the profitab ility determinants of conventional …
TRANSCRIPT
THE PROFITABILITY DETERMINANTS OF CONVENTIONAL
AND ISLAMIC BANKS IN INDONESIA
By
RAHMI ZUHA EMDI
014201300193
A Skripsi Presented to the
Faculty of Business President University
In Partial Fulfillment of the Requirements for
Bachelor Degree in Business, Major in Management
December 2016
V
ABSTRACT
The main object of this study is to investigate the internal factors that influence the profitability between conventional banks and Islamic banks in Indonesia over the quarterly period 2011-2016. The study involved all five conventional commercial banks and five Islamic commercial banks by using secondary data from Financial Services Authority of Indonesia (OJK). The test was adopted to examine ROA (Return On Asset) as the dependent variable and CAR (Capital Adequacy Ratio), LDR/FDR (Loan to Deposit Ratio/Financing to Deposit Ratio), NPL/NPF (Non-Performing Loan/Non-Performing Financing) as the independent variables. The result of multiple linear regression analysis indicated there was a positive significant impact of CAR and LDR on ROA in conventional bank. Meanwhile for Islamic banks found that NPF was significant but negatively impact on ROA. On the other hand, CAR and FDR had no significant effect on ROA of Islamic banks. Further the study revealed the significant different of each variables between conventional banks and Islamic banks in Indonesia.
Keyword: ROA, CAR, LDR, NPL, FDR, NPF, Conventional Banks, Islamic Banks
VI
ACKNOWLEDGEMENT
In the name of Allah, the Most Gracious and the Most Merciful
A deepest gratitude to Allah SWT for giving me strengths, health, guidance and His countless
blessing for me in all the time of my life especially in completing this research. Special
appreciation is delivered to my skripsi adviser, Anita Munir, S.E., MFin., for the patience, advice,
guidance and support. The success of this skripsi also depends on her rewarding suggestions and
comments during the research period. My appreciation also to lecturers and office staffs of
President University for their supports, teaching and facilities in completing this skripsi.
My gratefulness to my beloved parents, Mr. Erwandi and Mrs. Elmi Husni for their prayers,
endless love and encouragement in order their daughter will be able to graduate. Thank you to my
beloved brother, Arnsohio Muhammad Emdi for his prayers and support.
My special thanks to Ms. Shinta Havidz and Mr. Purwanto for the teaching and advice during the
arrangement of this skripsi. Sincere also presented to:
Dhani Wasistha Parussa, Ulfa Dwinda Umar, Rayang Amiriyanti, Riani Septi Hertini, Putri
Dini Azizi, Riska Nurhayati, Rahma Yustika Dewi, Nurfaeisyah, Tri Wulan Sari, Sindy Mega
Rosita, Rika Melyana, Rima Sera, Safira Rizqia for their love, understanding, kindness, and
moral support during my study. Thank you for the amazing memories and never-ending
friendship.
Islamic Banking and Finance mates for the unforgettable moments that we have spent together
during the study.
y in President
University.
The kindness means a lot to me to those who indirectly contributed in my research. Thank you
very much.
Cikarang, Indonesia, December 16th 2016
Rahmi Zuha Emdi
VII
TABLE OF CONTENTS
TITLE PAGE ................................................................................................................................... I
PANEL OF EXAMINERS ............................................................................................................. II
SKRIPSI ADVISER ..................................................................................................................... III
RECOMMENDATION LETTER ................................................................................................ III
DECLARATION OF ORIGINALITY ......................................................................................... IV
ABSTRACT ....................................................................................................................................V
ACKNOWLEDGEMENT ............................................................................................................ VI
TABLE OF CONTENTS ............................................................................................................. VII
LIST OF TABLES ........................................................................................................................ XI
LIST OF FIGURES ..................................................................................................................... XII
CHAPTER I .................................................................................................................................... 1
INTRODUCTION .......................................................................................................................... 1
1.1. Background of Study ........................................................................................................ 1
Table 1.1 Data of ROA in conventional and Islamic banks period 2011-2016....................... 2
Table 1.2 Data of Financial Ratio of Conventional and Islamic Banks: ................................. 3
Problem Identification ................................................................................................................. 5
Statement of Problem .................................................................................................................. 6
Research Objective ...................................................................................................................... 6
1.2 Significance of the Study ...................................................................................................... 7
1.3. Scope and Limitation of the Study ....................................................................................... 7
1.4 Definition of Terms ............................................................................................................... 8
CHAPTER II ................................................................................................................................... 9
LITERATURE REVIEW ............................................................................................................... 9
VIII
2.1. Introduction .......................................................................................................................... 9
2.1.1 Overview on Bank .......................................................................................................... 9
2.2. Return on Assets................................................................................................................... 9
2.3. Capital Adequacy Ratio ..................................................................................................... 10
2.4. Non-Performing Loan and Non-Performing Financing ..................................................... 11
2.5. Loan to Deposit Ratio and Financing to Deposit Ratio ..................................................... 12
2.6. Research Gaps .................................................................................................................... 12
CHAPTER III ............................................................................................................................... 14
RESEARCH METHODOLOGY.................................................................................................. 14
3.1. Introduction ........................................................................................................................ 14
3.2. Theoretical Framework ...................................................................................................... 14
3.3. Hypothesis .......................................................................................................................... 15
3.4. Operational Definitions of Variables ................................................................................. 15
3.5. Instrument........................................................................................................................... 16
3.6. Sampling............................................................................................................................. 16
3.7. Data Analysis Method ........................................................................................................ 17
3.7.1. Descriptive Statistics Analysis .................................................................................... 17
3.7.2. Assumption Classic Test ............................................................................................. 17
3.7.3. Multiple Linear Regression ......................................................................................... 18
3.7.4. Hypothesis Testing ...................................................................................................... 19
CHAPTER IV ............................................................................................................................... 23
RESULT AND DISCUSSION ..................................................................................................... 23
4.1 Gathered Sampling Data ..................................................................................................... 23
4.2 Result of Data Analysis ....................................................................................................... 23
4.2.1 Descriptive Statistics .................................................................................................... 23
IX
4.3 Assumption Classic Test Result .......................................................................................... 26
4.3.1 Normality Test .............................................................................................................. 26
4.3.2 Multicollinearity Test ................................................................................................... 26
4.3.3 Heteroscedasticity Test ................................................................................................. 27
4.3.4 Autocorrelation Test ..................................................................................................... 27
4.4 Multiple Linear Regression ................................................................................................. 27
4.5 Hypothesis Testing .............................................................................................................. 28
4.5.1 Significant Simultaneous Test (F-Test) ........................................................................ 28
4.5.2 Significant Partial Test (T-Test) ................................................................................... 29
4.5.3 Coefficient Multiple Determination Test (R2) .............................................................. 29
4.5.4 Group Statistics Result ................................................................................................. 30
4.5.5 Independent Sample Test.............................................................................................. 30
4.6 Interpretation of Result........................................................................................................ 32
4.6.1 The influence of Capital Adequacy Ratio toward the Return on Asset........................ 32
4.6.2 The Influence of Loan to Deposit Ratio and Financing to Deposit Ratio toward Return
on Asset ................................................................................................................................. 33
4.6.3 The influence of Non-Performing Loan or Non-Performing Financing toward ROA . 34
4.6.4 The influence of Capital Adequacy Ratio, Loan to Deposit Ratio/Financing to Deposit
Ratio, Non-Performing Loan/Non-Performing Financing toward Return on Asset .............35
CHAPTER V ................................................................................................................................ 36
CONCLUSION AND RECOMMENDATION ............................................................................ 36
5.1 Conclusion ........................................................................................................................... 36
5.2 Recommendation ................................................................................................................. 37
REFERENCES ............................................................................................................................. 39
APPENDIX ................................................................................................................................... 42
Table 2.1. for Research Gaps ........................................................................................................ 42
X
Table 3.1. List of Banks that used (in million) ............................................................................. 43
Table 4.1. Sampling Data.............................................................................................................. 43
Table 4.2. Descriptive Data for Conventional Banks ................................................................... 44
Table 4.3. Descriptive Data for Islamic Banks ............................................................................. 44
Table 4.4. Multicollinearity Test for Conventional Banks ........................................................... 45
Table 4.5. Multicollinearity Test for Islamic Banks ..................................................................... 45
Table 4.6. Durbin-Watson Result for Conventional Banks .......................................................... 45
Table 4.7. Durbin-Watson Result for Islamic Banks .................................................................... 46
Table 4.8. Multiple Linear Regression Result for Conventional Banks ....................................... 46
Table 4.9. Multiple Linear Regression Result for Islamic Banks ................................................. 46
Table 4.10. Simultaneous Result for Conventional Banks ........................................................... 47
Table 4.11. Simultaneous Result for Islamic Banks ..................................................................... 47
Table 4.12. Significant Partial Test Result of Conventional Banks ............................................. 47
Table 4.13. Significant Partial Test Result of Islamic Banks ....................................................... 48
Table 4.15. Coefficient Multiple Determination Test Result for Conventional Banks ................ 48
Table 4.16. Coefficient Multiple Determination Test Result for Islamic Banks .......................... 48
Table 4.17. Group Statistics Test Result ....................................................................................... 49
Table 4.18. Independent Sample Test Result ................................................................................ 50
Figure 4.1. Histogram for Conventional Banks ............................................................................ 51
Figure 4.2. Histogram for Islamic Banks ...................................................................................... 51
Figure 4.3. P-Plot for Conventional Banks ................................................................................... 52
Figure 4.4. P-Plot for Islamic Banks ............................................................................................. 52
Figure 4.5. Scatterplot Result for Conventional Banks ................................................................ 53
Figure 4.6. Scatterplot for Islamic Banks ..................................................................................... 53
XI
LIST OF TABLES
Table 2.1. for Research Gaps ........................................................................................................ 42
Table 3.1. List of Banks that used (in million) ............................................................................. 43
Table 4.1. Sampling Data.............................................................................................................. 43
Table 4.2. Descriptive Data for Conventional Banks ................................................................... 44
Table 4.3. Descriptive Data for Islamic Banks ............................................................................. 44
Table 4.4. Multicollinearity Test for Conventional Banks ........................................................... 45
Table 4.5. Multicollinearity Test for Islamic Banks ..................................................................... 45
Table 4.6. Durbin-Watson Result for Conventional Banks .......................................................... 45
Table 4.7. Durbin-Watson Result for Islamic Banks .................................................................... 46
Table 4.8. Multiple Linear Regression Result for Conventional Banks ....................................... 46
Table 4.9. Multiple Linear Regression Result for Islamic Banks ................................................. 46
Table 4.10. Simultaneous Result for Conventional Banks ........................................................... 47
Table 4.11. Simultaneous Result for Islamic Banks ..................................................................... 47
Table 4.12. Significant Partial Test Result of Conventional Banks ............................................. 47
Table 4.13. Significant Partial Test Result of Islamic Banks ....................................................... 48
Table 4.15. Coefficient Multiple Determination Test Result for Conventional Banks ................ 48
Table 4.16. Coefficient Multiple Determination Test Result for Islamic Banks .......................... 48
Table 4.17. Group Statistics Test Result ....................................................................................... 49
Table 4.18. Independent Sample Test Result ................................................................................ 50
XII
LIST OF FIGURES
Figure 4.1. Histogram for Conventional Banks ............................................................................ 51
Figure 4.2. Histogram for Islamic Banks ...................................................................................... 51
Figure 4.3. P-Plot for Conventional Banks ................................................................................... 52
Figure 4.4. P-Plot for Islamic Banks ............................................................................................. 52
Figure 4.5. Scatterplot Result for Conventional Banks ................................................................ 53
Figure 4.6. Scatterplot for Islamic Banks ..................................................................................... 53
Page 1 of 53
CHAPTER I
INTRODUCTION
1.1. Background of Study
Based on Law No. 10 of 1998 bank as an intermediary’s institution has an important role
among parties who have the funds with the parties who need the funds. Bank compiles the
fund from the surplus unit and distributes the fund to the deficit unit in order to improve the
standard living of people. In running the business, the bank divided into Conventional Bank
and Islamic Bank which is run their business in the Syariah principle. Conventional banking
system is the one that operating based on the interest-based banking. While Islamic bank is
an interest free banking system (Ramlan & Adnan 2015).
Both of conventional and Islamic banks are profit-making organizations which has aim to
gain profit in their business activities. The differences between conventional and Islamic
banks are in Islamic banks it is prohibited to trade in riba or anything business activities that
is not compliance with Syariah principles, but in contrast conventional banks has no
restrictions (Khir et al. 2008). Conventional and Islamic banks create a competition to satisfy
their customers with their own expectations and also for the long term benefit in the term of
the economy.
Banks have to maintain their financial performance for the public trust. There is a standard of
the banking industry to know or evaluate the health, it can be seen from the financial statement
of the bank that published periodically. Financial statement is a “road map” that can tells
about the banks conditions in the past, current, and perhaps can predict for the future.
Performance means how adequately a company meets the needs of its owner, employees,
depositors, and borrowing customers which is must to keep in the government regulation from
the company’s activities (Rose & Hudgins, 2008). This report is very useful to determine the
condition of the bank especially for owners, management, government, and the society
(Amelia, 2015). Based on BI regulation No.6/10/PBI/2004 on 12th April 2004 stated that
CAMELS (Capital, Asset Quality, Management, Earning, Liquidity, Sensitivity to Market
Risk) is the analysis to measure the health of the banks. The aspects of the analysis by using
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the financial ratio of the bank. Capital covered by CAR, Asset Quality covered by NPL/NPF,
Management covered by application system of risk management, Earnings covered by ROA,
Liquidity covered by LDR/FDR and Sensitivity to Market Risk covered by the assessment of
the capital reserve which can cover the fluctuation of interest rate.
ROA is a ratio that can be used to measure how profitable the company (Siahaan &
Anantadjaya 2013). Researcher wants to measure the financial performance by using the
financial ratio of the bank. Profitability is the most important indicator to measure the
performance or operation of the bank. In determined the bank’s health, Central Bank (BI)
more concerned in the ROA rather than ROE because BI more focus to measure the
profitability of the bank in the term of the asset which is the fund comes from the deposits of
the customers, so ROA is used to measure the bank’s profitability as a whole (Hakim and
Rafsanjani, 2015). ROA shows how much profit that the bank will get for each Rp 1 in the
assets that owned by the company (Siahaan & Anantadjaya 2013). The greater ROA of a bank,
the higher profit that the bank’s achieved and the better bank’s position to use the asset. Based
on Bank Indonesia Circular Letter No. 6/9/PBI/2004 the standard of ROA is 1.5%. See from
the table below:
Table 1.1 Data of ROA in conventional and Islamic banks period 2011-2016
NO Type of Bank ROA
2011 2012 2013 2014 2015 2016
1 Conventional Banks 1.91% 2.12% 2.44% 1.81% 1.53% 1.47%
2 Islamic Banks 1.27% 2.26% 1.45% 0.67% 0.77% 1.27%
Source: Data Published by 10 banks (5 Conventional and 5 Islamic Banks) from OJK website
Mostly for the conventional bank, the ratio of ROA was good enough which was more than
1.5% although in 2014-2016Q2 decreased into 1.47%. While for the Islamic banks the ratio
of ROA still fluctuated but still keep improving to achieve 1.5% point. Researcher can use the
data to analyze about the factor that affect ROA. It can be seen from the financial report of
each bank. Information about the financial position, financial performance, and other
information can be seen from the financial report (Ayuningrum, 2011).
In this study aspect of capital asset by the CAR (Capital Adequacy Ratio), asset quality aspects
by NPL/NPF (Non-Performing Loan/ Financing), the liquidity aspect by LDR/FDR
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(Loan/Financing to Deposit Ratio) and for the profitability by ROA (Return on Asset). That
financial ratio is used to know how the influence of CAR, NPL/NPF, LDR/FDR toward ROA
in conventional and Islamic banks in Indonesia period 2011Q1-2016Q2. See the table below
to know the data of each ratio that used.
Table 1.2 Data of Financial Ratio of Conventional and Islamic Banks:
Ratio Year
Average 2011 2012 2013 2014 2015 2016
CAR 20.28% 19.85% 44.96% 27.26% 22.18% 23.52%
LDR 82.71% 87.35% 96.05% 89.46% 99.23% 90.26%
NPL 1.46% 0.65% 0.92% 1.06% 2.17% 2.63%
ROA 1.91% 2.12% 2.44% 1.81% 1.53% 1.47%
Ratio Year
Average 2011 2012 2013 2014 2015 2016
CAR 24.31% 16.60% 16.48% 17.97% 16.35% 16.95%
FDR 100.08% 98.99% 96.86% 91.50% 92.20% 91.90%
NPF 1.79% 1.32% 1.48% 2.38% 2.73% 2.99%
ROA 1.27% 2.26% 1.45% 0.67% 0.77% 1.27%
Source: Data Published by 10 banks (5 Conventional and 5 Islamic Banks) from OJK website
The ratio of CAR is conventional banks in the period 2011-2013 was fluctuated until 44.96%
in 2013 and decrease by 22.18% in 2015 but increase by 23.52% in 2016Q2. While during
the decreasing of CAR in 2011-2012 and 2013-2015 the ratio of ROA still keeps increasing
until 2013. According to Kristiani & Yovin (2016), the higher of CAR the better performance
of the bank which means the increasing of ROA. In contrast, it happened in 2015-2016 the
increasing of CAR from 22.18%-23.52% affect the ROA, it decreased from 1.53% become
1.47%. The same thing also happened in the Islamic banks.
The ratio of LDR in 2014 is 89.46% become 99.23% in 2015, in contrast with ROA in 2014
is 1.81% decrease become 1.53% in 2015. While according to Ayunigrum (2011), if the
demand for credit increase, it also increase the profitability that makes ROA will show an
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increasing number. Islamic banks meet the same thing, by increased of FDR in 2013 to 2014
from 91.50% becomes 92.20% while the ROA decrease from 1.45% to 0.67%.
According to Susanto & Kholis (2016), NPL is a bad credit in the term of the payment that
can occur due to internal or external factor. This ratio is one of the key factors to know the
performance of functions of the bank (Siahaan & Anantadjaya 2013). It should be the
decreasing of the quality of bad credit will increase the number of ROA ratio. See from the
table in 2012 to 2013 the ratio of NPL was increasing but the ratio of ROA also keep increased
and that things also happened in Islamic banks in 2014-2016.
Some researcher had conducted a research to identify the profitability of the bank by the
financial ratio in one specific bank such as in conventional banks or Syariah banks and even
PT XYZ Syariah Bank. In this research, researcher used the financial ratio of CAR, NPL/NPF,
LDR/FDR directly both for conventional banks and Islamic banks in the same time period for
2011Q1-2016Q2. Previous research by Defri (2012) used CAR, LDR, BOPO of ROA in the
banking industry that listed in Indonesia Stock Exchange (conventional bank) found that CAR
has a positive insignificant effect toward ROA. On the other hand, Hardiyanti (2012) used
CAR, NPL, LDR toward ROA found that CAR has a positive significant effect toward the
profitability of the bank. While for Islamic banks, the previous researcher Havidz & Setiawan
(2015) found that CAR has a positive significant effect while Defri (2012) found that CAR
has positive insignificant effect in Islamic banks. NPL has a negative significant effect based
on the research by Susanto & Kholis (2016), but on the other hand, NPL has no significant
effect has been done by the previous also (Dasih, 2014; Alifah, 2014). Islamic banks aspect
of NPF according to Amelia (2015) found that NPF has negative and insignificant effect
toward the profitability of the bank while based on Abusharba et al. (2013), NPF has a
negative significant effect. LDR in the previous research showed that LDR has a positive
significant effect (Hardiyanti, 2012; Dasih, 2014; Alifah, 2014). On the other hand, according
to Adiyanto (2016) found that LDR has a negative insignificant effect. For the Islamic banks
Amelia (2015) found that FDR has a negative insignificant effect toward ROA while
Widyaningrum and Septiarini (2015) found that FDR has a positive insignificant effect. The
availability of data and limitation of time the researcher focus conducting the research on five
Conventional and five Islamic banks period 2011Q1-2016Q2. Based on the background
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above, the author decides to conduct further research with the title “The Profitability
Determinants of Conventional and Islamic Banks in Indonesia”.
Problem Identification
Based on the table 1.1 the data of average ROA in five conventional banks and five Islamic
banks showed that the ratio of ROA still fluctuated. Look at to the internal factors that will
affect the ratio of ROA and indicates that each variables CAR (Capital Adequacy Ratio), asset
quality aspects of NPL/NPF (Non-Performing Loan/ Financing), the liquidity aspect through
LDR/FDR (Loan/Financing to Deposit Ratio) have an increasing and decreasing from 2011-
2016Q2. So can conclude that the mean of each variable fluctuated, an increasing and
decreasing like in 2015-2016 the increasing of CAR in conventional banks from 22.18%-
23.52% affect to the decreasing of ROA from 1.53% become 1.47%.
From the previous research, there were differences of the results about the variables that affect
ROA. For the conventional banks according to Defri (2012) used CAR, LDR, BOPO of ROA
in the banking industry that listed in Indonesia Stock Exchange (conventional bank) found
that CAR has a positive insignificant effect toward ROA. On the other hand Hardiyanti (2012)
used CAR, NPL, LDR toward ROA found that CAR has a positive significantly toward ROA.
While Islamic banks according to Ismawati (2009) found that CAR has a positive significant
effect while Febrianti (2013) found that CAR has a positive insignificant effect in Islamic
banks.
Nugroho (2011) and Ramadhan (2015) found that FDR has positive significant effect toward
ROA, Alifah (2014) and Ayuningrum (2011) found that LDR has positive significant effect
while Susanto & Kholis (2016) found that LDR has no significant effect. Ismawati (2009) and
Widyaningrum & Septiarini (2015) found that FDR has no significant effect toward ROA.
Kristiani & Yovin (2016) and Susanto & Kholis (2016) found that NPL has negative
significant effect in contrast Dasih (2014) and Alifah (2014) found that NPL has positive
insignificant effect while Nugroho (2011) found that NPF has negative significant effect
toward ROA. Some research showed the different result, not consistency with the research
that has been done before, specifically the researcher intend to purpose further research of the
analysis of the determinants variables that determine the conventional Islamic bank’s
profitability during period 2011Q1-2016Q2 in Indonesia.
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Statement of Problem
According to the background, this research will discuss the internal factors that affect ROA
during period of 2011Q1-2016Q2, as the research questions as follows:
For conventional banks:
1. Does CAR have a significant effect toward ROA?
2. Does NPL has a significant effect toward ROA?
3. Does LDR has a significant effect toward ROA?
4. Does CAR, NPL, LDR have a partial and simultaneous effect toward ROA?
For Islamic banks:
1. Does CAR have a significant effect toward ROA?
2. Does NPF has a significant effect toward ROA?
3. Does FDR has a significant effect toward ROA?
4. Does CAR, NPF, FDR have a partial and simultaneous effect toward ROA?
Research Objective
The objectives of this research are:
For conventional banks period 2011Q1-2016Q2:
1. To analyze the effect of CAR toward ROA.
2. To analyze the effect of NPL toward ROA.
3. To analyze the effect of LDR toward ROA.
4. To investigate whether there is a partial and simultaneous effect of independent variables
(CAR, NPL, LDR) toward ROA.
For Islamic banks period 2011Q1-2016Q2:
1. To analyze the effect of CAR toward ROA.
2. To analyze the effect of NPF toward ROA.
3. To analyze the effect of FDR toward ROA.
4. To investigate whether there is a partial and simultaneous effect of independent variables
(CAR, NPF, FDR) toward ROA.
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1.2 Significance of the Study
The benefits of this research are:
1. For the Author
Through this study, the author can get insight and knowledge about factors that affect ROA,
the relationship of each factor in conventional and Islamic banks during period 2011Q1-
2016Q2 in Indonesia.
2. For Conventional and Islamic banks
The result of this research is expected to provide information for the bank to evaluate and
describe their financial performance between conventional and Islamic banks and hope this
research can give contributions in the decision making in banking policy in order to
maximize the profit.
1.3. Scope and Limitation of the Study
The researcher could not be generalized so there is some limitation that probably affects the
result. The scope and limitation of the study are:
1. The sampling consists of five conventional banks and five Islamic banks in Indonesia.
2. The research used quarter report period 2011Q1-2016Q2.
3. The research uses four financial ratios (CAR, NPL/NPF, LDR/FDR) of the banks that
expected to influence profitability (ROA) of each in conventional and Islamic banks.
The assessment of variables studies based on:
1. The financial report of conventional and Islamic banks in Indonesia during period 2011Q1-
2016Q2 that published by Financial Services Authority (OJK).
2. The financial report of conventional and Islamic banks in Indonesia during period 2011Q1-
2016Q2 that published by each bank.
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1.4 Definition of Terms
1. ROA
The ratio of managerial efficiency’s indicator that used to measure the management’s
capability of the bank to earn profit (Al-Gazzar, 2014).
2. Capital Adequacy Ratio (CAR)
This ratio can be set as a requirements to manage their capital in business acitivities without
ignoring the risk (Siahaan & Anantadjaya, 2013).
3. Non-Performing Loan (NPL)
The ratio as the key to assess the performance of functions of the bank, the intermediary
agency between exceeds funds and those who needs funds (Hendri, 2009).
4. Non-Performing Financing (NPF)
Describe the capacity and measured the asset quality in spreading risks (Sundarajan &
Errico, 2012).
5. Loan to Deposit Ratio (LDR)
The percentage ratio that shows the bank’s loans or financing funded through deposit ratio
(Al-Gazzar, 2014).
6. Financing to Deposit Ratio (FDR)
The percentage ratio that shows the bank’s financing funded through deposit ratio (Al-
Gazzar, 2014).
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CHAPTER II
LITERATURE REVIEW
2.1. Introduction
This chapter will discuss further about the theories regarding to the topic of this research.
The discussion will be divided no several parts, which are the definition of each variables
and the relationship between dependent variables and independent variables.
2.1.1 Overview on Bank
Bank defined as a business unit that raise funds from the public in savings and distribute
it in credit or others to improve the living standards of people (Law No. 10 of 1998
dated 10 November 1998). According to PSAK (Pernyataan Standard Akunting
Keuangan) No. 31 (1999), bank is an institutions that has the role between parties who
have surplus funds and parties need funds, also the institution that serves the payment
transaction.
In conventional banks no matter what the condition of the organization is, the customer
still must to pay the interest and there is no certain agreement of the contract but in
Islamic banks if the customers or organization suffered losses the banks and customers
will share the loss based on the agreement at the first time and the activities must to
have the contract like in Murabaha, Wadiah, Mudharabah or Musyarakah
(Indonesiainvestment, 2015).
2.2. Return on Assets
Variables of this research use the financial ratio data of the banks. Financial ratio analysis is
a calculation that can be used as an overview of the financial development and financial
position of the company. Financial statement can tells about the banks conditions in the past,
now, and perhaps can predict for the future (Rose & Hudgins, 2008). Financial statement
variable is one of the factor that can control bank’s management that relates to the balance
sheet and income statement. Financial ratios consider as the internal determinants and factor
that control the management consider as the external factor such as macroeconomic
environment like competition, regulation, concentration, market share, ownership, scarcity
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of capital, money supply, inflation and size (Haron, 2004). This research use financial ratio
to accessing the bank’s financial performance. Financial ratio that indicates of this research
consists of ROA as the dependent variable and CAR, NPL/NPF, LDR/FDR as the
independent variables.
Profitability is a fundamental that can be used to measure the bank’s performance and it is
important for the depositors, the management and also for the bank’s regulators. The ratio
that used to measure the profitability in this research is ROA. Return on Assets is used to
measure the efficiency and the ability of the bank to generate profit by using bank’s assets.
The smaller this ratio indicates that the management could not manage effectively the asset
to increase revenue and reduce cost. In other words, the higher ROA the better productivity
of assets that can increase the performance of the bank and also the income. Automatically
it can increase the attractiveness of the investors to the company since the rate of return or
dividend will be even greater. Besides, the effect can also increase the stock price if the high
number ratio of ROA happened. To calculate ROA, based on Bank Indonesia Circular Letter
No. 3/30/DPNP dated on December 14th 2001, the formula is:
ROA =
2.3. Capital Adequacy Ratio
CAR is the ratio to measure the bank’s ability to maintain sufficient capital. Bank’s duty is
to collect funds and distribute back in the form of loan. If the bank has a good capital and
meet the requirements it is a possibility to create profit so the bank’s profit will increase if
the CAR ratio is greater which means the bank is able to fund the operation of the bank or in
other words, the higher CAR is the better performance of the bank (Kristani & Yovin 2016).
CAR used as the independent variable that influence ROA since it connected with the risk
of the bank that will automatically affect the profitability of the bank. If the higher ratio of
CAR (based on BI regulation standard minimum of CAR is 8%). If the high ratio of CAR
but lack of the community trust it will not affect to the ROA. According to BI regulation,
No. 10/15/PBI/2008, article 2 paragraph 1 stated that Banks are required to provide a
Profit before taxes
Total assets X 100%
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minimum capital of 8% of risk-weighted assets. Based on Bank Indonesia Circular Letter
No. 6/23/DPNP dated 31th May, 2004, to calculate CAR the formula is:
CAR =
2.4. Non-Performing Loan and Non-Performing Financing
NPL ratio indicates the risks of loan payment by the debtor. After the bank gives credits,
banks have to monitor the use of credits as well, the ability and compliance the debtor to
meet their obligations since if there is a problem of the debtor to pay, and it can decrease the
bank’s profitability (Kristani & Yovin 2016). Credit is the greatest asset investment banks.
The ability to provide new loans will be hampered if the credit return failed. Credit capital is
needed to support the credit growth. According to Bank Indonesia Circular Letter No.
13/24/DPNP on October 25th 2011 the total loans is loans to non-third party funds. NPL
formula is:
NPL =
In financing, credit risk will happen if the bank cannot obtain the principle of financing
repayment. Banks will be more concern with the credit risk since financing activity is the
main thing of business activities. Collectability level can be used to measure the loss that
resulted by credit risk. Collectability in the bank can be divided into 5, pass/current, special
mention, sub-standard, doubtful, and loss. Based on its collectability, NPF is consist of sub-
standard, doubtful and loss (Bagaskara, 2016).
The formula of NPF is:
NPF =
The lower ratio of bad debt the better performance of the bank According to Bank Indonesia
Circular Letter No. 17/19/DPUM dated July 8th 2015, standard of maximum NPF is to be 5%
Capital
Risk Weighted Assets
X 100%
Non-Performing Loans
Total Loans
X 100%
Bad Collectability Financing (Sub-standard, doubtful, loss)
Total Financing
X 100%
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which means that if the ratio of NPF is more than 5% the bank is indicated to have a credit
risk problem.
2.5. Loan to Deposit Ratio and Financing to Deposit Ratio
LDR is used as a liquidity measurement to measure the amount of funds in the form of credits
from the funds that collected by the bank. The higher ratio of LDR shows more risky the
conditions of bank’s liquidity in contrast if the lower ratio of LDR means that the bank is not
efficient in channel back the funds to the third party funds (Kristani & Yovin 2016). LDR
shows the ability of the bank to repay the withdrawal of funds by the depositor to rely on
loans as the source of liquidity. According to BI regulation No 17/11/PBI/2015 dated on June
25th 2015 LDR changed into LFR (Loan to Funding Ratio with the standard 78%-92%.
Changed in LFR since the formula of LDR also change since LDR will used the securities
issued by the bank. So, the formula of LFR is:
LFR =
FDR can describe how much the funds from the third party funds that used for financing in
Islamic banks. If the high number ratio of FDR indicates that the bank is on the low capacity
condition of the liquidity. It can measure the banks growth in the term of financing and
lending. According to Bank Indonesia Circular Letter No. 12/11/DPNP/2010 standard of
FDR ratio is between 85%-110%. FDR can be calculated as follows:
FDR =
2.6. Research Gaps
Research on the profitability of the banking system has been done in economic research.
Besides, Indonesia is the largest population of muslim in the world but the people still has
lack of information and trust about syariah bank in Indonesia. It proves from the total asset
if compare with the conventional, Islamic bank is quite far different. Indonesian government
through Financial Services Authority (OJK) has a plan to merge all of the BUMN Islamic
bank in order to maximize their business activities efficiently to get the higher market share.
Net Loans
Third Party Funds + Securities Issued by the Bank
X 100%
Total Financing
Third Party Funds
X 100%
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Based on the previous research, the researcher found that previous objectives as a basic
concept. Erika (2015) found that CAR, NPF and FDR partially have no significant effect
toward ROA while BOPO has partially significant effect toward ROA. Anggrainy (2011)
found that CAR, NIM, NPL, BOPO and LDR have significant impact toward ROA and NIM
has no significant impact on ROA. Kristiani & Yovin (2016) found that CAR, NIM, LDR
have positive significant effect toward ROA, Operational Efficiency has significant effect
toward ROA and NPL has negative significant effect toward ROA. See from the table 2.1 to
know more detail of some previous researches and the result.
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CHAPTER III
RESEARCH METHODOLOGY
3.1. Introduction
This chapter is designed to explain the research methodology that is used by the researcher
in this research. This chapter consists of the theoretical framework, hypothesis, and
operational definition of variables, instrument, and sampling.
3.2. Theoretical Framework
For conventional banks:
For Islamic banks:
CAR
(X1)
NPL
(X2)
LDR
(X3)
ROA
(Y)
CAR
(X1)
NPF
(X2)
FDR
(X3)
ROA
(Y)
Source: Adjusted by Author
Source: Adjusted by Author
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Internal factors is one of the main things to find the independent variables that significantly
influence toward Return on Assets in conventional and Islamic banks in Indonesia during
period 2011Q1-2016Q2. In this research uses three internal factors which are CAR,
NPL/NPF, and LDR/FDR.
3.3. Hypothesis
Based on the statement of problem and theoretical framework above, the hypothesis that
tested in this research can be stated as follows:
Hypothesis 1: CAR has significant effect toward ROA in conventional banks.
Hypothesis 2: NPL has significant effect toward ROA in conventional banks.
Hypothesis 3: LDR has significant effect toward ROA in conventional bank.
Hypothesis 4: CAR, NPL, LDR have simultaneous effect toward ROA in conventional
banks.
Hypothesis 5: CAR has significant effect toward ROA in Islamic banks.
Hypothesis 6: NPF has significant effect toward ROA in Islamic banks.
Hypothesis 7: FDR has significant effect toward ROA in Islamic banks.
Hypothesis 8: CAR, NPF, FDR have simultaneous effect toward ROA in Islamic banks.
3.4. Operational Definitions of Variables
The operational definitions can show how the variables is measured both dependent and
independent variables.
1. Return on Assets (ROA)
The dependent variable in this research is ROA. Return on Assets is a ratio that can
measured the ability of the bank to make profit (profit before taxes).
2. Capital Adequacy Ratio
CAR is the ratio of capital to risk weighted assets or aktiva asset tertimbang menurut
resiko (ATMR).
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3. Non-Performing Loan
NPL ratio indicates the risks of loan payment by the debtor (Kristani & Yovin, 2016).
According to Bank Indonesia Circular Letter No. 13/24/DPNP on October 25th 2011 the
total loans is loans to non-third party funds.
4. Loan to Deposit Ratio or Loan to Funding Ratio
LDR shows the ability of the bank to repay the withdrawal of funds by the depositor to
rely on loans as the source of liquidity. According to BI regulation No 17/11/PBI/2015
dated on June 25th 2015 LDR changed into LFR (Loan to Funding Ratio with the standard
78%-92%.
5. Non-Performing Financing
NPF is the ratio between Total Bad Debts to Total Financing.
6. Financing to Deposit Ratio
FDR can measure the banks growth in the term of financing and lending. According to
Bank Indonesia Circular Letter No. 12/11/DPNP/2010 standard of FDR ratio is between
85%-110%.
3.5. Instrument
In this research, researcher used the secondary data since it was very convenient and it save
time and cost. Secondary data refer to information gathered from sources that already exist
(Ariana, 2011). This research used SPSS 16.00 as an analysis tool. SPSS is common software
used to accomplish the research by establishing database and statistical data processing. This
statistical tool that used in this research were descriptive statistics test, classical assumption
test, (normality test, multicollinearity test, heteroscedasticity test, and autocorrelation test),
multiple linear regression, and hypothesis test (f test, t test, coefficient multiple determination
test), group statistics test and independent sample test. By using SPSS as the statistical tools,
will help the researcher to establish the relationship between variables and help to present
the data. Besides, researcher also used Microsoft Excel 10 to help researcher to summarize
the data that covered the financial ratio.
3.6. Sampling
In this research, the population is taken from five conventional and five Islamic banks in
Indonesia that listed in Financial Services Authority of Indonesia (OJK). This research
Page 17 of 53
applies non-probability sampling with the focus on purposive sampling in order to achieve
the certain purpose of this research. The criteria for the purposive sampling are:
a. The five Conventional banks and five Islamic banks that published their report in OJK
and still running during period 2011Q1-2016Q2.
b. The availability of the financial statement position for period 2011Q1-2016Q2.
c. The conventional and Islamic banks is feasible to use based on their asset.
During this research, the data that used is secondary data in the form of financial ratios of
conventional and Islamic banks that published in OJK or that own website of each banks that
cover the period from 2011Q1-2016Q2. (See table 3.1 on appendixes about the banks
representative)
3.7. Data Analysis Method
3.7.1. Descriptive Statistics Analysis
This analysis can describe by the data by looking mean, standard deviation, maximum
and minimum. Mean is the average value of series, max and min are the maximum
and minimum values of the series in the current sample, std. deviation is a measure of
dispersion (Gujarati, 2004).
3.7.2. Assumption Classic Test
Data should fulfill classical assumption model in the regression analysis. It should be
passed in normality test, multicollinearity test, heteroscedasticity test and
autocorrelation test.
A. Normality Test
According to Ramadhan (2015), normality test is to determine whether the
independent variables and dependent variable has normal distribution or not.
By running SPSS 16.00 there will be several results one of them using graphs,
either in normal, plot and histogram graph. Normality test that used P-Plot will
form a diagonal line and the plotting data will compare with the diagonal line.
If the distribution of data is normal the line that represents the data will actually
follow the diagonal line.
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B. Multicollinearity Test
The purpose of multicollinearity test is to know the correlation between the
independent variables (Ghozali, 2007). A good result of regression model is
there is no relationship between the independent variables or free from
multicollinearity problems. Multicollinearity test shows the tolerance and VIF
(Variance Inflation Factor). A regression model result that has TOL ≥0.1 or
VIF <10.00 meaning that there is no multicollinearity problems that happened.
C. Heteroscedasticity Test
The purpose of heteroscedasticity test is to define whether the variance from
the residual of the observation variable is similar or not in the regression model
(Gujarati, 2004). A good result is there is no heteroscedasticity problem on the
research. It can show from the scatterplot between the value of dependent
variable (ZPRED) and the value of the residual (SRESID).
D. Autocorrelation Test
Autocorrelation is the correlation between error variable with another error
variable. The result of Durbin-Watson lower than -2 means that there is a
positive autocorrelation problem and higher that 2 means that there is a
negative autocorrelation problem (Singgih Santoso, 2009). So, it must around
-2 and +2 to conclude that the data has no autocorrelation problem.
3.7.3. Multiple Linear Regression
After the assumption classic test was completed and no problem happened thus it
complies the requirement to do multiple regression analysis and to do hypothesis
testing. The equation formula for multiple linear regressions is:
Y = a + βiX1 + βiiX2 + βiiiX3 + Ɛ
Where, for conventional banks:
Y = Return on Asset (ROA)
a = Constant
βi,ii,iii, = Coefficient of the regression
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X1 = Capital Adequacy Ratio (CAR)
X2 = Loan to Deposit Ratio (LDR)
X3 = Non-Performing Loan (NPL)
Ɛ = Error of Term
Where, for Islamic banks:
Y = Return on Asset (ROA)
a = Constant
βi,ii,iii, = Coefficient of the regression
X1 = Capital Adequacy Ratio (CAR)
X2 = Financing to Deposit Ratio (FDR)
X3 = Non-Performing Financing (NPF)
Ɛ = Error of Term
3.7.4. Hypothesis Testing
F-test and T-test will be used in this research to do a hypothesis testing. The purpose
of f test to define whether all independent variables have simultaneous influence
toward dependent variable. T test is to define whether each independent variable has
partial significant influence toward dependent variable.
A. Significant Simultaneous Test (F-Test)
Based on Alghozali (2005) F-test is to know whether every variable are
independent to be include in the model that have the influence of the dependent
variables against jointly bound. It will provide information whether there is
any influence of the independent variables against the dependent variable
simultaneously. F-test is performed by comparing the significance value of
Ftable and Fcount. The basic of making decision for this test are:
If Fcount ≤ Ftable, Ho accepted Ha rejected, for α ≥ 0.05
If Fcount ≥ Ftable, Ho rejected Ha accepted, for α ≤ 0.05
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Where, for conventional banks:
Ho: βi = βii = βiii = 0, CAR, LDR, NPL, do not give significant simultaneous
influence toward ROA.
Ha: at least one of βi ≠ βii ≠ βiii ≠ 0, CAR, LDR, NPL, have significant
simultaneous influence toward ROA.
Where, for Islamic banks:
Ho: βi = βii = βiii = 0, CAR, FDR, NPF, do not give significant simultaneous
influence toward ROA.
Ha: at least one of βi ≠ βii ≠ βiii ≠ 0, CAR, FDR, NPF, have significant
simultaneous influence toward ROA.
B. Significant Partial Test (T-Test)
The purpose of t test is to determine the partial influence of each independent
variable which are CAR, LDR and NPL toward ROA for conventional banks
and CAR, FDR, NPF toward ROA for Islamic banks. The formula of
hypotheses for this test is:
Conventional Banks:
If Ho1:βi= 0 or significance level > α, means that there is no significant
effect of CAR toward ROA.
If Ha1:βi ≠ 0 or significance level < α, means that there is significant effect
of CAR toward ROA.
If Ho2:βii= 0 or significance level > α, means that there is no significant
effect of LDR toward ROA.
If Ha2:βii ≠ 0 or significance level < α, means that there is significant effect
of LDR toward ROA.
If Ho3:βiii = 0 or significance level > α, means that there is no significant
effect of NPL toward ROA.
If Ha3:βiii ≠ 0 or significance level < α, means that there is significant effect
of NPL toward ROA.
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Islamic Banks:
If Ho1: βi= 0 or significance level > α, means that there is no significant
effect of CAR toward ROA.
If Ha1:βi ≠ 0 or significance level < α, means that there is significant effect
of CAR toward ROA.
If Ho2:βii = 0 or significance level > α, means that there is no significant
effect of FDR toward ROA.
If Ha2:βii ≠ 0 or significance level < α, means that there is significant effect
of FDR toward ROA.
If Ho3:βiii = 0 or significance level > α, means that there is no significant
effect of NPF toward ROA.
If Ha3:βiii ≠ 0 or significance level < α, means that there is significant effect
of NPF toward ROA.
Criteria for making decision for as follows:
If Tcount ≤ Ttable or significance level ≥ (α) 0.05, then Ho accepted Ha
rejected
If Tcount ≥ Ttable or significance level ≤ (α) 0.05, then Ho rejected Ha
accepted
C. Coefficient Multiple Determination Test (R2)
In order to measure the goodness of the regression equation r square and
adjusted r square can be as a defined. R2 is used if the independent variables is
less than two while if the independent variables have more than two, adjusted
R2 is used. It can indicates how far the independent variables used in the
regression equation which is able to explain a dependent variable (Gujarati,
2004). In order to overcome the problem it involves r square that has been
corrected called adjusted r square and will adjust if there is an additional
independent variable.
D. Group Statistics Result
This test will show the comparison average value between each variables in
conventional and Islamic banks to measure the ratio performance.
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E. Independent Sample Test
This test is to measure if there is a difference performance between
conventional and Islamic banks in Indonesia. In order to decide a decision for
the hypothesis of independent sample test, there are 2 basic decision that can
used:
1. If sig value of f test is > 0.05 Ho was accepted and Ha was rejected, the sig
value of t test is > 0.05.
2. If sig value of f test < 0.05 Ho was rejected and Ha was accepted, the sig
value of t test is < 0.05.
Where:
Ho: there is no significant different between variables in conventional and
Islamic banks
Ha: there is significant different between variables in conventional and Islamic
banks
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CHAPTER IV
RESULT AND DISCUSSION
In pursuance of the statement of problems and theoretical framework, to test the hypothesis, this
research used descriptive analysis and statistical analysis to interpret the data. The purposed of
descriptive analysis is to define the condition of the company from the data acquired by the
researcher. Statistical analysis is to calculate the data with the help of computer programs which
is SPSS 16.00 as statistical tool to run the data.
This chapter will discuss the descriptive analysis, classical assumption testing, hypothesis testing
and discussion.
4.1 Gathered Sampling Data
From the gathering data process, total data reaches 110 for Islamic Bank and 110 for
Conventional Bank, and total for both of it is 220. After the researcher do the first research
used the first data without outlier, the result is not valid from the normality and
heteroscedasticity test. Outlier is a cases that the data has a unique characteristics that look
very different from other observations data in the form of extreme in dependent or
independent variables. It overcomes by determining the limit values and categorized as a
data outlier and convert it into z score which has the standard score in between ≤2.5 and ≥-
2.5 (id thesis.com, AlGhozali 2007). In order to make the research valid from the secondary
data that has been collected, the researcher make the outlier data using SPSS 16.00
expectedly that the data can show the valid result.
4.2 Result of Data Analysis
4.2.1 Descriptive Statistics
Analysis for Conventional Bank in Indonesia period 2011Q1-2016Q2:
The purpose of descriptive table is to show the number of data (N), maximum and
minimum value of data, the average value (mean) and standard deviation of each
variable which are CAR, LDR, NPL and ROA can be seen from the table 4.1.
Page 24 of 53
The observation data of this research becomes 96 data after outlier that got from the
quarterly financial report of each bank samples of Bank Indonesia and Financial
Services Authority of Indonesia (OJK) report of period 2011Q1-2016Q2. The
information about each variable will describe below:
a. The average CAR is 21.6247% with the lowest value is CAR of Bank Artha Graha
International which only 9.67% during the period of Q2 in 2012 and the highest
value is CAR of Bank Multiarta Sentosa which reach 67.00% during the period Q3
in 2014. During the research period, the value of CAR fluctuated but it is consider
as good since it exceeds the minimum standard stated by Bank Indonesia which is
8%. The deviation of CAR is good because the standard deviation is 9.84996%
which is lower than the average value. CAR is one of the requirement to get FPJP
(Fasilitas Pendanaan Jangka Pendek) beside the bank must have a good high
quality of the collateral, the value of the collateral is good enough and meet the
capital according to the risk profile of the bank and based on the calculation of Bank
Indonesia. (BI Circular Letter No. 15/11/DPNP dated on April 3rd 2013).
b. The average LDR is 87.4251% with the lowest value is LDR of Bank ICBC
Indonesia which only 68.21% during the period of Q2 in 2011 and the highest value
is also LDR of Bank Mestika Dharma which reach 105.49% during the period of
Q2 in 2014. Averagely the value of LDR during the research period mostly are still
in the standard of Bank Indonesia which is ranging from 85%-110% (Bank
Indonesia Circular Letter No. 12/11/DPNP/2010) although the value of LDR
fluctuated during period of research. Changed according to BI regulation No
17/11/PBI/2015 dated on June 25th 2015 LDR changed into LFR (Loan to Funding
Ratio with the standard 78%-92%. The deviation of LDR is relatively good because
the standard deviation which is 7.9750% which lower that the average value.
c. The average of NPL is 1.3323% with the lowest value is NPL of Bank Multiarta
Sentosa which only 0.00 of Q1 in 2016 and 0.03 of Bank ICBC Indonesia during
the period of Q1 in 2013 and the highest value is NPL of Bank Nusantara
Parahyangan which reach 3.98% during period of Q4 in 2015. The standard NPL
from Bank Indonesia is less than 5% (Bank Indonesia Circular Letter No.
15/35/DPAU dated August 29th 2013). It shows the value of NPL during research
Page 25 of 53
period fluctuated but averagely NPL of those samples bank was classified as good
because it is still in the standard of BI regulation. If the NPL is exceeds than the
standard which mean is that several Islamic banks had credit risk problem. The
deviation of NPL is relatively good because the standard deviation which is
1.0464% lower than the average value 1.3323%.
Analysis for Islamic Bank in Indonesia period 2011Q1-2016Q2:
The observation data of this research is 95 data after outlier which got from the
quarterly financial report of each bank samples of Bank Indonesia and Financial
Service Authority of Indonesia (OJK) report of period 2011Q1-2016Q2. The
information about each variable is on table 4.2 and it will describe below:
a. The average CAR is 16.8787% with the lowest value is CAR of Bank BRI Syariah
which only 11.03% during the period of Q2 in 2015 and the highest value is CAR
of Bank Panin Syariah which reach 45.65% during the period Q2 in 2012. During
the research period, the value of CAR fluctuated but it is consider as good since it
exceeds the minimum standard stated by Bank Indonesia which is 8%. The
deviation of CAR is good because the standard deviation is 5.2817% which is lower
than the average value. CAR is one of the requirement to get FPJP (Fasilitas
Pendanaan Jangka Pendek) beside the bank must have a good high quality of the
collateral, the value of the collateral is good enough and meet the capital according
to the risk profile of the bank and based on the calculation of Bank Indonesia. (BI
Circular Letter No. 15/11/DPNP dated on April 3rd 2013).
b. The average FDR is 95.3636% with the lowest value is FDR of Bank BRI Syariah
which only 76.53% during the period of Q1 in 2011 and the highest value is also
FDR of Bank Panin Syariah which reach 127.88% during the period of Q2 in 2012.
Averagely the value of FDR during the research period mostly are still in the
standard of Bank Indonesia which is ranging from 85%-110% (Bank Indonesia
Circular Letter No. 12/11/DPNP/2010) although the value of FDR fluctuated
during period of research. The deviation of FDR is relatively good because the
standard deviation which is 9.8282% which lower that the average value.
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c. The average of NPF is 2.1073% with the lowest value is NPF of Bank Panin Syariah
which only 0.19 during the period of Q4 in 2012 and the highest value is NPF of
Bank Muamalat Indonesia which reach 4.61% during period of Q2 in 2016. The
standard NPF from Bank Indonesia is less than 5% (Bank Indonesia Circular Letter
No. 17/19/DPUM dated July 8th 2015). It shows the value of NPF during research
period fluctuated but averagely NPF of those samples bank was classified as good
because it is still in the standard of BI regulation. If the NPF is exceeds than the
standard which mean is that several Islamic banks had credit risk problem. The
deviation of NPF is relatively good because the standard deviation which is
1.0635% lower than the average value 2.1073%.
4.3 Assumption Classic Test Result
4.3.1 Normality Test
Based on the result the normal probability plot graphic and it shows the data spread
around the diagonal line or follow the direction of the diagonal stripe pattern which is
the data shows the normal distribution and the regression model meet the assumption of
normality. While for both conventional and Islamic of histogram graph result it shows
that the normal data distribution follows the curves and do not stay to the right or to the
left. It indicates the data has a normal distribution. The table is on the figure 4.1, 4.2,
4.3, 4.4.
4.3.2 Multicollinearity Test
In this research there are three independent variables which are CAR, FDR/LDR and
NPF/NPL. A regression model result that has TOL ≥0.1 or VIF <10.00 meaning that
there is no multicollinearity problems that happened. Based on the result (table 4.4 and
4.5). For conventional banks CAR has the value of TOL 0.941, LDR is 0.933, NPL is
0.969 and the value VIF value of CAR is 1.063, LDR is 1.072 and NPL is 1.032. While
for Islamic banks CAR has the value of TOL is 0.675, FDR is 0.828, NPF is 0.733 and
the VIF value of CAR is 1.481, FDR is 1.208 and NPF is 1.364. Both for conventional
and Islamic banks shows that each independent variables has TOL ≥0.1 and also has the
VIF value <10.00. Hence, in this research there is no multicollinearity problem. .
Page 27 of 53
4.3.3 Heteroscedasticity Test
Based on the scatterplot result (see on appendixes figure 4.5 and 4.6) the dots spread
randomly and scattered both below and above 0 in the Y axis.
4.3.4 Autocorrelation Test
It must around -2 and +2 to conclude that the data has no autocorrelation problem. The
table 4.6 and 4.7 will show the DW value of each in conventional and Islamic banks.
Because of the Durbin-Watson value is 0.417 for conventional and 0.680 for Islamic
which mean between -2 and 2 so there is no autocorrelation problem on the research
data.
4.4 Multiple Linear Regression
Based on the result of assumption classis test result it can conclude that the data on this
research has been distributed normally and there is no multicollinearity, heteroscedasticity, and
autocorrelation problems that happened. Thus it complies the requirement to do multiple
regression analysis and to do hypothesis testing (the result table is on appendixes table 4.8
and 4.9).
The result shows the multiple regression equation for conventional banks as follows:
Y = -4.938 + 0.035X1 + 0.066X2 + 0.078X3
1. Constant value for -4.938 shows that if there is no independent variables (CAR(X1=0),
LDR(X2=0) and NPL(X3=0)) the value of ROA(Y) will be -4.938.
2. β1 is 0.035 shows that every increasing of Capital Adequacy Ratio for 1% will follow
by increasing of ROA amounted 0.035, with estimates of other independent variables
is constant or not changes.
3. β2 is 0.066 shows that every increasing of Loan to Deposit Ratio for 1% will follow
by increasing of ROA amounted 0.066, with estimates of other independent variables
is constant or not change.
4. β3 is 0.078 shows that every increasing of Non-Performing Loan for 1 % will follow
by increasing of ROA amounted 0.078, with estimates of other independent variables
is constant or not change.
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While for the Islamic bank’s result:
Y = 1.586 + 0.007X1 + 0.004X2 – 0.369X3
1. Constant value for 1.586 shows that if there is no independent variables (CAR(X1=0),
FDR(X2=0) and NPF(X3=0)) the value of ROA(Y) will be 1.586.
2. β1 is 0.007 shows that every increasing of Capital Adequacy Ratio for 1% will follow
by increasing of ROA amounted 0.007, with estimates of other independent variables
is constant or not changes.
3. β2 is 0.004 shows that every increasing of Financing to Deposit Ratio for 1% will
follow by increasing of ROA amounted 0.004, with estimates of other independent
variables is constant or not change.
4. β3 is -0.369 shows that every increasing of Non-Performing Financing for 1 % will
follow by decreasing of ROA amounted 0.369, with estimates of other independent
variables is constant or not change.
4.5 Hypothesis Testing
4.5.1 Significant Simultaneous Test (F-Test)
F-test is performed by comparing the significance value of Ftable and Fcount. The basic of
making decision for this test are:
If Fcount ≤ Ftable, Ho accepted Ha rejected, for α ≥ 0.05
If Fcount ≥ Ftable, Ho rejected Ha accepted, for α ≤ 0.05
Where:
Ho = there is no significant influence of independent variables toward dependent
variable
Ha = there is significant influence of independent variables toward dependent variable
Based on the (table 4.10 and 4.11) result, for conventional banks the f count > f table,
17.649>2.70 with the sig. value of f test is 0.000 which is <0.05 and for Islamic banks
the f count > f table, 9.758 > 2.70 with the sig. value of f test is 0.000 which is <0.05.
So the researcher can reject Ho and accept Ha for each conventional and Islamic banks.
It means all independent variables affect significantly toward dependent variable.
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4.5.2 Significant Partial Test (T-Test)
Based on the (table 4.12 and 4.13 on appendixes) test result, can be concluded that:
Table 4.14. Explanation of T-Test Result
Conventional Banks Islamic Banks
CAR :
Tcount = 3.490 > Ttable = 1.984 with the sig.
value 0.001 < 0.05 which means Ho was
rejected and Ha was accepted. CAR has
positive significant effect toward ROA
CAR:
Tcount = 0.384 < Ttable = 1.984 with the sig.
value 0.702 > 0.05 which means Ho was
accepted and Ha was rejected. CAR has
no significant effect toward ROA.
LDR:
Tcount = 5.313 > Ttable = 1.984 with the sig.
value 0.000 < 0.05 which means Ho was
rejected and Ha was accepted. LDR has
positive significant effect toward ROA.
FDR:
Tcount = 0.440 < Ttable = 1.984 with the sig.
value 0.661 > 0.05 which means Ho was
accepted and Ha was rejected. FDR has
no significant effect toward ROA.
NPL:
Tcount = 0.835 < Ttable = 1.984 with the sig.
value 0.406 > 0.05 which means Ho was
accepted and Ha was rejected. NPL has
no significant effect toward ROA.
NPF:
Tcount = -4.269 < Ttable = 1.984 with the
sig. value 0.000 < 0.05 which means Ho
was rejected and Ha was accepted. NPF
has negative significant effect toward
ROA.
Source: Adjusted by Author from the processing result of SPSS 16.00
4.5.3 Coefficient Multiple Determination Test (R2)
Based on the (table 4.15 and 4.16) result, the R2 of the model in conventional bank is
0.365 and adjusted R2 is 0.345. The result of adjusted R2 0.345 means 34.5% of
dependent variable (ROA) is explained by the combination of independent variables
which are CAR, LDR and NPL. The rest 65.5% is influenced by other factors outside
the research model. While for the R2 in Islamic banks is 0.243 and adjusted R2 is 0.218.
The result of adjusted R2 0.218 means 21.8% of dependent variable (ROA) is explained
by the combination of independent variables which are CAR, FDR and NPF. The rest
78.2% is influenced by other factors outside the research model.
Page 30 of 53
4.5.4 Group Statistics Result
See from table 4.17 which the results are:
1. CAR in Islamic banks has the value of mean is 16.8787% which is lower than
conventional banks which amount 21.6247%. It means that during the period of 2011-
2016Q2 conventional banks has a better CAR than Islamic banks since the higher of
CAR is the healthier of the bank. If refer to the BI regulation No. 10/15/PBI/2008,
article 2 paragraph 1 stated that Banks are required to provide a minimum capital of
8% of risk-weighted assets Islamic bank still in an ideal condition that has the value
of CAR above the minimum standard of BI.
2. FDR of Islamic banks is 95.3636% which is higher than conventional banks
87.4251% it means that during period 2011-2016Q2 Islamic bank has the better
financing. Both of conventional and Islamic banks is in the ideal position since it
fulfill the standard of BI regulation around 78%-92% for conventional and 85%-
110% for Islamic.
3. NPF in Islamic banks is 2.1073% which is higher than conventional 1.3323% means
that during period 2011-2016Q2 conventional banks healthier in the term of credit
risk problem than Islamic banks but both of it is still in the ideal condition around 5%
based on BI regulation.
4. ROA in Islamic banks is 1.2956% lower than conventional banks 1.7385%. It means
during period 2011-2016Q2 conventional banks has the better quality of profitability
or ROA than Islamic banks since the higher ROA the better quality of the profit.
Based on BI regulation No. 6/9/PBI/2004 a health condition of bank must have the
ROA >1.5% so Islamic banks is in the less ideal conditions.
4.5.5 Independent Sample Test
The test result in on table 4.18, as explanation:
Table 4.19. Explanation for Independent Sample Test
Variables
CAR F count = 25.820 sig value 0.000 < 0.05
Ho was rejected Ha was accepted.
Page 31 of 53
There is a different variance between Cbs
and Ibs.
Used the basic equal variance not
assumed for the t test.
T count = 4.156 sig value 0.000 < 0.05
Ho was rejected Ha was accepted.
There is significant different performance
between conventional and Islamic banks
if see from the ratio of CAR.
LDR or FDR F count = 1.419 sig value 0.235 > 0.05
Ho was accepted Ha was rejected.
There is no significant different of
variance between Cbs and Ibs.
T count = 6.133 sig value 0.000 < 0.05
Ho was rejected Ha was accepted.
There is significant different performance
between conventional banks and Islamic
banks if see from the ratio of LDR or FDR
NPL or NPF F count = 0.322 sig value = 0.571 > 0.05
Ho was accepted Ha was rejected.
There is no significant different of
variance between Cbs and Ibs.
T count = 5.076 sig value 0.000 < 0.05
Ho was rejected Ha was accepted.
There is significant different performance
between conventional banks and Islamic
banks if see from the ratio of NPL or NPF
ROA F count = 4.484 sig value = 0.036 < 0.05
Ho was rejected and Ha was accepted.
There is a different variance between Cbs
and Ibs.
Page 32 of 53
Used the basic equal variance not
assumed for the t test.
T count = 175.437 sig value = 0.003 <
0.05.
Ho was rejected Ha was accepted.
There is significant different performance
between conventional banks and Islamic
banks if seen from the ratio of ROA.
Source: Adjusted by Author from the processing result of SPSS 16.00
4.6 Interpretation of Result
There were several tests that have been conducted. This section will analyze the data result
and answer the hypotheses that researcher tries to answer by conducting this research. All of
the hypotheses used the multiple linear regression and below are the interpretation result of
this research:
4.6.1 The influence of Capital Adequacy Ratio toward the Return on Asset
CAR has positive significant effect toward ROA in conventional banks shows that it is
based on the theory. Capital Adequacy Ratio or CAR is the main capital that must to
meet by the bank. According to BI regulation in 2008 CAR is the ratio that shows how
far the assets that contain the risks (credit, issued securities, claim or bill at another bank)
have to be financed by the own capital of the bank besides the third party funds. CAR
is the ratio to measure the bank’s ability to maintain sufficient capital. Bank is to collect
funds and distribute back in the form of loan. If the bank has a good capital and meet
the requirements it is a possibility to create profit so the bank’s profit will increase
(Kristani & Yovin 2016). Bank Indonesia stated that the minimum value of its capital is
for 8% and it will considered as a healthy bank. CAR used as the independent variable
that influence ROA since it connected with the risk of the bank that will automatically
affect the profitability of the bank. If the higher ratio of CAR (based on BI regulation
standard minimum of CAR is 8%) which means that the bank can financed the operation
both in critical condition or not and will give a big contribution to the profitability of the
bank. If the bank has an enough capital in the critical situation, the bank will safe since
Page 33 of 53
the banks have a capital reserve in Bank Indonesia. This result is similar with previous
research conducted by Hardiyanti (2012) and Kristani & Yovin (2016). While in Islamic
banks CAR has no significant effect toward ROA since BI regulation stated that the
minimum standard of CAR is 8% so many Islamic banks sometimes add their capital
reserve by provide fresh money to anticipate the risk that can happen and a guarantee in
order to fulfill the regulation of BI. This result is similar with the previous research
conducted by Ramadhan (2015) and Hakim & Rafsanjani (2015). The more capital that
the banks have sometimes it hampers their business activity especially in Islamic banks
the profit is based on profit sharing not based on the interest and Islamic banks do not
maximize the capital in the business activity since the banks want to maintain their
minimum standard of CAR. Besides, if the higher ratio of CAR but lack of the
community trusts it will not affect to the ROA ratio. It can see from the report if the ratio
of CAR increase the ratio of ROA was not always increase. Bank sometimes invests
money carefully and more concern in the survival of the bank so CAR has not influence
toward the profitability of the bank. Based on the independent sample test, the
performance of conventional banks and Islamic banks in the term of the financial ratio
of CAR has significant different, CAR in conventional bank is better performance than
the Islamic banks.
4.6.2 The Influence of Loan to Deposit Ratio and Financing to Deposit Ratio toward
Return on Asset
LDR has positive significant effect toward ROA in conventional banks that shows the
ability of the bank to repay the withdrawal of funds by the depositor to rely on loans as
the source of liquidity. This research is similar with the previous that conducted by
Kristani & Yovin (2016) and Kuntari Dasih (2014). If the bank has the high number of
LDR but still in the standard of BI it can indicates that the more credit that the bank’s
distributed and will increase the profitability of interest. The higher ratio of LDR
meaning that the lower bank’s liquidity because it indicates that a bank lends most of its
funds but the lower ratio of LDR indicates that the banks do not give an efficient
distribution of credit. According to BI regulation No 17/11/PBI/2015 dated on June 25th
2015 LDR changed into LFR (Loan to Funding Ratio with the standard 78%-92%) and
it will used the securities issued in LFR. In the Islamic banks, FDR has no significant
Page 34 of 53
effect toward ROA it indicates the quality of financing. According to Bank Indonesia
Circular Letter No. 12/11/DPNP/2010 standard of FDR ratio is between 85%-110%. No
significant effect between FDR and ROA can caused by the financing that was not
optimal and not effective and lack of the circumspection principle by the management
of the bank. This result is similar with the previous research that conducted by
Widyaningrum & Septiarini (2015) and Suryani (2011). Based on the independent
sample t test, the performance of conventional banks and Islamic banks in the term of
LDR or FDR has significant different, LDR in Islamic banks has a better performance
than conventional banks.
4.6.3 The influence of Non-Performing Loan or Non-Performing Financing toward
ROA
NPL has no significant effect toward ROA. The lower ratio of bad debt the better
performance of the bank. Bank as an intermediary’s institution and also the media for
payment transaction. NPL ratio indicates the risks of loan payment by the debtor if there
is a problem of the debtor to pay, and it can decrease the bank’s profitability (Kristani
& Yovin 2016). The development of financial industry push the banks to do innovation
in the products and services that will affect to income of the bank not only rely on the
earning assets but also in fee base income such as the securities, invest the capital on
non-bank financial institutions or other company, and also the placement funds at the
other banks (Retnadi, 2006). This research similar with the previous that conducted by
Dasih (2014) and Sukarno (2016). While for Islamic banks, NPF has negative significant
effect toward ROA based on the theory the higher ratio of NPF will decrease the
profitability of the bank. According to Bank Indonesia Circular Letter No. 17/19/DPUM
dated July 8th 2015, standard of maximum NPF is to be 5% which means that if the ratio
of NPF is more than 5% the bank is indicated to have a credit risk problem. Banks will
be more concern with the credit risk since financing activity is the main thing of business
activities in Islamic banks. The negative sign means that the increasing of bad financing
will decreased the profitability of the bank. This result is similar with the previous that
conducted by Nugroho (2011) and Hayati et al (2010). Based on the independent sample
test, the performance of conventional banks and Islamic banks in the term of NPL or
Page 35 of 53
NPF has significant different, conventional banks that has the lower ratio of NPL is the
healthier bank’s performance than Islamic banks.
4.6.4 The influence of Capital Adequacy Ratio, Loan to Deposit Ratio/Financing to
Deposit Ratio and Non-Performing Loan/Non-Performing Financing toward Return
on Asset
CAR, LDR/FDR and NPL/NPF have simultaneous effect toward ROA both in
conventional and Islamic banks in Indonesia. It means all independent variables of this
research affect significantly toward dependent variable. The ratio of CAR, LDR/FDR
and NPL/NPF can explain the ratio of ROA in conventional and Islamic banks in
Indonesia. Besides, this result is empirical evidence that profitability of the banks is also
affected by external and internal factors. The change of all variables significantly
influence the change of profitability of the banks.
Page 36 of 53
CHAPTER V
CONCLUSION AND RECOMMENDATION
5.1 Conclusion
This research attempts to analyze the comparative study about the factors that influence
profitability between conventional banks and Islamic banks in Indonesia. It used ROA as the
dependent variables, CAR (Capital Adequacy Ratio), LDR/FDR (Loan to Deposit
Ratio/Financing to Deposit Ratio), and NPL/NPF (Non-Performing Loan/Non-Performing
Financing) as the independent variables. Based on multiple linear regression analysis, the
result as follows:
Conventional Banks:
a) CAR has positive significant effect toward ROA. It proves the roles of Capital Adequacy
Ratio is something that must be fulfilled by the bank which can help bank to face losses
that can be happened in order to maintain the bank’s activities run effectively and
efficiently to help increasing the profit that will impact to the financial performance of the
bank.
b) LDR has positive significant effect toward ROA. Based on to BI regulation No
17/11/PBI/2015 dated on June 25th 2015 LDR changed into LFR (Loan to Funding Ratio
with the standard 78%-92%). So the higher LFR but still keep in the healthy standard of
Bank Indonesia meaning that the bank distributed the credit optimally and with the big
amount of the third party funds that the banks can distribute to loans. With the growing of
loans granted will increase the profit of the bank and will gain a healthy financial
performance.
c) NPL has no significant effect toward ROA. It indicates the risks of loan payment by the
debtor if there is a problem of the debtor to pay, and it can decrease the bank’s profitability.
In this research the increasing of NPL will not decrease ROA since the provision of loans
losses can cover the bad debt problems.
d) Simultaneously, all of these independent variables have 0.000 level of significant with
0.345 Adjusted R Square. It means CAR, LDR, NPL having significant influence toward
Page 37 of 53
ROA by 34.5% the remaining 65.5% influenced by other factors outside the research
model.
Islamic Banks:
a) CAR has no significant effect toward ROA. Meaning that Islamic banks do not use capital
efficiently and effectively to do a business activity besides, the lack of community trust is
one of the factors that cause CAR in Islamic banks is not significant toward ROA.
b) FDR has no significant effect toward ROA it indicates the quality of financing. According
to Bank Indonesia Circular Letter No. 12/11/DPNP/2010 standard of FDR ratio is between
85%-110%. No significant effect between FDR and ROA can caused by the financing that
was not optimal and not effective and lack of the circumspection principle by the
management of the bank especially in Islamic banks the profit that will get by the bank is
not from the interest fee but from the profit sharing.
c) While NPF has negative significant effect toward ROA based on the theory the higher
number of NPF will decrease the profitability of the bank so the lower ratio is the better
performance of the bank.
d) Simultaneously, all of these independent variables have 0.000 level of significant with
0.218 Adjusted R. It means CAR, FDR, NPF having significant influence toward ROA
toward ROA by 21.8% the remaining 78.2 % influenced by other factors outside the
research model.
5.2 Recommendation
From the conclusion the researcher can give some recommendation for some parties that can
be useful, which are:
a) Need to give more concerned for Islamic bank to compete with the conventional banks.
Focus and be careful to search the opportunities to push the high number of third party
funds so the optimal financing can happen efficiently and effectively.
b) Islamic banks can duplicate the strategy of conventional banks but still in the syariah
principle.
c) Conventional banks still keep improving to be a better performance and compete in
Indonesia or international by maintain the public trust and investor trust.
Page 38 of 53
d) For further research, the researcher recommends conducting both for internal and external
factors that influenced ROA in conventional and Islamic banks so the most significance
factors can be shown either in internal or external factors.
Page 39 of 53
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Page 42 of 53
APPENDIX
Table 2.1. for Research Gaps
No Researcher Research’s Title Methodology Result and Conclusion
1 Erika (2015) Financial Ratio
and Its Influence
to Profitability in
Islamic Banks
Multiple
Regression
Analysis
CAR, NPF, FDR, BOPO
simultaneously effect to
ROA. CAR, NPF and FDR
partially no significant effect
to ROA while BOPO
partially significant effect to
ROA.
2 Anggrainy
(2011)
Analysis of CAR,
NPL, BOPO,
NIM and LDR
toward ROA in
Commercial
Banks that listed
in IDX period
2005-2009
Multiple
Regression
Analysis
CAR, NIM, NPL, BOPO,
and LDR have significant
impact on ROA while NIM
have no significant impact on
ROA
3 Kristiani,
Yovin (2016)
Factors Affecting
Bank
Performance:
Cases of Top 10
Biggest
Government and
Private Banks in
Indonesia in
2004-2013
Multiple
Linear
Analysis
CAR has positive significant
effect toward ROA.
Operational efficiency has a
significant negative impact
on ROA. NIM has a
significant positive impact on
ROA. NPL has negative
significant effect toward
ROA. LDR has a significant
positive impact on ROA.
Page 43 of 53
Table 3.1. List of Banks that used (in million)
Conventional Bank Islamic Bank
Name of Banks Total Asset Name of Banks Total Asset
PT Bank ICBC Rp46,137,643 PT Bank Muamalat Indonesia Rp52, 695.732
PT Bank Artha Graha Rp26,639,793 PT Bank BNI Syariah Rp26,676,278
PT Bank Mestika Dharma Rp10,415,916 PT Bank BRI Syariah Rp24,953,941
PT Bank Multiarta Sentosa Rp5,784,800 PT Bank Panin Dubai Syariah Rp7,770,955
PT Bank Nusantara Parahyangan Rp8,382,818 PT Bank Mega Syariah Rp5,478,501
Source: OJK websites and each banks website
Table 4.1. Sampling Data
Conventional Banks Islamic Banks
No Variable Period Basis Data
1 CAR March
2011-
June
2016
Quarterly 110
2 LDR March
2011-
June
2016
Quarterly 110
3 NPL March
2011-
June
2016
Quarterly 110
4 ROA March
2011-
June
2016
Quarterly 110
No Variable Period Basis Data
1 CAR March
2011-
June
2016
Quarterly 110
2 FDR March
2011-
June
2016
Quarterly 110
3 NPF March
2011-
June
2016
Quarterly 110
4 ROA March
2011-
June
2016
Quarterly 110
Page 44 of 53
Table 4.2. Descriptive Data for Conventional Banks
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
CAR 96 9.67 67.00 21.6247 9.84996
LDR 96 68.21 105.49 87.4251 7.97503
NPL 96 .00 3.98 1.3323 1.04636
ROA 96 .16 5.44 1.7385 1.16028
Valid N (listwise) 96
Source: Processing result on secondary data (SPSS 16.0)
Table 4.3. Descriptive Data for Islamic Banks
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
CAR 95 11.03 45.65 16.8787 5.28174
FDR 95 76.53 127.88 95.3636 9.82823
NPF 95 .19 4.61 2.1073 1.06354
ROA 95 -.73 3.57 1.2956 .86253
Valid N (listwise) 95
Source: Processing result on secondary data (SPSS 16.0)
Page 45 of 53
Table 4.4. Multicollinearity Test for Conventional Banks
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) -4.938 1.061 -4.654 .000
CAR .035 .010 .299 3.490 .001 .941 1.063
LDR .066 .013 .457 5.313 .000 .933 1.072
NPL .078 .094 .070 .835 .406 .969 1.032
a. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Table 4.5. Multicollinearity Test for Islamic Banks
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) 1.586 .875 1.812 .073
CAR .007 .018 .043 .384 .702 .675 1.481
FDR .004 .009 .044 .440 .661 .828 1.208
NPF -.369 .086 -.455 -4.269 .000 .733 1.364
a. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Table 4.6. Durbin-Watson Result for Conventional Banks
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate Durbin-Watson
1 .604a .365 .345 .93933 .417
a. Predictors: (Constant), NPL, CAR, LDR
b. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Page 46 of 53
Table 4.7. Durbin-Watson Result for Islamic Banks
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate Durbin-Watson
1 .493a .243 .218 .76252 .680
a. Predictors: (Constant), NPF, FDR, CAR
b. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Table 4.8. Multiple Linear Regression Result for Conventional Banks
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) -4.938 1.061 -4.654 .000
CAR .035 .010 .299 3.490 .001 .941 1.063
LDR .066 .013 .457 5.313 .000 .933 1.072
NPL .078 .094 .070 .835 .406 .969 1.032
a. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Table 4.9. Multiple Linear Regression Result for Islamic Banks
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) 1.586 .875 1.812 .073
CAR .007 .018 .043 .384 .702 .675 1.481
FDR .004 .009 .044 .440 .661 .828 1.208
NPF -.369 .086 -.455 -4.269 .000 .733 1.364
a. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Page 47 of 53
Table 4.10. Simultaneous Result for Conventional Banks
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 46.718 3 15.573 17.649 .000a
Residual 81.176 92 .882
Total 127.894 95
a. Predictors: (Constant), NPL, CAR, LDR
b. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Table 4.11. Simultaneous Result for Islamic Banks
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 17.021 3 5.674 9.758 .000a
Residual 52.911 91 .581
Total 69.932 94
a. Predictors: (Constant), NPF, FDR, CAR
b. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Table 4.12. Significant Partial Test Result of Conventional Banks
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) -4.938 1.061 -4.654 .000
CAR .035 .010 .299 3.490 .001 .941 1.063
LDR .066 .013 .457 5.313 .000 .933 1.072
NPL .078 .094 .070 .835 .406 .969 1.032
a. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Page 48 of 53
Table 4.13. Significant Partial Test Result of Islamic Banks
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) 1.586 .875 1.812 .073
CAR .007 .018 .043 .384 .702 .675 1.481
FDR .004 .009 .044 .440 .661 .828 1.208
NPF -.369 .086 -.455 -4.269 .000 .733 1.364
a. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Table 4.15. Coefficient Multiple Determination Test Result for Conventional Banks
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate Durbin-Watson
1 .604a .365 .345 .93933 .417
a. Predictors: (Constant), NPL, CAR, LDR
b. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Table 4.16. Coefficient Multiple Determination Test Result for Islamic Banks
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate Durbin-Watson
1 .493a .243 .218 .76252 .680
a. Predictors: (Constant), NPF, FDR, CAR
b. Dependent Variable: ROA
Source: Processing result on secondary data (SPSS 16.0)
Page 49 of 53
Table 4.17. Group Statistics Test Result
Group Statistics
GROUP N Mean Std. Deviation Std. Error Mean
CAR Conventional Banks 96 21.6247 9.84996 1.00531
Islamic Banks 95 16.8787 5.28174 .54190
LDRorFDR Conventional Banks 96 87.4251 7.97503 .81395
Islamic Banks 95 95.3636 9.82823 1.00835
NPLorNPF Conventional Banks 96 1.3323 1.04636 .10679
Islamic Banks 95 2.1073 1.06354 .10912
ROA Conventional Banks 96 1.7385 1.16028 .11842
Islamic Banks 95 1.2956 .86253 .08849
Source: Processing result on secondary data (SPSS 16.0)
Page 50 of 53
Table 4.18. Independent Sample Test Result
Levene's Test for
Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
CAR Equal variances
assumed 25.820 .000 4.144 189 .000 4.74595 1.14539 2.48656 7.00534
Equal variances
not assumed
4.156 145.787 .000 4.74595 1.14206 2.48882 7.00308
LDRorFDR Equal variances
assumed 1.419 .235
-
6.133 189 .000 -7.93847 1.29447
-
10.49194 -5.38501
Equal variances
not assumed
-
6.126 180.556 .000 -7.93847 1.29587
-
10.49548 -5.38147
NPLorNPF Equal variances
assumed .322 .571
-
5.076 189 .000 -.77497 .15267 -1.07612 -.47382
Equal variances
not assumed
-
5.076 188.864 .000 -.77497 .15268 -1.07615 -.47379
ROA Equal variances
assumed 4.484 .036 2.992 189 .003 .44296 .14806 .15091 .73502
Equal variances
not assumed
2.996 175.437 .003 .44296 .14783 .15120 .73472
Source: Processing result on secondary data (SPSS 16.0)
Page 51 of 53
Figure 4.1. Histogram for Conventional Banks
Source: Processing result on secondary data (SPSS 16.0)
Figure 4.2. Histogram for Islamic Banks
Source: Processing result on secondary data (SPSS 16.0
Page 52 of 53
Figure 4.3. P-Plot for Conventional Banks
Source: Processing result on secondary data (SPSS 16.0)
Figure 4.4. P-Plot for Islamic Banks
Source: Processing result on secondary data (SPSS 16.0)
Page 53 of 53
Figure 4.5. Scatterplot Result for Conventional Banks
Source: Processing result on secondary data (SPSS 16.0)
Figure 4.6. Scatterplot for Islamic Banks
Source: Processing result on secondary data (SPSS 16.0)