.1 above has been in the standard number of

Cronbach’s Alpha, which has been determined that is above .600. So all the

dimensions in perceived value of this research is reliable.

b. Reliability Test of Purchase Intention

Table 4.27 Reliability Statistics of Purchase Intention

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items

N of Items

.896 .897 8

The result of the table above is also satisfactory. The number in the table of purchase

Intention as variable Y has been in the standard number of Cronbach’s Alpha, which

has been determined that is above .600. So it can be concluded that all the dimensions

of this variable is reliable.

4.4 NORMALITY TEST

Generally, normality test is a test tool that is used to determine whether the data is

spread follow a normal distribution or not.

4.4.1 NORMALITY TEST OF PERCEIVED VALUE (Variable X)

In the normality test, this research are using 0.05 alpha (standard error) and the result

of normality test from the first population are shown below:



Table 4.28. Tests of Normality of Variable X

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Perceived

Value

.080 100 .117 .978 100 .091

a. Lilliefors Significance Correction

Based on the table above, it shown that the significance from Kolmogorov-Smirnov

row is 0.117

Hypothesis

H0 = the data are normally distributed

Ha = the data are not normally distributed

Decision-making

Sig , Ho accepted, Ha rejected

Sig < , Ho rejected, Ha accepted

Result

Sig = 0.117

Because the Sig > , so the Ho are accepted. So it can be concluded that the data are

normally distributed.

Figure 4.1. Perceived Value Plot Output



Based on the figure above, it shows the data distribution from researcher to

respondents can be said that is quite good distribution, because the normal QQ plot of

the results from the previous data prove that the distribution of the points on the plot

is a straight-line.

4.4.2 NORMALITY TEST OF PURCHASE INTENTION (Variable Y)

After concluding that the population from the “before” data are normally distributed,

the next step is to make sure that the data from the “after” population are normally

distributed. The result of the “after” population normality test are shown below:

Table 4.29 Tests of Normality of Variable Y Output

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Purchase

Intention

.095 100 .127 .960 100 .014

a. Lilliefors Significance Correction

Based on the table above, it’s shown that the significance from Kolmogorov-Smirnov

row is 0.127

Hypothesis

H0 = the data are normally distributed

Ha = the data are not normally distributed

Decision-making

Sig , Ho accepted, Ha rejected

Sig < , Ho rejected, Ha accepted

Result

Sig = 0.127

Because the Sig = , so the Ho are accepted. So it can be concluded that the data are

normally distributed.



Figure 4.2 Purchase Intention Normality Output

Based on the figure above, it shows the distribution of the data before can be said as a

good distribution, because the normal QQ plot of the results from the “before” data

prove that the distribution of the points on the plot is a straight- line.

After it shown that both data are normally distributed, the next steps from this

processing phase are to test whether both data have a different variance by using

Correlations test of variable X towards Y.

4.5 CORRELATION TEST OF VARIABLE Y TOWARDS VARIABLE Y

After passed the test of normality, then the research will be continued in order to

measuring the strong relationship between the perceived values and the variable of

purchase intention, after an examination of the correlation using SPSS 21.0 software,

it was found out the following of output:

Table 4.30. Table of Correlations output Correlations

Purchase Intention

Perceived Value

Pearson Correlation

Purchase intention 1.000 .826 Perceived Value .826 1.000

Sig. (1-tailed) Purchase Intention . .000 Perceived Value .000 .

N Purchase Intention 100 100 Perceived Value 100 100

Source: Data processing using SPSS 21.0 for mac



From the above table, it will be explained using the following hypotheses:

Ho = There is a significant relationship between perceived value with purchase

intention

Ha = There is no significant relationship between perceived value with purchase

intention

Basic Decision Making

Sig <Alpha, so there is a relationship between perceived values with purchase

intention

Sig> Alpha, so there is no relationship between perceived values with purchase

intention

Intention Decision

Sig = 0.000

Alpha = 0.05 level,

So Sig <Alpha, Ho is accepted.

Conclusion

There are significant relationships between perceived values towards purchase

intention with 0.826 points, where the influence are very positive and very strong

(Riduwan and Kuncoro, 2008). So, when the perceived values decrease, it will greatly

affects the purchase intention, otherwise if the perceived values increases, it also will

greatly affects the purchase intention.

4.6 FACTOR ANALYSIS This analysis should be done because the researcher would like to know the

dimension of the independent variables on which factors are very influence on the

dependent variable. Previously, researcher has explained that there are four dimension

of the variable X, which these dimensions obtained from Sweeney and Soutar theory.



In analyzing this factor, it will be performed several times until researcher find the

result of output from component matrix there is only one column.

4.6.1 FIRST TEST OF FACTOR ANALYSIS Figure 4.31. First KMO and Bartlett’s output

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .877

Bartlett's Test of Sphericity Approx. Chi-Square 555.604 df 45 Sig. .000

Table 4.32. Anti-Image Matrix First Test output Anti-image Matrices

PV1emotional

PV2emotional

PV3emotional

PV4social

PV5social

PV6quality

PV7quality

PV8price

PV9price

PV10price

Anti-image Covariance

PV1emotional

.583 -.125 .009 .027 -.072 -.066 .005 .071 -.010 -.070

PV2emotional

-.125 .308 -.136 -.011 .015 -.007 -.036 -.006 -.046 -.066

PV3emotional

.009 -.136 .311 -.007 -.005 -.104 -.050 -.004 -.019 .034

PV4social

.027 -.011 -.007 .612 -.101 -.048 -.024 .024 -.142 -.066

PV5social

-.072 .015 -.005 -.101 .678 -.073 .034 -.049 -.074 -.020

PV6quality

-.066 -.007 -.104 -.048 -.073 .277 -.113 -.032 .044 -.030

PV7quality

.005 -.036 -.050 -.024 .034 -.113 .335 -.046 .097 -.103

PV8price

.071 -.006 -.004 .024 -.049 -.032 -.046 .408 -.240 -.084

PV9price

-.010 -.046 -.019 -.142 -.074 .044 .097 -.240 .429 -.017

PV10price

-.070 -.066 .034 -.066 -.020 -.030 -.103 -.084 -.017 .410

Anti-image Correlation

PV1emotional

.904a -.294 .022 .046 -.115 -.165 .012 .145 -.021 -.143

PV2emotional

-.294 .893a -.440 -.026 .034 -.024 -.111 -.016 -.127 -.185

PV3emotional

.022 -.440 .884a -.017 -.011 -.355 -.154 -.012 -.053 .094

PV4social

.046 -.026 -.017 .920a -.156 -.117 -.053 .049 -.277 -.133

PV5social

-.115 .034 -.011 -.156 .929a -.169 .071 -.094 -.136 -.039

PV6quality

-.165 -.024 -.355 -.117 -.169 .889a -.370 -.096 .128 -.088

PV7quality

.012 -.111 -.154 -.053 .071 -.370 .879a -.124 .256 -.278

PV8price

.145 -.016 -.012 .049 -.094 -.096 -.124 .817a -.574 -.205



PV9price

-.021 -.127 -.053 -.277 -.136 .128 .256 -.574 .706a -.040

PV10price

-.143 -.185 .094 -.133 -.039 -.088 -.278 -.205 -.040 .924a

a. Measures of Sampling Adequacy(MSA)

Table 4.33 componet matrix ouput Component Matrixa

Component 1 2

PV1emotional .646 -.310 PV2emotional .844 -.182 PV3emotional .819 -.247 PV4social .647 .317 PV5social .589 .322 PV6quality .844 -.286 PV7quality .773 -.386 PV8price .678 .507 PV9price .518 .737 PV10price .808 -.030 Extraction Method: Principal Component Analysis.

a. 2 components extracted.

Based on the first test, it can be seen from the component matrix have 2 components,

which is supposed or expected to form for one component. So to make the data above

to be valid or there is only formed one component, there should be re-testing to

removing the items in anti-image correlation that have MSA score less than alpha or

0,5. However in this case basically there is no score less than alpha or 0,5. So the

smallest MSA score have to dispose, that is PV9 Price, which is one of price

dimension.

4.6.2 SECOND TEST OF FACTOR ANALYSIS

After conducted the re-testing, which is there is only 9 items of variable independent

dimensions. In the second times of retesting of factor analysis still there are two

components in the matrix components. This indicates that the data is still not valid,

and the factors that influence cannot be concluded. As described in the formula for

searching the factor analysis, the data have a possibility to be concluded if the

component matrix has only one component.



So based on these tables below, the items PV3 emotional, which is one of the

emotional dimension items, should be take it out. And conducted the next re-testing.

Table 4.34 KMO and bartlett’s Test Output



Table 4.35 Anti-image matrices output

Anti-image Matrices

PV1emotional

PV2emotional

PV3emotional

PV4social

PV5social

PV6quality

PV7quality

PV8price

PV10price


PV1emotional

.583 -.128 .009 .026 -.075 -.066 .008 .097 -.071

PV2emotional

-.128 .313 -.141 -.029 .008 -.002 -.028 -.048 -.069

PV3emotional

.009 -.141 .312 -.015 -.008 -.104 -.049 -.023 .033

PV4social

.026 -.029 -.015 .663 -.138 -.037 .009 -.089 -.078

PV5social

-.075 .008 -.008 -.138 .691 -.068 .055 -.138 -.024

PV6quality

-.066 -.002 -.104 -.037 -.068 .282 -.134 -.011 -.028

PV7quality

.008 -.028 -.049 .009 .055 -.134 .358 .014 -.106

PV8price

.097 -.048 -.023 -.089 -.138 -.011 .014 .608 -.140

PV10price

-.071 -.069 .033 -.078 -.024 -.028 -.106 -.140 .411


PV1emotional

.898a -.299 .021 .041 -.119 -.164 .018 .162 -.144

PV2emotional

-.299 .886a -.451 -.064 .017 -.007 -.082 -.109 -.192

PV3emotional

.021 -.451 .880a -.033 -.018 -.351 -.145 -.052 .092

PV4social

.041 -.064 -.033 .935a -.204 -.085 .019 -.140 -.150

PV5social

-.119 .017 -.018 -.204 .893a -.154 .111 -.212 -.045

PV6quality

-.164 -.007 -.351 -.085 -.154 .887a -.420 -.028 -.084

PV7quality

.018 -.082 -.145 .019 .111 -.420 .892a .029 -.277



PV8price

.162 -.109 -.052 -.140 -.212 -.028 .029 .887a -.279

PV10price

-.144 -.192 .092 -.150 -.045 -.084 -.277 -.279 .907a

a. Measures of Sampling Adequacy(MSA) Table 4.36 Component Matrix output

Component Matrixa Component

1 2 PV1emotional .663 -.323 PV2emotional .850 -.191 PV3emotional .833 -.218 PV4social .625 .452 PV5social .572 .523 PV6quality .867 -.171 PV7quality .804 -.272 PV8price .634 .485 PV10price .810 .045 Extraction Method: Principal Component Analysis. a. 2 components extracted.

4.6.3 THIRD TEST OF FACTOR ANALYSIS

After passed the re-testing for the three times, finally the data of matrix component

can be directly declared valid, because in component column there is only one

component, and the factors that influences can be concluded.

And also based on the table below, the KMO score can be said valid, because the

score is above the alpha score or 0,5. That is 0,880 and then the data are significance

because the Sig. score is less than alpha

Decision-making

KMO > Alpha = accepted

Sig = 0.000

Alpha = 0.05 level

So Sig <Alpha, Ho is accepted.



The percentage of those factors

Based on table total variance explained below, revealed that these factors have 54,8%

in influencing customer behavior.

4.37 Output of KMO and Barlett’s third test



4.38 Anti Image Matrices third test output

Anti-image Matrices PV1emot

ional PV2emot

ional PV4so

cial PV5so

cial PV6qu

ality PV7qu

ality PV8price

PV10price


PV1emotional

.583 -.156 .026 -.075 -.072 .010 .098 -.072

PV2emotional

-.156 .393 -.045 .005 -.071 -.063 -.073 -.068

PV4social

.026 -.045 .664 -.139 -.048 .007 -.090 -.077

PV5social

-.075 .005 -.139 .692 -.081 .055 -.139 -.023

PV6quality

-.072 -.071 -.048 -.081 .321 -.175 -.022 -.020

PV7quality

.010 -.063 .007 .055 -.175 .366 .010 -.104

PV8price .098 -.073 -.090 -.139 -.022 .010 .610 -.139 PV10price

-.072 -.068 -.077 -.023 -.020 -.104 -.139 .414


PV1emotional

.872a -.325 .042 -.119 -.167 .021 .164 -.147

PV2emotional

-.325 .904a -.088 .009 -.198 -.167 -.149 -.169

PV4social

.042 -.088 .922a -.205 -.103 .014 -.142 -.147

PV5social

-.119 .009 -.205 .877a -.171 .109 -.214 -.043

PV6quality

-.167 -.198 -.103 -.171 .862a -.509 -.049 -.055

PV7quality

.021 -.167 .014 .109 -.509 .843a .022 -.267

PV8price .164 -.149 -.142 -.214 -.049 .022 .868a -.276 PV10price

-.147 -.169 -.147 -.043 -.055 -.267 -.276 .905a




Table 4.39 Output of Component Matrix third Test Component Matrixa Component

1 PV1emotional .669 PV2emotional .833 PV4social .645 PV5social .594 PV6quality .854 PV7quality .797 PV8price .652 PV10price .829

Extraction Method: Principal Component Analysis. a. 1 components extracted.

Table 4.40 Output of Total Variance Explained

Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared

Loadings Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% 1 4.387 54.841 54.841 4.387 54.841 54.841 2 .971 12.132 66.973 3 .688 8.599 75.572 4 .569 7.118 82.690 5 .504 6.297 88.987 6 .353 4.411 93.398 7 .311 3.887 97.285 8 .217 2.715 100.000 Extraction Method: Principal Component Analysis.

4.6.3 CONCLUSION OF FACTOR ANALYSIS TESTS

From all items of variable X or independent, which is recommended sellers as

perceived value there is only eight items from four dimensions that highly influence

purchase intention of Kaskus’ community. These factors are: PV1 and PV2 from

emotional dimension, PV4 and PV5 from social dimension, PV6 and PV7 from

quality dimension, PV8 and PV10 from price dimension.



The total percentage of these factors in influencing purchase intention is 54.8% which

is it can bee seen from the table total variance explained. From the total of 54,8%, the

most influence factors are PV6 quality, after that followed by PV2 emotional and

PV10 price. Which is the score of PV6 as quality dimension is 0,854, PV2 as

emotional dimension is 0,833 and PV10 as price 0,829

In chapter 3, the researcher has described that the question of PV6 in questionnaire is

komunikasi antara penjual dan pembeli di forum jual beli kaskus sangat baik (The

communication level between the seller and buyer in trading forum of Kaskus is

going well) and the question of PV2 is Saya memiliki rasa percaya untuk melakukan

transaksi, seperti membeli sebuah hand phone di forum jual beli kaskus (I do believe

in making a transactions, such as buy a hand phone in the trading forum of kaskus)

and the last the question for PV10 as price dimension is Harga yang ditawarkan oleh

penjual sesuai dengan manfaat yang ditawarkan (Seller offers the price in accordance

with the benefit offered)



Chapter 5 - Conclusion

5.1 CONCLUSION

This research aims to determine the customer perceptions regarding the recommended

sellers as perceived value and to know about customer intention. Furthermore this

research also aimed to determine the effect of recommended sellers as perceived

value towards purchase intention of Kaskus’ community to a hand phone on

www.kaskus.co.id.

Based on the descriptive analysis of the variables generally known perceived value

which consist of the emotional dimension, social dimension, quality dimension, and

price dimension. Otherwise, the purchase intention consists of in three dimensions,

namely: Likely, Definitely Would and Probable. Recommended seller as perceived

value in this research is the independent variable, while the purchase intention is

dependent variable.

In chapter 4, the researcher has been described that there is influences of

recommended seller as perceived value towards purchase intention of Kaskus

community and the influence exerted very strong or significant. Which the results

obtained from the analysis using the pearson correlation.

So based on the pearson correlation results makes the first research question has been

answered, which the question is how are the influence of “recommended seller” to

increaser purchase intention from the potential buyers?

The researcher also looking for the specific factors in dimension of recommended

seller as perceived value to answer the second research question in this research. And

the researcher found that each dimension of recommended seller as perceived value is

very influential, which the level of influencing is 54,8% towards purchase intention of

Kaskus’ community.



Thus can be concluded that sending a messages or values in positive terms and

trustworthy can increase the purchase intention from the potential buyers and the

submission of such value in the online-shopping can be a determining factor in the

success of purchase intention.

5.2 RECOMENDATION

Based on the conclusion obtained, the researcher propose some practical advice and

theoretical, those are

5.2.1 PRATICAL ADVICE

Practical advices given to the seller on trading forum of www.kaskus.co.id and the

Kaskus itself as the company and also to other online-shopping are:

1. The marketing department of www.kaskus.com should be keep focused on the

recommended seller as perceived value as the one basic techniques to get

people to make transactions activities on www.kaskus.co.id. Because the

higher perceived positive value, then people would be interested in making

transaction on www.kaskus.co.id, so it can be increase the traffic of

www.kaskus.co.id and exactly it is give benefit to www.kaskus.co.id as online

company, which is always trying to improve the traffic level. Besides

spreading positive messages or values to the users, and people the marketing

of www.kaskus.co.id should give more unique ideas to the seller, which as

already described in this research that the sending-values inly affect 54%

purchase intention of customer.

2. The seller on www.kaskus.co.id should be provide more clearly identity about

themselves, because it can be created a better the sending-values or messages

to customers. Usually, online-shopping customers more preferred the clarity.

Online-shopping is not like traditional market or stores, where the customers

can directly trust on the things, because they have a possibility to make

physical contact with the seller and the product offered. Different story with



the online-shopping, where the identity of seller and sending-messages or

positive values is the key to make the customer trust and increase the purchase

intention.

5.2.2 ACADEMIC ADVICE

Academic suggestions are primarily for advanced research include the following:

1. Future research should be directed at the object research broader research to

get more general result of the factors that influence the recommended seller as

perceived value and increase customer purchase intention, for example by

increasing the number of samples, or addition of product categories.

2. In this research, 54,8% of recommended seller as perceived value factors are

influencing the purchase intention, so the further research may be to examine

the other factors that may affect the purchase intention.



References: Books Aakouk, Mustafa ,2006, Faculty of Economics Thesis: Market-based capabilities, perceived quality and firm performance Defended, Groningen, Netherlands.

Alifahmi, Hifni, 2005, Strategi Komunikasi Pemasaran, PT. Mizan Pustaka, Jakarta.

Anwar, S, 2007, Metode penelitian, Penerbit Pustaka Pelajar, Yogyakarta. Arikunto. Suharsimi, 2006, Prosedur Penelitian Suatu Pendekatan Praktik, Rineka Cipta, Jakarta.

Bandyo-padhyay, N, 2003, E-commerce. Context, concepts and consequences. McGraw-Hill International Editions, New York.

Berman, Barry; Evans, and Joel R. 2002, Retail Management: A Strategic Approach. Prentice Hall, Englewood Cliffs.

Chaffey, Dave; 2006, Internet Merketing. Pearson Education. Prentince Hall, London.

Churchill, G.A, and Iacobucci, D, 2005, Marketing Research: Methodological Foundations, 9th . Belomont CA: Thomson South-Western.

Dhar. Pinder, Gupta. Prashant, and Jain. Rajesh, 2007, Enhancing enterprise competitiveness: Marketing, people, IT, and entrepreneurship, Allied Publishers.

Ghozali, Imam 2005. Aplilaksi analisis multivariate dengan program SPSS, Badan Penerbit Diponegoro, Semarang. Hamidi. 2005, Metode Penelitian Kualitatif, UMM Press, Malang Hermawan, Kartajaya, 2002, Marketing Plus 2000 Siasat Memenangkan Persaingan Global, Gramedia Pustaka Utama, Jakarta

Hikmat, Mahi M. 2011. Metode Penelitian dalam Perspektif Ilmu Komunikasi dan Sastra, Graha Ilmu, Yogjajarkata

Keller, Kevin Lane. 1998, Strategic Brand Management : Building, Measuring, and Managing Brand Equity, Prentice Hall, New Jersey

Kotler, and Keller, 2006, Marketing Management, 12th edition, Prentice Hall, New Jersey Kotler, P, and Armstrong, G, 2004, Principles of Marketing, 10th Edition. Pearson Education Inc, Upper Saddle River,New Jersey



Kotler, P. 2001, A framework for marketing management. Upper Saddle River, Prentice Hall, New Jersey

Kotler, Philip and Gary Armstrong, 2001, Prinsip-prinsip Pemasaran, jilid 2, Edisi kedelapan, Erlangga, Jakarta

Kotler. Philip, and Gary. Armstrong, 2006, Principles of Marketing, 11th Edition, Pearson Prentice Hall, New Jersey. Philip Kotler, 2007, Marketing Management, Pearson Prentice Hall, New York Schiffman, L.G. and L. L. Kanuk, 2000, Consumer Behaviour. 7th Edition. Prentice Hall, New Jersey.

Sugiyono, 2009, Metodologi Penelitian Kuantitatif Kualitatif dan R&D, Alfabeta, Bandung

Sujoko Efferin. 2004. Metode Penelitian Untuk Akuntansi, Bayumedia Publishing, Jawa Timur. Terence A. Shimp. 2003, Periklanan Promosi Aspek Tambahan Komunikasi Pemasaran Terpadu, First edition, Erlangga, Jakarta Uma Sekaran, 2006, Metodologi Penelitian untuk Bisnis, Edisi 4, Buku 2, Salemba Empat, Jakarta. Wahyuningsih, 2004, Customer Value: Consept, Operationalization, and Outcome. Usahawan. Agustus, No.8 TH XXXIII.

William F. Arens, 1993, Contemporary Advertising (international Edition).Mc.Graw Hill, New York.

Journal:

Anckar, Bill and D'Incau, Davide, 2002, "Value Creation in Mobile Commerce: Findings from a Consumer Survey," Journal of Information Technology Theory and Application (JITTA), Bagozzi, Baumgartner, and YI, 1989, ” An investigation into the role of intentions as mediators of the attitude-behavior relationship”, Journal of Economic Psychology 1989 pages 35-62, North Holland Chen, W.K. Huang, and H.C. Chou, S.C, 2008, “Understanding consumer recommendation behavior in a mobile ohone service context” Cronin, J.J., Brady, M.K., and Hult, G.T.M, 2000, “Assessing the effects of quality,



value, and customer satisfaction on consumer behavioral intentions in service environments”. Journal of Retailing, 76(2), 193-218.

Garusing Arachchige, 2002, “J.J Application of marketing mix elements (4ps) in the library sector” http://eprints.rclis.org/6742/, accessed on May 29th 2013 at 11.17 PM Hsinkuang Chi, Huery-Ren Yeh, and Yi Ching Tsai, 2011, “The Influences of Perceived Value on Consumer Purchase Intention: The Moderating Effect of Advertising Endorser.” Journal of International Management Studies, Pages 92-97 Karen H Smith and Natesan. N Chinna, 1999, “Consumer Price-quality beliefs: Schema Variable Predicting Individual Differences, Advances in Consumer Research”, volume 26, Pages 562-568 Kinnear, Thomas C. and James R. Taylor, 1995, “Marketing Research: An Applied Approach”. McGraw Hill Text.

Komulainen, Mainela, Tahtinen, and Ulkuniemi in Alsheikhand and Bojei, 2012, “Customer’s perceived value to use mobile banking services” Kuo. Ying-Feng, Wu. Chi-Ming, Deng. And Wei-Jaw, 2009, “The relationships among service quality, perceived vaue, customer satisfaction, and post-purchase intention in mobile value-added services”, Journal computers in Human Behavior, pages 887-896 Lestari. P.N, Siburian.P.S, and Asnawati, 2012, ”Pengaruh Iklan, Brand Trust, dan Brand Image terhadap Minat Beli Konsumen WiGo 4G WiMax PT Berca Hardaya Perkasa Di Kota Balikpapan” “Life Online”, 2012, Digital Agenda Scorboard, https://ec.europa.eu/digital-agenda/sites/digital-agenda/files/scoreboard_life_online.pdf, accessed on June 25th 2013 at 04.21 PM Navarone, Okki, 2003, ”Analisi pengaruh tingkat kesuksesan produk baru dalam peningkatan kinerja pemasaran” Jurnal sains pemasaran Indonesia, Mei 2003 pages 111-122 Singgih D. 2011, “Penggunaan internet sebagai media komunikasi dalam menciptakan hubungan akrab.” [Skripsi].Intstitut Pertanian Bogor, Bogor Sweeney, J.C and G.N. Soutar. 2001, “Customer Perceived Value : The Development of Multiple Item Scale”, Journal Retailing, Vol.77

Yaseen, Mariam Tahira, Gulzar and Anwar, 2011, ”Impact of Brand Awarness, perceived quality and customer loyalty on brand profitability and purchase intention: A reseller’s view”, journal of contemporary research in business Yulihasri, Aimnul and David, 2011, “factors that influence customer’s buying intention on shopping online”



Website http://royal.pingdom.com/2009/11/27/study-males-vs-females-in-social-networks/, “Study:Males vs. females in social networks”, accessed on June 21st 2013 at 09.08 PM http://www.brandrich.com/blog/search-engine-optimization/what-is-the-purpose-of-your-website.html, Prakash, Vinai, 2008, “What is purpose of your website?”, accessed on June 25th 2013 at 10.23 AM http://www.jugglingart.org/2013/01/products-and-services-classification.html “Products and Services Classification According to Philip Kotler and Henry Assael”, accessed on May 24th 2013 at 05.14 PM http://www.oprah.com/relationships/The-Negative-Effects-of-Porn, ”the negative effects of porn”, accessed on June 21st 2013 at 08.00 AM http://www.pewinternet.org/Reports/2011/Technology-and-social-networks/Part-2/Demographics.aspx, Hampton. K, Goulet. S, Raineie. L, and Purcell. Kristen, 2011 “Who are the social networking users?”, accessed on June 20th 2013 at 11.50 PM http://www.she-conomy.com/facts-on-women, Holland, Stephanie, 2009 “Marketing to woman quick fact” accessed on June 21st 2013 at 11.34 AM http://www.slashdocs.com/yvuxm/factor-analysis.html”, Flyingvince, 2010, “Factor Analysis”,accessed on June 20th 2013 at 03.14 PM http://www.statstutor.ac.uk, accessed on 5th June 2013 at 09.06 PM www.alexa.com, accessed on April 29th 2013 at 03.21 PM www.danielsoper.com, accessed on 5th June 2013 at 08.45 PM www.kaskus.co.id, accessed on April 28th at 09.31 AM



APPENDICES

APPENDIX A – SURVEY QUESTIONNAIRE



APPENDIX B – DATA OF RESPONDENTS



The researcher has spread the questionnaire through www.kaskus.co.id on Hand phone and PDA category Timestamp

Nama

Jenis

Kelamin

Usia

Pekerjaan

Apakah

anda terdaftar sebagai

member di

www.kaskus.co.id

?

Jika YA,

sudah

berapa

lama anda sebagai

member di

www.kaskus.co.id

?

Apakah

anda pernah

membeli Handphone di

forum

jual beli

www.kaskus.co.id

?

PV1emotional

PV2emotional

PV3emotional

PV4social

PV5social

PV6social

PV7quality

PV8quality

PV9price

PV10price

PI1likely

PI2likely

PI3likely

PI4DW

PI5DW

PI6probable

PI7probable

PI8probable

Jika YA, berapa kali

pembelian

40/10/2013 19:40:31

Joni Rizal

Laki-lak

i

23 - 25 Tahun

Wirausaha

YA > 2 Tahu

n

YA 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 2 Joni.rizal1234@gma

il.com

43/11/2013 9:43:1

6

Andisyah

Laki-lak

i

23 - 25 Tahun

Pega

wai Ne

egri

YA 2 Tahu

n

YA 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1

45/12/2013 9:45:5

2

Ami Perem

puan

17 - 19 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 4 2 4 4 2 2 4 5 4 4 4 4 4 4 4 4 4 1 Amidianty_09@yah

oo.com

47/12/2013 9:47:5

2

Toni Andr

a

Laki-lak

i

20 - 22 Tahun

Pega

wai

YA > 2 Tahu

n

YA 1 2 2 4 3 2 2 4 4 2 3 2 2 2 2 2 2 3 1 [email protected]

om

49/12/2013 10:49:14

Rianti Kinan

da

Perem

puan

20 - 22 Tahun

Pega

wai Swast

a

YA 2 Tahu

n

YA 5 4 4 4 4 5 4 4 4 4 5 4 4 4 4 4 4 5 1 rianti_kinanda@gma

il.com

51/12/2013 11:51:24

Nufus Zahra

Perem

puan

20 - 22 Tahun

Pega

wai Swast

a

YA > 2 Tahu

n

YA 4 5 4 5 4 4 5 4 5 4 5 5 5 5 5 5 5 5 2 nufus_zahra20@yah

oo.com

52/12/2013 12:52:29

Rian Muba

rak

Laki-lak

i

17 - 19 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 Mubarak_elrian@ya

hoo.com

53/ Toma La 2 Ma YA 2 YA 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 1



12/2013 15:53:17

s ki-lak

i

0 - 22 Tahun

hasisw

a

Tahun

26/12/2013 16:26:30

Ahmad

Subarjo

Laki-lak

i

20 - 22 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 4 2 5 4 3 2 4 5 4 4 4 4 4 5 5 5 4 2

43/12/2013 16:43:56

ridho Laki-lak

i

20 - 22 Tahun

Wiraswasta

YA 2 Tahu

n

TIDAK

4 4 4 4 3 3 3 4 4 4 4 4 4 4 3 3 3 3 tidak pernah

85215888812

49/12/2013 16:49:41

Selvia Sari

Rahmaw

ati

Perem

puan

17 - 19 Tahun

Pelajar

YA > 2 Tahu

n

TIDAK

4 2 2 5 3 4 3 4 4 4 1 5 5 4 3 5 3 4 0 Contact number:

085250211340

E-mail: v2ituaza@

yahoo.com

59/12/2013 16:59:34

Marvian

Laki-lak

i

> 26 Tahun

Wirausaha

YA > 2 Tahu

n

YA 5 5 5 5 5 4 2 4 4 4 5 4 4 4 4 4 5 5 > 10 kal

i

vrab_kaskus@yahoo

.co.id

3/12/201

3 17:03:53

yukihiro

Laki-lak

i

17 - 19 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 1 2 3 3 3 2 1 2 2 2 1 3 3 1 2 1 2 2 1 8388033931

5/12/201

3 17:05:01

amanda

Perem

puan

23 - 25 Tahun

karyawa

n swast

a

YA > 2 Tahu

n

YA 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 dua

kali

email saya di

frankyawesome@ya

hoo.com untuk no hp nya di

082111400671

5/12/201

3 17:05:28

adama

pasajadi

Laki-lak

i

17 - 19 Tahun

pelajar

YA > 2 Tahu

n

TIDAK

4 5 5 4 4 5 5 3 3 4 3 2 4 5 5 5 4 5 0 08977939327 sma

only :)

30/12/2013 17:30:24

combro

Perem

puan

20 - 22 Tahun

Pekerja sex non

komersial

TIDAK

2 Tahu

n

TIDAK

1 5 1 5 1 5 1 5 1 5 1 5 1 5 1 5 1 5 1 [email protected]

45/12/2013 17:45:42

Haris Rizqi Arifin

Laki-lak

i

> 26 Tahun

Guru

YA 2 Tahu

n

YA 3 4 4 4 4 5 3 5 5 3 5 5 5 5 5 5 5 5 >30

085641280807

[email protected]

o.id

52/12/

andi Laki-

> 2

wiras

YA > 2 Tahu

YA 4 4 5 5 5 4 4 5 5 4 5 4 4 4 5 5 5 4 diat

joe_mari@rocketm



2013 17:52:02

laki

6 Tahun

wasta

n as 10 kal

i

ail.com

2/12/201

3 18:02:09

1syarif

Laki-lak

i

20 - 22 Tahun

karyawa

n

YA 2 Tahu

n

YA 4 3 3 4 3 4 3 3 3 3 4 4 4 4 4 4 3 3 1 082136281995

akhmadm.syarif@gm

ail.com

22/12/2013 18:22:01

richard

Laki-lak

i

> 26 Tahun

mahasisw

a

YA > 2 Tahu

n

YA 3 3 3 4 3 3 3 5 4 4 4 4 4 4 4 4 3 3 1 85299960986

23/12/2013 18:23:11

richard

Laki-lak

i

> 26 Tahun

mahasisw

a

YA > 2 Tahu

n

YA 3 3 3 4 3 3 3 4 4 4 4 4 4 4 4 4 3 3 1 85299960986

28/12/2013 18:28:33

sigit Laki-lak

i

> 26 Tahun

guru

YA > 2 Tahu

n

YA 4 5 5 5 5 5 4 5 5 5 5 5 5 4 5 5 5 5 2 085647079868

sigit_pduns@yahoo.

co.id.

33/12/2013 18:33:58

Fadil Laki-lak

i

23 - 25 Tahun

Karyawa

n Swast

a

YA 2 Tahu

n

YA 4 3 3 2 2 2 2 2 4 3 2 4 4 3 3 4 3 4 1x 81294137572

58/12/2013 18:58:51

Donie Laki-lak

i

> 26 Tahun

Karyawa

n

YA > 2 Tahu

n

YA 3 2 2 4 4 3 1 2 4 4 2 3 4 3 2 3 1 3 1 085711551985

semoga

skripisinya cepat kelar

gan... sukses selalu

5/12/201

3 19:05:05

agung

Laki-lak

i

17 - 19 Tahun

pelajar

YA 2 Tahu

n

YA 4 4 4 3 5 4 4 2 2 3 1 1 4 4 3 4 2 4 1 CP : 08788382

3573 Emal :

agung50.marulitua

@gmail.com

14/12/2013 19:14:44

Ahmad

Habibulloh

/ Khbbsemplan(k

askus)

Laki-lak

i

17 - 19 Tahun

Mahasisw

a

YA > 2 Tahu

n

YA 3 4 5 4 5 5 3 5 5 4 4 5 5 4 5 5 5 4 2 08978946364.

Email: gokilhabib@rocketm

ail.com Kaskus:

Khbbsemplan

41/12/2013 19:41:20

Khairul

Hanafi

Laki-lak

i

20 - 22 Tahun

Wiraswasta

YA > 2 Tahu

n

YA 5 3 5 5 5 5 3 5 5 3 4 5 5 5 5 5 5 5 5 kal

i

43/12/2013 19:43:04

Setipen

Laki-lak

i

23 - 25 Ta

Mahasisw

a

YA > 2 Tahu

n

YA 5 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 4 4 1 capek selasai

penelitiannyo..



hun

58/12/2013 19:58:52

Deny Danu Prase

tia

Laki-lak

i

17 - 19 Tahun

Pelajar

YA > 2 Tahu

n

YA 4 4 4 5 5 5 5 5 5 5 4 5 5 5 4 5 3 5 1 HP : 08974709

275 email :

[email protected]

om

38/12/2013 20:38:01

aditya

brilian

Laki-lak

i

17 - 19 Tahun

pelajar

YA > 2 Tahu

n

YA 4 4 5 5 4 4 4 5 5 5 4 4 5 4 5 4 4 5 4 85716167977

5/12/201

3 21:05:07

Lucy Apriy

anti

Perem

puan

> 26 Tahun

Pega

wai Swast

a

YA > 2 Tahu

n

YA 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1x [email protected]

m

11/12/2013 21:11:51

agus rianto

Laki-lak

i

23 - 25 Tahun

wiraswasta

YA 2 Tahu

n

YA 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 2

39/12/2013 21:39:02

Bagus dwi putra

Laki-lak

i

20 - 22 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 4 4 3 3 4 3 5 4 4 2 4 4 4 4 4 2 2 1X 87771194362

39/12/2013 21:39:47

Nikki lauda hariyona

Laki-lak

i

23 - 25 Tahun

Mahasisw

a

YA > 2 Tahu

n

YA 4 4 4 4 3 4 2 5 5 4 3 4 5 5 3 5 5 4 Tiga kal

i

Nikki lauda h :

082122582875

[email protected]

52/12/2013 21:52:45

Perem

puan

20 - 22 Tahun

Mahasisw

a

YA > 2 Tahu

n

YA 5 4 4 4 5 5 4 4 4 4 4 4 5 5 5 5 3 3 1 Rhefreshyourmind@

yahoo.com

43/13/2013 0:43:2

3

Irvan amra

n

Laki-lak

i

20 - 22 Tahun

Mahasisw

a

YA > 2 Tahu

n

YA 3 3 4 3 4 4 3 4 5 4 4 4 4 4 3 4 4 4 1 amran.irvan@yahoo.

com

5/13/201

3 1:05:5

3

Rifry Marth

a

Laki-lak

i

23 - 25 Tahun

mahasisw

a

YA > 2 Tahu

n

YA 5 4 4 2 4 3 3 5 4 4 3 5 4 3 2 5 5 4 satu

kali

[email protected]

om +6281277

229433

8/13/201

3 11:08:

Andreas

Laki-lak

i

23 - 25 T

Creativ

e Designer

YA 2 Tahu

n

YA 3 3 4 5 4 2 2 5 5 4 3 5 5 5 5 5 4 4 3 no hp 08787771

6405 email

[email protected]



04 ahun

m

good luck gan!

ditunggu pulsanya

:p 16/13/2013 11:16:41

katy gak

pake perry

Perem

puan

20 - 22 Tahun

Pelajar

YA 2 Tahu

n


21/13/2013 11:21:01

yorida

Perem

puan

23 - 25 Tahun

karyawa

n

YA > 2 Tahu

n

YA 2 2 3 4 5 3 3 4 4 3 3 4 4 4 4 5 4 5 1 83877124715

4/13/201

3 12:04:33

Arif Hiday

at

Laki-lak

i

> 26 Tahun

Karyawa

n

YA > 2 Tahu

n

TIDAK

3 4 4 4 4 4 4 3 4 4 4 5 4 4 4 5 3 4 0 CP : 0857 150 22424

Email :

arif.hidayat.an@gma

il.com

Semoga sukses

gan,,,Thank U....

7/13/201

3 12:07:41

ester Perem

puan

20 - 22 Tahun

mahasiswi

YA > 2 Tahu

n

YA 4 3 4 5 4 4 3 4 4 4 4 5 4 4 4 5 4 4 2 ester.etregie@yahoo.

com

24/13/2013 12:24:03

Agusriady

Saputra

Laki-lak

i

23 - 25 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 4 4 4 4 4 5 4 4 5 5 4 4 4 4 5 4 5 2 kal

i

33/13/2013 12:33:23

Muhamma

d Alpia

ni

Laki-lak

i

20 - 22 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 3 3 4 5 4 3 5 4 5 5 4 4 4 4 4 4 4 5 kal

i

85312520003

34/13/2013 12:34:54

saeful

bahrhi

Laki-lak

i

23 - 25 Tahun

freelance

YA > 2 Tahu

n

YA 5 4 4 3 4 3 3 3 4 3 5 4 4 4 4 4 4 3 2 email : [email protected]

.id HP :

08983512220

semoga

penelitian anda

lancar dan sukses

37/13/2013 12:37:33

agung

Laki-lak

i

17 - 19 Tahun

pelajar

YA 2 Tahu

n

TIDAK

4 4 3 4 3 2 2 2 4 1 4 4 5 3 4 2 4 0 cp : 08788382

3573 email :

agung50.marulitua

@gmail.com

7/13/201

3 13:

CATUR

PRAYOG

O

Laki-lak

i

20 - 22

SWASTA

YA > 2 Tahu

n

YA 4 5 5 5 5 5 4 5 5 5 5 5 4 5 1 4 5 10 08983344412

EMAIL caturprayogo@rocke



07:51

Tahun

tmail.com

12/13/2013 14:12:20

fadking

Laki-lak

i

> 26 Tahun

profesi

onal

YA > 2 Tahu

n

TIDAK

4 4 3 4 4 3 4 3 4 4 3 4 3 4 4 3 4 3 1 81380035006

16/13/2013 14:16:43

Gugi Laki-lak

i

23 - 25 Tahun

Pega

wai

YA > 2 Tahu

n


m

7/13/201

3 15:07:40

Riondira

Laki-lak

i

20 - 22 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 5 4 4 5 5 4 4 4 5 4 4 5 5 4 4 3 4 5 081228525651

[email protected]

48/13/2013 15:48:48

Andri Kurniawan

Laki-lak

i

23 - 25 Tahun

Satpam

YA > 2 Tahu

n

YA 5 3 3 4 4 4 2 3 5 4 2 4 3 3 3 3 3 5 1 8983500931

30/13/2013 16:30:46

Arvin Tobia

s

Laki-lak

i

17 - 19 Tahun

Mahasisw

a

YA > 2 Tahu

n

YA 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 1 085693140992/arvintobias7@g

mail.com

Semoga ane yg dapet

pulsanya, sukses

buat tugas akhirnya

gan 35/13/2013 16:35:10

Kholid

Abdillah P.

Laki-lak

i

20 - 22 Tahun

Mahasisw

a

YA 2 Tahu

n

TIDAK

4 5 4 3 5 5 4 5 5 4 4 5 5 5 4 5 2 4 - 085731825957

kholidabdillah@gmail

.com

10/13/2013 17:10:58

Andi Laki-lak

i

23 - 25 Tahun

Mahasisw

a

YA > 2 Tahu

n

YA 2 2 1 3 3 2 1 3 3 2 2 1 2 2 1 2 2 3 1 Sukses!

16/13/2013 17:16:20

Shani Perem

puan

23 - 25 Tahun

Pega

wai Swast

a

YA > 2 Tahu

n

YA 4 4 4 3 4 4 3 4 5 3 4 3 4 5 4 4 3 4 2 see you!

18/13/2013 17:18:05

Atika Perem

puan

17 - 19 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 5 4 4 5 5 4 5 4 5 4 4 5 4 5 4 4 5 4 2

26/ Yoma La 2 Ma YA > 2 YA 2 2 2 3 2 2 2 2 3 2 2 1 1 2 1 2 2 2 1 Sukses



13/2013 18:26:40

den ki-lak

i

0 - 22 Tahun

hasisw

a

Tahun

skripsnya gan

29/13/2013 18:29:03

Sandhi

Laki-lak

i

> 26 Tahun

Sopir

YA 2 Tahu

n

YA 4 4 3 5 4 3 3 4 5 4 4 5 4 4 5 5 5 5 3 sandhi_aktar@yaho

o.com

30/13/2013 18:30:33

tami Perem

puan

> 26 Tahun

Pega

wai Swast

a

YA 2 Tahu

n


32/13/2013 18:32:03

Tia Perem

puan

17 - 19 Tahun

Mahasisw

a

YA > 2 Tahu

n


om

59/13/2013 20:59:37

vay rivai

Perem

puan

> 26 Tahun

swast

a

YA > 2 Tahu

n

YA 5 4 3 5 5 5 4 4 4 4 4 5 4 4 4 4 4 5 2 83834367727

6/13/201

3 21:06:37

Handre

Putra

Laki-lak

i

20 - 22 Tahun

Dokter

YA > 2 Tahu

n

YA 4 4 4 5 5 4 3 5 5 5 3 5 3 5 4 5 5 5 2 kal

i

[email protected]

m

45/14/2013 1:45:0

8

John Laki-lak

i

> 26 Tahun

Forex-Index-Gol

d Trader

YA > 2 Tahu

n

YA 4 3 3 5 5 3 3 4 5 3 4 5 5 3 4 4 5 5 17

45/14/2013 14:45:54

Aji Anind

ito

Laki-lak

i

> 26 Tahun

Pekerja musik

YA > 2 Tahu

n

YA 5 4 4 3 3 4 3 4 3 3 4 4 4 2 4 4 2 3 1 [email protected] - good

luck ya Pras!

27/14/2013 16:27:35

Andro

Laki-lak

i

20 - 22 Tahun

wirausaha

YA 2 Tahu

n

YA 3 2 2 4 2 2 2 2 2 2 1 2 2 2 1 2 1 2 1

33/14/2013 16:33:41

Tutias

Perem

puan

23 - 25 Tahun

Mahasisw

a

YA > 2 Tahu

n


37/14/2013 16:37:47

Pepper

Perem

puan

> 26 Tahun

Pega

wai Swast

a

YA > 2 Tahu

n

YA 3 4 4 5 4 5 1 4 5 3 4 4 3 3 4 4 4 5 2 pepper_potts@stark.

com



49/14/2013 18:49:34

vhy Perem

puan

23 - 25 Tahun

skrg

nganggur,kmrn kontrak BP

S

YA > 2 Tahu

n

YA 3 4 4 5 3 3 3 4 5 4 2 3 4 4 5 3 3 1 1x 085274533614

oktaviyani.vhy@gmai

l.com

51/14/2013 18:51:18

agung

febrian

Laki-lak

i

> 26 Tahun

swast

a

YA > 2 Tahu

n

YA 4 3 4 4 4 4 3 2 3 4 2 4 4 5 3 3 3 3 1 adungfebrian@gmail.

com

08197554546

0/14/201

3 19:00:48

Tono Laki-lak

i

20 - 22 Tahun

mahasisw

a

YA > 2 Tahu

n

YA 3 2 1 2 3 2 1 4 4 3 2 3 2 2 2 1 2 2 1 tono_andtoni@yaho

o.com

8/14/201

3 20:08:44

Duarjo

Laki-lak

i

> 26 Tahun

Satpam

YA 2 Tahu

n

YA 4 4 4 5 5 3 2 4 5 4 3 4 4 4 4 4 5 5 1 diarjo-martoyo432@yahoo.

com

39/14/2013 22:39:46

Vincent

Leo Saput

ra

Laki-lak

i

20 - 22 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 3 3 3 4 3 2 4 4 3 3 4 3 3 3 4 2 2 1 Contact Number :

083829469145

Email :

[email protected]

m

Sukses ya bro tugas

akhirnya,semoga

bermanfaat

kuisionernya.

0/14/201

3 23:00:24

Syamsul

Maarif

Laki-lak

i

23 - 25 Tahun

Mahasisw

a

YA > 2 Tahu

n

YA 4 4 4 5 2 4 2 4 5 4 4 4 4 5 5 3 4 5 lebih

dari 5

kali

untuk

hp

Contact Number :

083820002900

E-Mail : cacuyz.maarif@gmail

.com

51/14/2013 23:51:09

Izhharrudin Afkar

Laki-lak

i

17 - 19 Tahun

Pelajar

YA > 2 Tahu

n

YA 4 5 4 5 4 5 4 5 5 4 4 5 4 3 4 4 4 4 1 hp : 08385737

3521 email :

[email protected]

m

smoga aja ane dapet

gan mayan

buat pulsa 2bln gan

:shakehand

31/15/2013 0:31:5

2

saintho

valentino

Laki-lak

i

20 - 22 Tahun

IT YA > 2 Tahu

n

YA 5 3 3 5 5 5 4 5 5 5 4 4 5 5 4 3 3 4 2 087871139958

sainthosgm@gmail.

com

29/15/2013

Tono Laki-lak

i

23 - 2

Wirausaha

YA > 2 Tahu

n

YA 2 3 2 3 2 1 1 4 5 3 2 1 2 2 2 2 2 1 2 tono_antoni@gmail.

com



10:29:08

5 Tahun

31/15/2013 10:31:20

Rianti Perem

puan

> 26 Tahun

Pega

wai Swast

a

YA 2 Tahu

n

YA 2 2 2 2 2 1 1 4 5 3 2 3 2 3 2 1 2 2 1 rianti_mahdi@gmail.

com

55/15/2013 11:55:38

Azhari

Laki-lak

i

20 - 22 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 2 3 3 2 4 3 3 3 4 3 4 3 3 4 5 4 2 1 Contact Number .

XL 08194707

2212 Email

[email protected]

50/15/2013 19:50:34

Barnes

Laki-lak

i

> 26 Tahun

Wiraswasta

YA 2 Tahu

n


m

53/15/2013 19:53:31

Kijoy Laki-lak

i

> 26 Tahun

assista

nt ma

nager

YA 2 Tahu

n

YA 3 3 4 5 5 4 4 5 4 4 4 5 3 4 4 5 5 4 2 87788079806

56/15/2013 19:56:14

Kinoy Laki-lak

i

> 26 Tahun

Store

manag

er

YA 2 Tahu

n

YA 4 3 4 3 4 4 3 3 4 3 4 5 4 4 4 5 5 5 4 82112366600

19/16/2013 7:19:1

0

Nadia Rizki

Perem

puan

17 - 19 Tahun

mahasiswi

YA > 2 Tahu

n

YA 3 3 3 4 5 4 3 5 5 4 2 5 5 4 2 5 2 3 1 081809991344/nadia.nugget

@gmail.com

25/16/2013 7:25:5

3

Inggra

Perem

puan

> 26 Tahun

Karyawa

n

YA 2 Tahu

n


m 0878 2342

2573

22/16/2013 11:22:06

lanjar setiawan

Laki-lak

i

> 26 Tahun

wiraswasta

YA > 2 Tahu

n

YA 5 4 4 4 4 4 3 4 5 3 4 4 4 4 4 4 4 4 3 no hp : 08560856

2220 email :

lanjar.setiawan@gm

ail.com

10/16/2013 14:10:35

Ronny

Andrew

Laki-lak

i

> 26 Tahun

Karyawa

n Swast

a

YA > 2 Tahu

n

YA 4 3 3 4 4 4 2 4 4 4 3 4 4 4 3 4 2 3 1 8568900244

59/16/2013 14:59:39

Prawira

(jawir750)

Laki-lak

i

23 - 25 Tahun

Mahasisw

a

YA > 2 Tahu

n

YA 4 4 4 5 4 4 3 4 4 4 3 4 4 4 4 4 5 4 2x Prawira 08177293

29

12/16/2013

Yogi Laki-lak

i

20 - 2

Mahasisw

a

YA > 2 Tahu

n

YA 4 4 4 4 5 4 2 3 4 4 3 5 4 4 4 4 3 3 1 85365655676



22:12:53

2 Tahun

34/16/2013 23:34:35

Alfredo

Valiantsi

Laki-lak

i

20 - 22 Tahun

Junior

Trader

YA 2 Tahu

n

YA 2 4 4 4 5 5 4 5 5 4 5 5 4 4 5 5 5 5 1

52/17/2013 9:52:0

4

Santi Perem

puan

> 26 Tahun

Pega

wai swast

a

YA > 2 Tahu

n

YA 2 2 2 4 4 2 1 4 5 3 3 4 4 4 3 4 2 4 1

14/17/2013 12:14:54

Neli Perem

puan

> 26 Tahun

Wirausaha

YA > 2 Tahu

n

YA 4 3 3 4 5 3 2 4 5 3 4 4 5 5 4 4 3 4 3 neli_futados@yahoo

.com

16/17/2013 12:16:44

Tondri

Laki-lak

i

> 26 Tahun

Wirausaha

YA > 2 Tahu

n


m

22/17/2013 12:22:16

Jarot Laki-lak

i

> 26 Tahun

Wirausaha

YA > 2 Tahu

n


om

24/17/2013 12:24:52

mimin

Laki-lak

i

> 26 Tahun

pegawai

Swast

a

YA > 2 Tahu

n


om

37/17/2013 12:37:44

momod

Laki-lak

i

> 26 Tahun

Pega

wai Ne

geri

YA > 2 Tahu

n

YA 2 3 3 4 5 3 2 4 5 3 3 4 5 4 4 4 4 3 1 sukses mas gan!

39/17/2013 12:39:42

momod

Laki-lak

i

20 - 22 Tahun

mahasisw

a

YA 2 Tahu

n

YA 4 3 3 4 4 3 2 4 5 3 3 2 5 4 4 3 4 3 1 Ane doakan

ane lancar gan!

20/17/2013 13:20:33

Firmansya

h

Laki-lak

i

23 - 25 Tahun

Mahasisw

a

YA > 2 Tahu

n

YA 4 4 4 5 5 4 3 4 5 4 4 5 3 4 4 5 4 4 4 081319142871

firmansyahwijaya19

[email protected]

23/18/2013 9:23:2

7

Sinta Perem

puan

20 - 22 Tahun

mahasisw

a

YA 2 Tahu

n

YA 4 3 3 4 4 3 2 4 5 3 3 2 5 4 4 3 4 3 1 Good luck

25/18/

Rahma

Pere

23

Pega

YA 2 Tahu

YA 4 3 3 4 4 3 1 4 5 3 3 2 5 4 3 2 4 3 3 rahma_tonn@yahoo.



2013 11:25:09

mpuan

- 25 Tahun

wai swast

a

n com

27/18/2013 14:27:39

Randi Laki-lak

i

> 26 Tahun

Pega

wai Ne

geri

YA > 2 Tahu

n

YA 2 3 3 4 5 3 2 4 5 3 3 2 5 4 3 2 4 3 1 Randi.abdul@gmail.

com

29/18/2013 16:29:43

Rahmad

Laki-lak

i

> 26 Tahun

Broker

YA > 2 Tahu

n

YA 3 3 3 4 5 3 2 4 5 3 3 2 5 4 3 2 4 4 1 Saham_Broker@yah

oo.com sukses

gan, dan klo mau

tau tentang

bursa kabarin ane aja gan... :)

37/18/2013 17:37:41

Ade Laki-lak

i

17 - 19 Tahun

mahasisw

a

YA > 2 Tahu

n

YA 3 4 4 4 5 3 2 4 5 4 4 3 5 5 4 4 4 4 2

44/18/2013 18:44:30

Romi Laki-lak

i

20 - 22 Tahun

mahasisw

a

YA 2 Tahu

n


59/18/2013 23:59:02

yandi Laki-lak

i

20 - 22 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 3 2 4 5 2 1 4 5 4 3 3 4 4 4 4 4 5 2

59/18/2013 23:59:08

Jessica

Cua

Perem

puan

20 - 22 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 3 2 4 5 2 1 4 4 3 3 4 3 4 4 5 3 5 2

0/19/201

3 0:00:4

2

Cicila Perem

puan

17 - 19 Tahun

Mahasisw

a

YA 2 Tahu

n

YA 4 3 2 4 5 2 1 4 4 3 3 4 3 4 4 5 2 4 1

6/19/201

3 4:06:4

6

Anggi Perem

puan

20 - 22 Tahun

mahasisw

a

YA 2 Tahu

n

YA 3 2 2 3 4 2 1 3 3 3 2 3 4 4 3 4 3 5 1

10/19/2013 4:10:0

1

Ayunda

Perem

puan

20 - 22 Tahu

mahasisw

a

YA > 2 Tahu

n

YA 3 2 2 3 4 2 1 3 3 3 2 3 4 4 3 4 3 5 1 Ayunda,pratiwi@gm

ail.com



n 11/19/2013 5:11:1

3

Sindrah

Perem

puan

23 - 25 Tahun

Pega

wai Swast

a

YA > 2 Tahu

n

YA 3 2 2 3 4 2 1 3 3 3 2 3 4 4 3 4 3 3 1 sindrah-randu@ya

hoo.com

16/19/2013 0:16:4

2

Andika

Laki-lak

i

23 - 25 Tahun

wirausaha

YA > 2 Tahu

n

YA 3 2 3 4 4 3 3 4 5 4 4 5 4 4 4 4 5 4 4 boom_bast17@ymail

.com

APPENDIX C – SPSS 21.0 FOR MAC OUTPUTS FREQUENCIES VARIABLES=PI1likely PI2likely PI3likely PI4DW PI5DW PI6probable PI7probable PI8probable /ORDER=ANALYSIS. Frequencies

Notes Output Created 22-JUN-2013 12:18:08 Comments

Input

Active Dataset DataSet1 Filter <none> Weight <none> Split File <none> N of Rows in Working Data File 100

Missing Value Handling Definition of Missing User-defined missing values are treated

as missing.

Cases Used Statistics are based on all cases with valid data.

Syntax

FREQUENCIES VARIABLES=PI1likely PI2likely PI3likely PI4DW PI5DW PI6probable PI7probable PI8probable /ORDER=ANALYSIS.

Resources Processor Time 00:00:00.02 Elapsed Time 00:00:00.00

[DataSet1]

Statistics PI1likely PI2likely PI3likely PI4DW PI5DW PI6probable PI7probable PI8probable

N Valid 100 100 100 100 100 100 100 100 Missing 0 0 0 0 0 0 0 0

Frequency Table PI1likely


Valid

1.0 3 3.0 3.0 3.0 2.0 15 15.0 15.0 18.0 3.0 25 25.0 25.0 43.0 4.0 40 40.0 40.0 83.0 5.0 17 17.0 17.0 100.0 Total 100 100.0 100.0

PI2likely


Valid 1.0 5 5.0 5.0 5.0 2.0 7 7.0 7.0 12.0 3.0 13 13.0 13.0 25.0



4.0 45 45.0 45.0 70.0 5.0 30 30.0 30.0 100.0 Total 100 100.0 100.0

PI3likely Frequency Percent Valid Percent Cumulative Percent

Valid

1.0 1 1.0 1.0 1.0 2.0 7 7.0 7.0 8.0 3.0 12 12.0 12.0 20.0 4.0 47 47.0 47.0 67.0 5.0 33 33.0 33.0 100.0 Total 100 100.0 100.0

PI4DW


Valid

1.0 1 1.0 1.0 1.0 2.0 7 7.0 7.0 8.0 3.0 13 13.0 13.0 21.0 4.0 55 55.0 55.0 76.0 5.0 24 24.0 24.0 100.0 Total 100 100.0 100.0

PI5DW


Valid

1.0 3 3.0 3.0 3.0 2.0 9 9.0 9.0 12.0 3.0 17 17.0 17.0 29.0 4.0 52 52.0 52.0 81.0 5.0 19 19.0 19.0 100.0 Total 100 100.0 100.0

PI6probable


Valid

1.0 4 4.0 4.0 4.0 2.0 8 8.0 8.0 12.0 3.0 11 11.0 11.0 23.0 4.0 47 47.0 47.0 70.0 5.0 30 30.0 30.0 100.0 Total 100 100.0 100.0

PI7probable Frequency Percent Valid Percent Cumulative Percent

Valid

1.0 2 2.0 2.0 2.0 2.0 15 15.0 15.0 17.0 3.0 22 22.0 22.0 39.0 4.0 36 36.0 36.0 75.0 5.0 25 25.0 25.0 100.0 Total 100 100.0 100.0

PI8probable Frequency Percent Valid Percent Cumulative Percent

Valid

1.0 2 2.0 2.0 2.0 2.0 8 8.0 8.0 10.0 3.0 23 23.0 23.0 33.0 4.0 38 38.0 38.0 71.0 5.0 29 29.0 29.0 100.0 Total 100 100.0 100.0



FREQUENCIES VARIABLES=PV1emotional PV2emotional PV3emotional PV4social PV5social PV6quality PV7quality PV8price PV9price PV10price /ORDER=ANALYSIS. Frequencies


Input



as missing.


Syntax

FREQUENCIES VARIABLES=PV1emotional PV2emotional PV3emotional PV4social PV5social PV6quality PV7quality PV8price PV9price PV10price /ORDER=ANALYSIS.


[DataSet1]

Statistics PV1emoti

onal PV2emoti

onal PV3emoti

onal PV4so

cial PV5so

cial PV6qua

lity PV7qua

lity PV8pri

ce PV9pri

ce PV10pr

ice

N Valid 100 100 100 100 100 100 100 99 100 100 Missing

0 0 0 0 0 0 0 1 0 0

Frequency Table

PV1emotional Frequency Percent Valid Percent Cumulative Percent

Valid

1.0 2 2.0 2.0 2.0 2.0 10 10.0 10.0 12.0 3.0 21 21.0 21.0 33.0 4.0 51 51.0 51.0 84.0 5.0 16 16.0 16.0 100.0 Total 100 100.0 100.0

PV2emotional


Valid

2.0 16 16.0 16.0 16.0 3.0 34 34.0 34.0 50.0 4.0 40 40.0 40.0 90.0 5.0 10 10.0 10.0 100.0 Total 100 100.0 100.0

PV3emotional Frequency Percent Valid Percent Cumulative Percent

Valid

1.0 2 2.0 2.0 2.0 2.0 15 15.0 15.0 17.0 3.0 30 30.0 30.0 47.0 4.0 42 42.0 42.0 89.0 5.0 11 11.0 11.0 100.0



Total 100 100.0 100.0

PV4social Frequency Percent Valid Percent Cumulative Percent

Valid

1.0 1 1.0 1.0 1.0 2.0 4 4.0 4.0 5.0 3.0 18 18.0 18.0 23.0 4.0 44 44.0 44.0 67.0 5.0 33 33.0 33.0 100.0 Total 100 100.0 100.0

PV5social Frequency Percent Valid Percent Cumulative Percent

Valid

2.0 7 7.0 7.0 7.0 3.0 13 13.0 13.0 20.0 4.0 39 39.0 39.0 59.0 5.0 41 41.0 41.0 100.0 Total 100 100.0 100.0

PV6quality


Valid

1.0 2 2.0 2.0 2.0 2.0 16 16.0 16.0 18.0 3.0 27 27.0 27.0 45.0 4.0 36 36.0 36.0 81.0 5.0 19 19.0 19.0 100.0 Total 100 100.0 100.0

PV7quality


Valid

1.0 15 15.0 15.0 15.0 2.0 26 26.0 26.0 41.0 3.0 33 33.0 33.0 74.0 4.0 18 18.0 18.0 92.0 5.0 8 8.0 8.0 100.0 Total 100 100.0 100.0

PV8price Frequency Percent Valid Percent Cumulative Percent

Valid

2.0 7 7.0 7.1 7.1 3.0 12 12.0 12.1 19.2 4.0 56 56.0 56.6 75.8 5.0 24 24.0 24.2 100.0 Total 99 99.0 100.0

Missing System 1 1.0 Total 100 100.0

PV9price


Valid

2.0 3 3.0 3.0 3.0 3.0 11 11.0 11.0 14.0 4.0 33 33.0 33.0 47.0 5.0 53 53.0 53.0 100.0 Total 100 100.0 100.0

PV10price Frequency Percent Valid Percent Cumulative Percent Valid 2.0 5 5.0 5.0 5.0



3.0 36 36.0 36.0 41.0 4.0 44 44.0 44.0 85.0 5.0 15 15.0 15.0 100.0 Total 100 100.0 100.0

FACTOR /VARIABLES PV1emotional PV2emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /MISSING LISTWISE /ANALYSIS PV1emotional PV2emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /PRINT INITIAL KMO AIC EXTRACTION /CRITERIA MINEIGEN(1) ITERATE(25) /EXTRACTION PC /ROTATION NOROTATE /METHOD=CORRELATION. FACTOR /VARIABLES PV1emotional PV2emotional PV3emotional PV4social PV5social PV6quality PV7quality PV8price PV9price PV10price /MISSING LISTWISE /ANALYSIS PV1emotional PV2emotional PV3emotional PV4social PV5social PV6quality PV7quality PV8price PV9price PV10price /PRINT INITIAL KMO AIC EXTRACTION /CRITERIA MINEIGEN(1) ITERATE(25) /EXTRACTION PC /ROTATION NOROTATE /METHOD=CORRELATION. FIRST TEST Factor Analysis [DataSet1]



Anti-image Matrices

PV1emotional

PV2emotional

PV3emotional

PV4social

PV5social

PV6quality

PV7quality

PV8price

PV9price

PV10price


PV1emotional

.583 -.125 .009 .027 -.072 -.066 .005 .071 -.010 -.070

PV2emotional

-.125 .308 -.136 -.011 .015 -.007 -.036 -.006 -.046 -.066

PV3emotional

.009 -.136 .311 -.007 -.005 -.104 -.050 -.004 -.019 .034

PV4social

.027 -.011 -.007 .612 -.101 -.048 -.024 .024 -.142 -.066

PV5social

-.072 .015 -.005 -.101 .678 -.073 .034 -.049 -.074 -.020

PV6quality

-.066 -.007 -.104 -.048 -.073 .277 -.113 -.032 .044 -.030

PV7quality

.005 -.036 -.050 -.024 .034 -.113 .335 -.046 .097 -.103

PV8price .071 -.006 -.004 .024 -.049 -.032 -.046 .408 -.240 -.084 PV9price -.010 -.046 -.019 -.142 -.074 .044 .097 -.240 .429 -.017 PV10price

-.070 -.066 .034 -.066 -.020 -.030 -.103 -.084 -.017 .410


PV1emotional

.904a -.294 .022 .046 -.115 -.165 .012 .145 -.021 -.143

PV2emotional

-.294 .893a -.440 -.026 .034 -.024 -.111 -.016 -.127 -.185



PV3emotional

.022 -.440 .884a -.017 -.011 -.355 -.154 -.012 -.053 .094

PV4social

.046 -.026 -.017 .920a -.156 -.117 -.053 .049 -.277 -.133

PV5social

-.115 .034 -.011 -.156 .929a -.169 .071 -.094 -.136 -.039

PV6quality

-.165 -.024 -.355 -.117 -.169 .889a -.370 -.096 .128 -.088

PV7quality

.012 -.111 -.154 -.053 .071 -.370 .879a -.124 .256 -.278

PV8price .145 -.016 -.012 .049 -.094 -.096 -.124 .817a -.574 -.205 PV9price -.021 -.127 -.053 -.277 -.136 .128 .256 -.574 .706a -.040 PV10price

-.143 -.185 .094 -.133 -.039 -.088 -.278 -.205 -.040 .924a


Communalities Initial Extraction PV1emotional 1.000 .514 PV2emotional 1.000 .745 PV3emotional 1.000 .732 PV4social 1.000 .519 PV5social 1.000 .451 PV6quality 1.000 .794 PV7quality 1.000 .747 PV8price 1.000 .716 PV9price 1.000 .812 PV10price 1.000 .654 Extraction Method: Principal Component Analysis.

Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative % 1 5.257 52.566 52.566 5.257 52.566 52.566 2 1.426 14.259 66.825 1.426 14.259 66.825 3 .701 7.009 73.833 4 .621 6.211 80.044 5 .556 5.565 85.609 6 .475 4.755 90.364 7 .321 3.209 93.573 8 .232 2.315 95.888 9 .227 2.269 98.157 10 .184 1.843 100.000 Extraction Method: Principal Component Analysis.

Component Matrixa Component

1 2 PV1emotional .646 -.310 PV2emotional .844 -.182 PV3emotional .819 -.247 PV4social .647 .317 PV5social .589 .322 PV6quality .844 -.286 PV7quality .773 -.386 PV8price .678 .507 PV9price .518 .737 PV10price .808 -.030 Extraction Method: Principal Component Analysis. a. 2 components extracted.



FACTOR /VARIABLES PV1emotional PV2emotional PV3emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /MISSING LISTWISE /ANALYSIS PV1emotional PV2emotional PV3emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /PRINT INITIAL KMO AIC EXTRACTION /CRITERIA MINEIGEN(1) ITERATE(25) /EXTRACTION PC /ROTATION NOROTATE /METHOD=CORRELATION. Factor Analysis [DataSet1]



Anti-image Matrices PV1emoti

onal PV2emoti

onal PV3emoti

onal PV4so

cial PV5so

cial PV6qu

ality PV7qu

ality PV8pr

ice PV10pr

ice


PV1emotional

.583 -.128 .009 .026 -.075 -.066 .008 .097 -.071

PV2emotional

-.128 .313 -.141 -.029 .008 -.002 -.028 -.048 -.069

PV3emotional

.009 -.141 .312 -.015 -.008 -.104 -.049 -.023 .033

PV4social .026 -.029 -.015 .663 -.138 -.037 .009 -.089 -.078 PV5social -.075 .008 -.008 -.138 .691 -.068 .055 -.138 -.024 PV6quality

-.066 -.002 -.104 -.037 -.068 .282 -.134 -.011 -.028

PV7quality

.008 -.028 -.049 .009 .055 -.134 .358 .014 -.106

PV8price .097 -.048 -.023 -.089 -.138 -.011 .014 .608 -.140 PV10price -.071 -.069 .033 -.078 -.024 -.028 -.106 -.140 .411


PV1emotional

.898a -.299 .021 .041 -.119 -.164 .018 .162 -.144

PV2emotional

-.299 .886a -.451 -.064 .017 -.007 -.082 -.109 -.192

PV3emotional

.021 -.451 .880a -.033 -.018 -.351 -.145 -.052 .092

PV4social .041 -.064 -.033 .935a -.204 -.085 .019 -.140 -.150 PV5social -.119 .017 -.018 -.204 .893a -.154 .111 -.212 -.045 PV6quality

-.164 -.007 -.351 -.085 -.154 .887a -.420 -.028 -.084

PV7quality

.018 -.082 -.145 .019 .111 -.420 .892a .029 -.277

PV8price .162 -.109 -.052 -.140 -.212 -.028 .029 .887a -.279 PV10price -.144 -.192 .092 -.150 -.045 -.084 -.277 -.279 .907a


Communalities Initial Extraction PV1emotional 1.000 .544 PV2emotional 1.000 .760 PV3emotional 1.000 .742 PV4social 1.000 .596 PV5social 1.000 .601 PV6quality 1.000 .780 PV7quality 1.000 .721



PV8price 1.000 .637 PV10price 1.000 .658 Extraction Method: Principal Component Analysis.


Total % of Variance Cumulative % Total % of Variance Cumulative % 1 5.031 55.899 55.899 5.031 55.899 55.899 2 1.007 11.192 67.091 1.007 11.192 67.091 3 .692 7.690 74.781 4 .570 6.329 81.110 5 .527 5.861 86.971 6 .439 4.878 91.849 7 .321 3.566 95.415 8 .228 2.536 97.950 9 .184 2.050 100.000 Extraction Method: Principal Component Analysis.

Component Matrixa

Component 1 2

PV1emotional .663 -.323 PV2emotional .850 -.191 PV3emotional .833 -.218 PV4social .625 .452 PV5social .572 .523 PV6quality .867 -.171 PV7quality .804 -.272 PV8price .634 .485 PV10price .810 .045 Extraction Method: Principal Component Analysis. a. 2 components extracted.

FACTOR /VARIABLES PV1emotional PV2emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /MISSING LISTWISE /ANALYSIS PV1emotional PV2emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /PRINT INITIAL KMO AIC EXTRACTION /CRITERIA MINEIGEN(1) ITERATE(25) /EXTRACTION PC /ROTATION NOROTATE /METHOD=CORRELATION. Second Test Factor Analysis


Input


Missing Value Handling Definition of Missing MISSING=EXCLUDE: User-defined missing values are treated as missing.



Cases Used LISTWISE: Statistics are based on cases with no missing values for any variable used.

Syntax

FACTOR /VARIABLES PV1emotional PV2emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /MISSING LISTWISE /ANALYSIS PV1emotional PV2emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /PRINT INITIAL KMO AIC EXTRACTION /CRITERIA MINEIGEN(1) ITERATE(25) /EXTRACTION PC /ROTATION NOROTATE /METHOD=CORRELATION.

Resources Processor Time 00:00:00.02 Elapsed Time 00:00:00.00 Maximum Memory Required 9264 (9.047K) bytes

[DataSet1]



Anti-image Matrices PV1emotio

nal PV2emotio

nal PV4soci

al PV5soci

al PV6quali

ty PV7quali

ty PV8pri

ce PV10pri

ce


PV1emotional

.583 -.156 .026 -.075 -.072 .010 .098 -.072

PV2emotional

-.156 .393 -.045 .005 -.071 -.063 -.073 -.068

PV4social .026 -.045 .664 -.139 -.048 .007 -.090 -.077 PV5social -.075 .005 -.139 .692 -.081 .055 -.139 -.023 PV6quality -.072 -.071 -.048 -.081 .321 -.175 -.022 -.020 PV7quality .010 -.063 .007 .055 -.175 .366 .010 -.104 PV8price .098 -.073 -.090 -.139 -.022 .010 .610 -.139 PV10price -.072 -.068 -.077 -.023 -.020 -.104 -.139 .414


PV1emotional

.872a -.325 .042 -.119 -.167 .021 .164 -.147

PV2emotional

-.325 .904a -.088 .009 -.198 -.167 -.149 -.169

PV4social .042 -.088 .922a -.205 -.103 .014 -.142 -.147 PV5social -.119 .009 -.205 .877a -.171 .109 -.214 -.043 PV6quality -.167 -.198 -.103 -.171 .862a -.509 -.049 -.055 PV7quality .021 -.167 .014 .109 -.509 .843a .022 -.267 PV8price .164 -.149 -.142 -.214 -.049 .022 .868a -.276 PV10price -.147 -.169 -.147 -.043 -.055 -.267 -.276 .905a


Communalities Initial Extraction PV1emotional 1.000 .448 PV2emotional 1.000 .695 PV4social 1.000 .416 PV5social 1.000 .352 PV6quality 1.000 .729 PV7quality 1.000 .635 PV8price 1.000 .426 PV10price 1.000 .687



Extraction Method: Principal Component Analysis.


Total % of Variance Cumulative % Total % of Variance Cumulative % 1 4.387 54.841 54.841 4.387 54.841 54.841 2 .971 12.132 66.973 3 .688 8.599 75.572 4 .569 7.118 82.690 5 .504 6.297 88.987 6 .353 4.411 93.398 7 .311 3.887 97.285 8 .217 2.715 100.000 Extraction Method: Principal Component Analysis.

Component Matrixa

Component 1

PV1emotional .669 PV2emotional .833 PV4social .645 PV5social .594 PV6quality .854 PV7quality .797 PV8price .652 PV10price .829 Extraction Method: Principal Component Analysis. a. 1 components extracted.

FACTOR /VARIABLES PV1emotional PV2emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /MISSING LISTWISE /ANALYSIS PV1emotional PV2emotional PV4social PV5social PV6quality PV7quality PV8price PV10price /PRINT INITIAL KMO AIC EXTRACTION /CRITERIA MINEIGEN(1) ITERATE(25) /EXTRACTION PC /ROTATION NOROTATE /SAVE REG(ALL) /METHOD=CORRELATION. Third Test Factor Analysis [DataSet1]





Anti-image Matrices

PV1emotional

PV2emotional

PV4social

PV5social

PV6quality

PV7quality

PV8price

PV10price


PV1emotional

.583 -.156 .026 -.075 -.072 .010 .098 -.072

PV2emotional

-.156 .393 -.045 .005 -.071 -.063 -.073 -.068

PV4social .026 -.045 .664 -.139 -.048 .007 -.090 -.077 PV5social -.075 .005 -.139 .692 -.081 .055 -.139 -.023 PV6quality -.072 -.071 -.048 -.081 .321 -.175 -.022 -.020 PV7quality .010 -.063 .007 .055 -.175 .366 .010 -.104 PV8price .098 -.073 -.090 -.139 -.022 .010 .610 -.139 PV10price -.072 -.068 -.077 -.023 -.020 -.104 -.139 .414


PV1emotional

.872a -.325 .042 -.119 -.167 .021 .164 -.147

PV2emotional

-.325 .904a -.088 .009 -.198 -.167 -.149 -.169

PV4social .042 -.088 .922a -.205 -.103 .014 -.142 -.147 PV5social -.119 .009 -.205 .877a -.171 .109 -.214 -.043 PV6quality -.167 -.198 -.103 -.171 .862a -.509 -.049 -.055 PV7quality .021 -.167 .014 .109 -.509 .843a .022 -.267 PV8price .164 -.149 -.142 -.214 -.049 .022 .868a -.276 PV10price -.147 -.169 -.147 -.043 -.055 -.267 -.276 .905a


Communalities Initial Extraction PV1emotional 1.000 .448 PV2emotional 1.000 .695 PV4social 1.000 .416 PV5social 1.000 .352 PV6quality 1.000 .729 PV7quality 1.000 .635 PV8price 1.000 .426 PV10price 1.000 .687 Extraction Method: Principal Component Analysis.


Total % of Variance Cumulative % Total % of Variance Cumulative % 1 4.387 54.841 54.841 4.387 54.841 54.841 2 .971 12.132 66.973 3 .688 8.599 75.572 4 .569 7.118 82.690 5 .504 6.297 88.987 6 .353 4.411 93.398 7 .311 3.887 97.285 8 .217 2.715 100.000 Extraction Method: Principal Component Analysis.

Component Matrixa

Component 1

PV1emotional .669 PV2emotional .833 PV4social .645 PV5social .594 PV6quality .854 PV7quality .797 PV8price .652 PV10price .829 Extraction Method: Principal Component Analysis. a. 1 components extracted.



FREQUENCIES VARIABLES=JenisKelamin Usia Pekerjaan JikaYAsudahberapalamaandasebagaimemberdiwwwkaskusco JikaYAberapakalipembelian /FORMAT=DFREQ /ORDER=ANALYSIS. Respondents Descriptive Frequencies


Input



as missing.


Syntax

FREQUENCIES VARIABLES=JenisKelamin Usia Pekerjaan JikaYAsudahberapalamaandasebagaimemberdiwwwkaskusco JikaYAberapakalipembelian /FORMAT=DFREQ /ORDER=ANALYSIS.


[DataSet1]

Statistics JenisKela

min Usia

Pekerjaan

JikaYAsudahberapalamaandasebagaimemberdiwwwkaskusco

JikaYAberapakalipembelian

N Valid 100 10

0 100 100 100

Missing

0 0 0 0 0

Frequency Table

JenisKelamin Frequency Percent Valid Percent Cumulative Percent

Valid Laki-laki 71 71.0 71.0 71.0 Perempuan 29 29.0 29.0 100.0 Total 100 100.0 100.0

Usia Frequency Percent Valid Percent Cumulative Percent

Valid

> 26 Tahun 31 31.0 31.0 31.0 20 - 22 Tahun 31 31.0 31.0 62.0 23 - 25 Tahun 25 25.0 25.0 87.0 17 - 19 Tahun 13 13.0 13.0 100.0 Total 100 100.0 100.0

Pekerjaan


Valid Mahasiswa 45 45.0 45.0 45.0 Pegawai Swasta 17 17.0 17.0 62.0



Wirausaha 13 13.0 13.0 75.0 Pegawai 6 6.0 6.0 81.0 Pegawai Negeri 3 3.0 3.0 84.0 Broker 2 2.0 2.0 86.0 Guru 2 2.0 2.0 88.0 Satpam 2 2.0 2.0 90.0 Assistant Manager 1 1.0 1.0 91.0 Creative Designer 1 1.0 1.0 92.0 Dokter 1 1.0 1.0 93.0 freelance 1 1.0 1.0 94.0 IT 1 1.0 1.0 95.0 Junior Trader 1 1.0 1.0 96.0 Pekerja musik 1 1.0 1.0 97.0 skrg nganggur,kmrn kontrak BPS

1 1.0 1.0 98.0

Sopir 1 1.0 1.0 99.0 Store manager 1 1.0 1.0 100.0 Total 100 100.0 100.0

JikaYAsudahberapalamaandasebagaimemberdiwwwkaskusco Frequency Percent Valid Percent Cumulative Percent

Valid > 2 Tahun 61 61.0 61.0 61.0 2 Tahun 39 39.0 39.0 100.0 Total 100 100.0 100.0

JikaYAberapakalipembelian Frequency Percent Valid Percent Cumulative Percent

Valid

1 52 52.0 52.0 52.0 2 25 25.0 25.0 77.0 3 7 7.0 7.0 84.0 4 4 4.0 4.0 88.0 5 4 4.0 4.0 92.0 6 3 3.0 3.0 95.0 > 10 2 2.0 2.0 97.0 >30 1 1.0 1.0 98.0 10 1 1.0 1.0 99.0 17 1 1.0 1.0 100.0 Total 100 100.0 100.0

Reliability of Variable X


Input

Data /Users/fajarprasetya/Desktop/sgu/Thesis almost done/Data Analysis.sav


Matrix Input /Users/fajarprasetya/Desktop/sgu/Thesis almost done/Data Analysis.sav




as missing.

Cases Used Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY /VARIABLES=PV1emotional PV2emotional PV3emotional PV4social PV5social PV6quality PV7quality PV8price PV9price PV10price /SCALE('ALL VARIABLES') ALL /MODEL=ALPHA.


[DataSet2] Scale: ALL VARIABLES

Case Processing Summary N %

Cases Valid 99 99.0 Excludeda 1 1.0 Total 100 100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics Cronbach's Alpha N of Items

.895 10 Reliability [DataSet2] Scale: ALL VARIABLES

Case Processing Summary N %

Cases Valid 100 100.0 Excludeda 0 .0 Total 100 100.0

a. Listwise deletion based on all variables in the procedure.

a study about the influence of ‘recommended seller’ as perceived value towards purchase...

Documents