Indonesian Islamic Banking Performance Analysis
Erna Handayani
1
and Naelati Tubastuvi
1
1
Magister Management, Universitas Muhammadiyah Purwokerto, Banyumas-Indonesia
Keywords: Return on Assets, Capital Adequacy Ratio, Financing to Deposit Ratio, Non Performing Financing,
Operating Expense to Operating Income Ratio, Net Operating Margin
Abstract: The performance of Islamic banking in Indonesia must be improved continuously so that it can be
equivalent to conventional banking. Performance can be assessed from several bank health ratios. This
study analyzes the effect of Capital Adequacy Ratio (CAR), Financing to Deposit Ratio (FDR), Non
Performing Financing (NPF), Operating Expense to Operating Income Ratio (BOPO) and Net Operating
Margin (NOM) towards Return on Assets (ROA). The study was conducted on 13 Islamic public banks
registered at Indonesia Financial Service Authority (OJK) during 2012-2017 with multiple linear regression
methods. Partially, the results of the study showed that CAR and BOPO have significant effect towards
ROA, while CAR, FDR, NPF, BOPO and NOM have simultaneous effect on ROA.
1 INTRODUCTION
Public awareness of Islamic banking in Indonesia
has increased after issuance of the Indonesian Ulema
Council Fatwa (Fatwa MUI) Number 1 of 2004
concerning interest and usury. The development of
Islamic banking continues to increase which can be
seen from the growth in the number of Sharia
Commercial Banks, Sharia Business Units and
Islamic People's Financing Banks. Based on
Indonesia Financial Services Authority statistics on
Islamic banking at the end of 2017, there were 13
Sharia Commercial Banks, 21 Sharia Business Units
and 167 Islamic People's Financing Banks.
Based on Indonesia Financial Services Authority
data until August 2017, the total Indonesian Islamic
financial assets (excluding Sharia Shares) reached
Rp 1,048.8 trillion, which consisted of Sharia
Banking assets of Rp 389.74 trillion, Sharia Non-
Bank Financial Industry of Rp 99.15 trillion, and
Markets Sharia capital of Rp. 559.59 trillion.
The total Indonesian Islamic financial assets is
small compared to the total assets of the financial
industry which reached Rp. 13,092 trillion. It
showed that the market share of the Islamic finance
industry only reached 8.01% of the total national
market share. (Press Release: Sharia Financial
Market Share, Indonesia Financial Services
Authority, 2017).
Although the market share of the national
banking and sharia finance industry still has not
reached the expected level (seen from the market
share data), in terms of the magnitude of Indonesian
Islamic financial assets has reached the ninth largest
position in the world with assets around USD 35.6
billion (in 2013). In addition, Indonesia has received
recognition and appreciation from the international
community together with the UAE, Saudi Arabia,
Malaysia and Bahrain are considered to be in a
position to offer lessons to other countries in the
world for sharia finance development. The Indonesia
Financial Services Authority also received the award
as the best regulator in promoting Islamic finance
(Indonesia Financial Services Authority, 2017).
Based on the data above, Islamic banking in
Indonesia is required to continue improving the
performance of its business in facing the challenges
from both in international competition and an
increase in the market share of domestic banking. In
addition, a significant increase in profitability is
needed for the development of the position of
Islamic banking in Indonesia. Data from Indonesia
Financial Services Authority (2017) which showed
Islamic banking performance from its Return on
Assets (ROA) is still in the range of 0.63-1.12%.
This number still lags behind general conventional
banking, which ranges from 2.35-2.50%.
1244
Handayani, E. and Tubastuvi, N.
Indonesian Islamic Banking Performance Analysis.
DOI: 10.5220/0009500612441250
In Proceedings of the 1st Unimed International Conference on Economics Education and Social Science (UNICEES 2018), pages 1244-1250
ISBN: 978-989-758-432-9
Copyright
c
2020 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
The Government through Indonesia Financial
Services Authority has made the direction of the
Indonesian Islamic banking development which
called the Sharia Banking Roadmap 2015-2019. This
is proof that the government is starting to give more
attention to the continuous growth of Islamic
banking (Indonesia Financial Services Authority,
2017)
Another regulator, Bank Indonesia, has
established a risk-based bank rating system
contained in Bank Indonesia Regulation no.
1/13/2011 concerning the assessment of risk-based
bank rating of commercial banks. In this regulation,
banks are required to conduct a self-assessment of
the health of banks with a risk-based approach (Risk
based Bank Rating-RBBR) both individually and on
a consolidated basis. The purpose of evaluating the
risk-based bank rating is to obtain an overview of
the health of the bank so that it can be used as an
input for the bank in developing future business
strategies and plans and improving weaknesses that
could potentially disrupt the bank's performance.
(Indonesian Bankers Association, 2015)
Assessment of the bank health level, both
individual and consolidation with the assessment
factors including:
1. Risk Profile
2. Good Corporate Governance (GCG)
3. Earning
4. Capital
The risk profile consists of credit risk, market
risk, operational risk, liquidity risk, strategic risk,
compliance risk, legal risk, reputation risk, and risk
profile ranking. Good Corporate Governance (GCG)
consists of structure, process, results and GCG
ranking. Earning (Rentability) consists of
performance, source, sustainability, and rentability
ratings. Capital consists of adequacy, management
and capital rating (Indonesian Bankers Association,
2015).
Banking performance will increase with a good
level of health. Banking performance concerns the
study of profitability. There are two ratios which are
usually used to measure banking performance,
namely Return on Assets (ROA) and Return on
Equity (ROE).
Return on Asset as a benchmark for bank
profitability is influenced by several factors
including internal factors and external banking
factors. Internal factors include capital risk, liquidity
risk, credit risk and operational risk.
Based on the background above, this study tried
to measure the effect of Capital Adequacy Ratio
(CAR), Financing to Deposit Ratio (FDR), Non
Performing Financing (NPF), Operating Expense to
Operating Income Ratio (BOPO) and Net Operating
Margin (NOM) towards Return on Asset (ROA).
This study was conducted on Islamic banking in
Indonesia, especially Sharia Commercial Banks
registered at Indonesia Financial Services Authority
during 2012-2017.
2 THEORICAL FRAMEWORK
Based on Circular Letter of Bank Indonesia No.6 /
23 / DPNP dated May 31, 2004 concerning the Risk-
based Bank Rating System for Commercial Banks,
there are eight indicators used to measure the level
of profitability, namely return on assets, return on
equity, net interest margin, operating expense to
operating income, development of operating profit,
composition of the portfolio of earning assets and
diversification of income, application of accounting
principles in revenue recognition, prospects for
operating profit.
The ratio commonly used in measuring the level
of rentability / profitability is ROA (Hery, 2016).
ROA is a measurement of the bank's financial
performance in obtaining profit before tax, which is
generated from the total assets of the bank (Circular
Letter of BI No.3 / 30 / DPNP December 14, 2001).
ROA can be calculated by dividing profit after tax
by total assets (Sartono, 2001).
Based on Circular Letter No.9 / 24 / DPBS /
2007 concerning the Sharia risk-based bank rating
system, Bank Indonesia stipulates a minimum ROA
of 1.26% or greater than 1.25% to determine the
ROA for a health bank. So that the greater the ROA
shows the bank's performance the better, because the
rate of return is greater (Husnan, 1992). ROA as a
reflection of the bank's financial performance is
influenced by factors as follows:
2.1 Bank Capital
Assessment of capital factors includes an assessment
of the level of capital adequacy and capital
management. (Indonesian Bankers Association,
2016). There are several ratios used to monitor bank
capital positions, one of which is Capital Adequacy
Ratio (Indonesian Bankers Association, 2016).
According to Bank Indonesia regulations, Capital
Adequacy Ratio is a ratio that shows how much the
bank assets containing risk (credit, participation,
securities, bills on other banks) that are also financed
from their own capital in addition to obtaining funds
from outside sources. Capital Adequacy Ratio is
obtained by dividing Capital with Risk Weighted
Assets or RWA (Circular Letter of BI, 2011).
Based on the Indonesia Financial Services
Authority Regulation Number 21 / POJK.03 / 2014
concerning about Minimum Capital Requirement for
Indonesian Islamic Banking Performance Analysis
1245
Sharia Commercial Banks, the provision of
minimum capital is determined as follows:
a. 8% (eight percent) of Risk Weighted Assets for
banks with a risk profile rating of 1 (one);
b. 9% (nine percent) up to less than 10% (ten
percent) of RWA for banks with a risk profile
rating of 2 (two);
c. 10% (ten percent) up to less than 11 (eleven
percent) of RWA for banks with a risk profile
rating of 3 (three); or
d. 11% (eleven percent) to 14% (fourteen percent)
of RWA for banks with a risk profile rating of 4
(four) or 5 (five).
The greater the CAR ratio, the bank has the
potential to increase profits. In other words, CAR
affects ROA. This has been proven by Kishori
(2017), Anggreni, (2014), Shamki, Alulis and
Sayari, (2016), Margaretha (2017), Chou and
Buchdadi, (2016), Sukirmo (2016), Sudiyanto
(2010), Nahar and Prawoto, (2017), Kinanti, (2017),
Amelia, (2015), Andhina Dyah Sulityowati, Noer
Azam Achsani, (2017), Hantono, (2017), M, Ali and
Habbe, (2012) and Bachri (2013). Meanwhile, some
research showed different results and indicates that
CAR does not have a significant effect on ROA
(Sudiyatno, 2013, and Wibowo and Syaichu, 2013).
2.2 Liquidity
Banks are very concerned about fulfilling their
liquidity because the most important measure of
public trust is about whether the bank can fulfill the
withdrawal of funds made by the customers for their
interests anytime. It is in addition to fulfill the
conditions set by the monetary authorities and
correspondent banks where banks maintain non-
bank accounts (Ericson Leon Boy Sonny, 2007).
In the banking industry, the liquidity ratio is
known as the Loan to Deposit Ratio. In Islamic
banking, the term of loan is known as financing
(Antonio, 2001). This ratio is known as Financing to
Deposit Ratio (FDR). FDR is a ratio to measure the
composition of the amount of financing provided
compared to the amount of public funds and the
capital used (Kasmir, 2012). The higher this ratio
shows the lower the ability of bank liquidity because
the amount of funds needed for financing is getting
bigger (Dendawijaya, 2009).
Based on Financial Services Authority
Regulation Number 3 / POJK.03 / 2016 concerning
Islamic People's Financing Bank is setting the
Financing to Deposit Ratio ranges from 78% -100%.
If the FDR is under the standard set by Indonesia
Financial Services Authority, it shows the lack of
effectiveness of the bank in channeling its financing,
so that there is a loss of opportunity for profit. If the
FDR is more than 100%, the financing channeled
exceeds the funds collected so that the bank will
experience a shortage of funds to fulfill its
obligations. This high and low ratio indicates the
level of liquidity of the bank, the higher the FDR
number of a bank, described as a bank that is less
liquid compared to banks that have a smaller ratio.
FDR is calculated from the amount of financing
divided by third party funds (Muhammad, 2005).
Several studies have examined the effect of liquidity
(FDR) on profitability (ROA) with a significant
effect that was carried out by Zakaria (2015),
Farooq, Qasim and Asad, (2015), Malik et al.,
(2014), Chou and Buchdadi, (2016), Hantono,
(2017) dan Sukirmo (2006), Kishori (2017),
Andhina Dyah Sulityowati, Noer Azam Achsani,
(2017) dan M, Ali and Habbe, (2012). Meanwhile,
research from Pramuka, (2010) showed that FDR
has no significant effect on ROA.
2.3 Credit Risk
Credit risk is also called financing risk. Financing
risk is the risk due to the failure of the debtor and /
or other parties in fulfilling the obligation to pay off
financing at the bank. In financing activities, both
commercial financing and consumption financing,
there is a possibility that the debtor cannot fulfill the
obligation to the bank for various reasons such as
business failure, because the character of the debtor
who does not have good faith to fulfill obligations to
the bank, or indeed there is an error from the bank
itself in the financing approval process (Indonesian
Bankers Association, 2015).
Sharia Commercial Banks need to improve
management of their financing risks so that the level
of Non Performing Financing does not exceed the
provisions of Indonesia Financial Services
Authority. Financial Services Authority Regulation
Number 3 / POJK.03 / 2016 concerning Islamic
People's Financing Bank have set that the ratio of
Non-Performing Financing is a maximum of 7% of
total financing.
According to Bank Indonesia regulations in
2012, Non Performing Financing is calculated by
adding all of KL, D, M Financing divided by total
financing. The higher the NPF level of a bank, the
lower the income that must be obtained. Vice versa,
if the NPF level is low, the level of bank income will
increase. Thus, increasing NPF is considered to have
a significant effect on bank performance. Previous
research that proved the significant effect of NPF
towards ROA was found by Yoppy and
Purbaningsih, (2014), Zakaria (2015), Anggreni,
(2014), Amelia, (2015), Pramuka, (2010), Hantono,
(2017), Wibowo (2013) and Bachri (2013), Nahar
and Prawoto, (2017), Kinanti, (2017) and Sudiyanto
(2010). Whereas, previous research from M. Ali and
Habbe, (2012) found that NPF has no significant
effect on ROA.
UNICEES 2018 - Unimed International Conference on Economics Education and Social Science
1246
2.4 Operational Risk
Operational risk is a risk that happens due to
inadequate and / or non-functioning internal
processes, human errors, system failures, or the
presence of external problems that affecting bank
operations (Ali, 2006). Operational risk is the risk of
loss because the bank works inefficiently,
uneconomically, ineffectively, not smooth,
insecurely, and disorderly. Generally, bank failures
are caused by operational risks. In the CAMEL
approach, the measurement of operational risk is
reflected in the BOPO ratio. The higher BOPO ratio
indicates high operational risk (Hayati, 2017).
Financial Services Authority Regulation Number
3 / POJK.03 / 2016 concerning Islamic People's
Financing Bank have set that the BOPO ratio
(Operating Expense to Operating Income) is a
maximum of 94% (Indonesian Bankers Association,
2015).
If a bank has BOPO more than the predetermined
provisions, the bank is included in the inefficient
category, because the higher the BOPO means that
the increase in operational costs is greater than the
increase in operating income so that the profit
earned will eventually decreases. According to
Suyanto, (2016), BOPO (Operating Expense to
Operating Income) can be measured by dividing the
operating expenses with operating income.
Previous research have showed that BOPO has
effect towards the profitability (ROA) (Sudiyatno,
2013; Nahar and Prawoto, 2017; Amelia, 2015;
Chou and Buchdadi, 2016; Sukirmo, 2006;
Sudiyanto, 2016; Wibowo, 2013; M, Ali and Habbe,
2012; and Margaretha 2015). Meanwhile, research
from Malik et al., (2014) showed that BOPO has no
significant effect on ROA.
2.5 Net Operating Margin (NOM)
Net Operating Margin (NOM) is a ratio to assess the
bank's profitability. NOM is calculated by dividing
operating profit by the average of earning assets
(Indonesian Bankers Association, 2016). Operating
profit is annual net interest income deduced by
annual operating expenses. Earning assets are assets
that generate interest both on the balance sheet and
on TRA. Average earning assets are calculated by
adding the total productive assets positions from
January to June divided by 6 (Indonesian Bankers
Association, 2016). Banks are required to maintain a
positive NOM value. The higher the NOM, the
higher the bank's income generated by the bank's
productive assets. The previous research supported
the statement was the research from M. Ali and
Habbe, (2012), Subandi (2013), Sudiyatno, 2013),
Andhina Dyah Sulityowati, Noer Azam Achsani,
(2017). However, the opposite results found by
(Rindhatmono, 2005).
3 RESEARCH METHOD
This study uses secondary data in the form of
financial statements of Islamic Commercial Banks
presented by Indonesia Financial Services Authority
website, ojk.go.id, during 2012-2017. Data is
collected with time series, namely quarterly financial
statements.
The analytical model used is multiple regression
analysis model. The analysis technique that will be
used in this study is multiple linear regression
analysis. Multiple linear regression analysis measure
the strength of the relationship between two or more
variables, also shows the direction of the
relationship between assumed to be random /
stochastic which means it has a probabilistic
distribution (Ghozali, 2016). In this study, a
regression test was performed with an independent
variable (x) towards the dependent variable (y). The
multiple linear regression equation used are:
Y
it
= α + β
1
X
1it
+ β
2
X
2it
+ β
3
X
3it
+ β
4
X
4it
+ β
5
X
5it
+ e
it
Where :
Y : Financial Performance (ROA)
i : Islamic Commercial Banks
t : Year
α : Constant/Intercept
β : Regression Coefficient
X_1 : Capital Adequacy Ratio
X_2 : Financing to Deposit Ratio
X_3 : Non Performing Financing
X_4 : BOPO ratio (Operating Expense to Operating
Income)
X_5 : Net Operating Margin
e : error
The hypothesis in this study are:
1. Capital with CAR indicators affects
performance (ROA) in Sharia Commercial
Banks in Indonesia during 2012-2017.
2. Liquidity Risk with the FDR indicator affects
the performance (ROA) of Islamic Commercial
Banks in Indonesia during 2012-2017.
3. Credit Risk with the NPF indicator affects the
performance (ROA) of Islamic Commercial
Banks in Indonesia during 2012-2017.
4. Operational risks with BOPO indicators affect
performance (ROA) in Islamic Commercial
Banks in Indonesia during 2012-2017.
5. Rentability with NOM indicators influences
performance (ROA) in Islamic Commercial
Banks in Indonesia during 2012-2017.
Before testing multiple linear analysis of the
research hypothesis, it is necessary to test a classic
Indonesian Islamic Banking Performance Analysis
1247
assumption first. The classic assumption test aims to
find out and test the feasibility of the regression
model used in this study. The classic assumption test
consists of normality test, multicollinearity test,
autocorrelation test, and heteroscedasticity test
(Ghozali, 2016).
4 ANALYSIS
Table 1 showed that the sig. value of normality test
is 0.603. It was concluded that the normality
assumption of research data was fulfilled because it
was greater than 0.05. (Ghozali, 2016)
Table 1: Normality Test
One-Sample Kolmogorov-Smirnov Test
Unstandardized
Residual
N
215
Normal
Parameters
a,
b
Mean
-.0389634
Std.
Deviation
.35537830
Most
Extreme
Differences
Absolute
.052
Positive
.052
Negative
-.027
Kolmogorov-Smirnov Z
.764
Asymp. Sig. (2-tailed)
.603
a. Test distribution is Normal.
b. Calculated from data.
Multicollinearity test results as shown in Table 2
obtained a Tolerance value of > 0.1, while the VIF
value is < 10, meaning that there were no symptoms
of multicollinearity (Suliyanto, 2011).
Table 2: Multicollinearity Test
Model
Tolerance
VIF
1
(Constant)
CAR
.726
1.377
FDR
.829
1.206
NPF
.672
1.487
BOP
O
.511
1.955
NOM
.684
1.463
Autocorrelation test results showed in table 3.
indicates that the Durbin Watson value of 0.772 are
found between -2 and 2, so it is concluded that there
is no data autocorrelation (Santosa, 2012).
Tabel 3: Autocorrelation Test
Model Summary
b
Mod
el
Std. Error of
the Estimate
Durbin-
Watson
1
.31112
.779
a. Predictors: (Constant), NOM, CAR, FDR,
NPF, BOPO
b. Dependent Variable: ROA
Table 4. showed the results of Heteroscedasticity
Test. The sig value for the independent variable is
greater than 0.05, which means there is no
heteroscedasticity (Suliyanto, 2011).
Table 4: Heteroscedasticity Test
Model
Standardized
Coefficients
T
Sig.
Beta
1
(Constant)
-
.631
.529
CAR
.052
.618
.537
FDR
-.063
-
.786
.433
NPF
.092
1.05
9
.291
BOPO
.151
1.54
3
.125
NOM
.042
.483
.630
a. Dependent Variable: abs_res2
After all the classical assumption tests are carried
out and resulted that all the data can be used, then
multiple linear regression analysis is carried out. The
following are the equations obtained from the test
results:
ROA =7,508+0.09CAR+0,01FDR+0,13 NPF
0,076BOPO+0,011NOM
The results showed that the value of ROA constant
is 7.508. CAR regression coefficient is 0.09
indicating that a 1% increase from the CAR value
will increase ROA by 0.09% assuming other
variables remain. The result is similar with FDR,
NPF and NOM. BOPO regression coefficient is -
0.076 which means that if there is a reduction in
BOPO of 1%, it will increase the ROA by 0.076.
UNICEES 2018 - Unimed International Conference on Economics Education and Social Science
1248
Table 5. showed the coefficient of determination test
with the results of the Adjusted R Square value is
0.861. It means that 86.1% percent ROA can be
affected by the simultaneous effect from
independent variables namely CAR, FDR, NPF,
BOPO and NOM, while the rest are influenced by
other variables.
Table 5: Coefficient of Determination Test
Model Summary
Mode
l
R
R
Square
Adjusted
R Square
Std. Error of
the Estimate
1
.930
a
.864
.861
.31112
a. Predictors: (Constant), NOM, CAR, FDR,
NPF, BOPO
Table 6 showed the results of the F test where the
results is 0,000 which means that all the independent
variables simultaneously affect the dependent
variable.
Table 6 Results of the F Test
ANOVA
a
Model
Sum
of
Square
s
Df
Mean
Square
F
Sig.
Regressio
n
128.5
48
5
25.710
265.6
14
.000
b
Residual
20.230
209
.09
7
Total
148.77
8
214
a. Dependent Variable: ROA
b. Predictors: (Constant), NOM, CAR, FDR, NPF, BOPO
Coefficients
a
Table 7: Showed the Results of T test
Model
Unstandardiz
ed
Coefficients
Standard
ized
Coeffici
ents
t
Sig.
B
Std.
Error
Beta
1
(Consta
nt)
7.508
.298
25.173
.000
CAR
.009
.002
.120
3.995
.000
FDR
.001
.001
.031
1.118
.265
NPF
.013
.017
.023
.733
.464
BOPO
-.076
.003
-.864
-24.221
.000
NOM
.011
.008
.047
1.525
.129
a. Dependent Variable: ROA
Table 7 showed the results of T test. It found that
CAR results significantly affects ROA with a sig
value of 0,000 > 0.05. The result is similar with the
BOPO value. The sig. value of FDR, NPF and NOM
are greater than 0.05, so they are not significant.
Hypothesis Test 1
The results of data analysis show that Hypothesis 1:
CAR has a significant effect on ROA, supported.
This result supports the opinion that with the
addition of capital, banks have greater opportunities
to increase profits. The results of hypothesis 1 are in
line with previous researches from Kishori (2017),
Anggreni, (2014), Shamki, Alulis and Sayari,
(2016), Margaretha (2017), Chou and Buchdadi,
(2016), Sukirmo (2016), Sudiyanto (2010).
Hypothesis Test 2
The results of hypothesis 2 showed different results.
The result showed that T test value of more than
0.05, which is 0.265, the conclusion of the FDR has
no effect towards ROA. This result is the same as
previous result by Pramuka, (2010). So, hypothesis 2
is not supported.
Hypothesis Test 3
The test of the effect of NPF towards ROA obtained
a significant value of 0.464, it is concluded that
hypothesis 3 is not supported. The result is
supported by previous research from M, Ali and
Habbe, (2012).
Hypothesis Test 4
Significant affect towards ROA is then obtained
from BOPO. In general, effective costs will increase
profits. So, hypothesis 2 is supported. The result is
supported by previous researches from Sudiyatno,
(2013), Sudiyatno, (2013), Amelia, (2015), Chou
and Buchdadi, (2016), Sukirmo (2006), Sudiyanto
(2016), Wibowo (2013) and M. Ali and Habbe,
(2012), Margaretha (2015).
Hypothesis test 5
Indonesian Islamic Banking Performance Analysis
1249
The result of t test showed that the value is 0.129,
then hypothesis 4 is not supported. This result is
supported by previous research from Ferdi
Rindhatmono (2005).
5 CONCLUSION
The results showed that CAR and BOPO have a
significant effect towards ROA, while FDR, NPF
and NOM have no significant effect towards ROA.
In the other hand, FDR, NPF and NOM have a
simultaneous effect on ROA with a coefficient level
of 86.1%. Based on 5 years’ observation, other
factors that affect ROA in Indonesian Islamic
Banking still need to be explored. The significant
effect of CAR and BOPO have been theoretically
proven. However, it needs to be reexamined why
FDR, NPF and NOM has no effect towards ROA.
Based on existing theories, credit risk and liquidity
risk are important for banks because during the
period of 2012-2017 there were several Islamic
banks that were in the early stages of developing and
some were newly founded. It is because banks are
still focused on aspects of capital and performance
efficiency.
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