p–ISSN: 2723 - 6609 e-ISSN: 2745-5254
Vol. 5, No. 10, October 2024 http://jist.publikasiindonesia.id/
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3903
The Influence of Internal and External Factors on Non-
Performing Financing at Islamic Commercial Banks in 2018-
2022
Putri Novia Rahmawati
1*
, Gita Syafira Setiady
2
, Mardi
3
, Itah Miftahul Ulum
3
Universitas Swadaya Gunung Jati, Indonesia
Email: [email protected]
1*
, [email protected]
2
,
[email protected]
3
, [email protected]
4
*Correspondence
ABSTRACT
Keywords: non-
performing financing
(NPF);
internal and external
factors;
Islamic commercial banks.
Financing is one of the main functions in Islamic banking,
the risk that can occur in such financing is Non-Performing
Financing (NPF). This study aims to determine the factors
that affect the NPF of Islamic commercial banks in the
period 2018-2022, the variables used in this study are Capital
Adequacy Ratio (CAR), Financing to Deposit Ratio (FDR),
Inflation, and Gross Domestic Product (GDP), this study
uses a quantitative approach, using panel data regression
analysis with the Generalized Least Square (GLS)
estimation method. Partially, the CAR variable has a positive
effect on NPF, the FDR variable hurts NPF, while the
Inflation and GDP variables do not affect NPF. Based on
analysis and discussion, the Capital Adequacy Ratio (CAR)
hurts Non-Performing Financing (NPF). This indicates that
the higher the CAR of a bank, the more credit can be given
to the public. Banks can finance their assets with higher
CARs without the risk of bad loans affecting the health of
Islamic banks.
Introduction
People are becoming more interested in Islamic banks due to their interest-free
system and use of profit-sharing mechanisms. The various types of financing and
fundraising options provide customers with many choices. The services offered adhere to
Islamic law and are free from elements of usury (riba), uncertainty (gharar), and haram
(prohibited). Financing in Islamic banks is a primary source of income. However, the
distribution of financing carries various risks, such as economic crises that may cause
customers to be unable to pay or delay payments.
Islamic banks channel customer funds through investments and financing. The
financing products offered by Islamic banks can be utilized by customers in need of funds
and who meet the specified requirements. The increasing growth in financing becomes a
major driver of the bank’s profits and profit-sharing system. Larger funds from cost-
sharing contribute to the profitability of Islamic banks. (Effendi et al., 2017).
Putri Novia Rahmawati, Gita Syafira Setiady, Mardi, Itah Miftahul Ulum
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3904
As a business entity, Islamic banks aim to optimize profits that can be achieved by
expanding distribution and reducing costs. Distribution expansion can be an effective
strategy for increasing market share and customer reach. However, credit risks may arise
during distribution expansion if the bank is not careful in conducting risk analysis and
taking measures to mitigate such risks.
The Non-Performing Financing (NPF) ratio is used to evaluate how well the
management of an Islamic bank handles problematic financing by balancing productive
assets. NPF is also a comparison between the amount of bad credit and the total financing
provided by the bank (Ratugfirli & Sugiyanto, 2020).
The Capital Adequacy Ratio (CAR) illustrates the bank’s capacity to bear losses
from its risky assets. The purpose of CAR is to ensure that the bank has sufficient capital
to cover losses due to bad loans, fulfill obligations to customers, and maintain financial
stability.
The Financing to Deposit Ratio (FDR) is a liquidity component. FDR explains how
a bank compares Third-Party Funds (DPK) to the amount of loans provided, and this can
be calculated using this ratio (Tsania et al., 2022).
Inflation is a phenomenon of a continuous increase in prices, bringing negative
consequences for society. Rising inflation results in a decrease in real income, causing
the purchasing power of the public to decline, which has implications for reducing the
ability of the public to meet basic needs and fulfill financial obligations (Nuraliyah, 2021).
Such fluctuations are a normal part of everyday life.
Gross Domestic Product (GDP) is an economic measure that calculates the market
value of all final products, namely goods and services made within a country over a
certain period. A country's economic well-being is reflected by GDP. An increase in GDP
indicates higher productivity, which drives sales and boosts trade. (Soekapdjo et al.,
2019). Economic improvement alongside rising public income encourages debtors to
repay loans to banks. Increased repayment rates will reduce bad credit. (Purba &
Darmawan, 2018).
Figure 1
NPF, CAR, FDR, Inflation, and GDP Graph in Islamic Commercial Banks
The Influence of Internal and External Factors on Non-Performing Financing at Islamic
Commercial Banks in 2018-2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3905
According to the figure above, the NPF ratio tends to decrease from 2018 to 2022. In 2018,
it stood at 4.27%, which is considered a good indicator as it remains below 7%. In the following
years, the ratio stayed below 7%, indicating that the bank's condition was still healthy and
performing well. However, credit risk can arise, potentially increasing the NPF value. Financing
risk occurs when the debtor or another party fails to fulfill their obligations to the bank. One of
the factors contributing to the decline in NPF in Islamic Commercial Banks (BUS) is the increase
in financing, the decrease in inflation, and the stability of interest rates.
Many studies have examined the influence of various NPF variables. Research by (Wijaya,
2023)Found that the CAR variable affects NPF, while Purnamasari & Mushdholifah (2016) found
no effect. (Wijaya, 2023) Found that the FDR variable influences NPF, while research by Fatimah
& Izzaty (2022) showed no effect. (Nugrohowati & Bimo, 2019) Demonstrated that inflation has
no impact on NPF, while other studies, such as (Bakhtiar Purkon et al., 2023), indicated that
inflation does influence NPF. Studies by Damahur et al. (2018) and Arinda et al. (2022) found
that GDP affects NPF, whereas Kuswaharini et al. (2022) and Purwaningtyas (2020) found no
significant effect of GDP on NPF.
Previous studies have identified several variables influencing the NPF of Islamic
commercial banks. To fully understand these factors, further research is necessary. The purpose
of this study is to determine the influence of CAR, FDR, Inflation, and GDP on NPF in Islamic
Commercial Banks during 2018-2022.
Method
This study is basic research, using a quantitative approach. The data was processed
using EViews 12 through panel data regression analysis. Panel data combines cross-
sectional and time-series data. (Basuki & Suwarno, 2021). The best model approach for
estimating panel data regression, namely the Random Effect Model (REM), was
determined through a series of statistical tests, including the Chow Test, Hausman Test,
and Lagrange Multiplier Test. The REM was selected after considering alternative
models, including the Common Effect Model (CEM), Fixed Effect Model (FEM), and
REM itself.
This research utilized the annual financial reports of Islamic Commercial Banks for
2018–2022. Data was collected through literature reviews, journals, articles, bank
financial reports, and publications from BPS (Statistics Indonesia) and OJK (Financial
Services Authority). The study sample consists of 10 Islamic Commercial Banks out of
the 13 registered with OJK. These banks were selected based on the availability of
complete financial reports for the 2018-2022 period and the completeness of the
necessary research data.
This study investigates various internal and external bank components. The
independent variables used in this research include internal bank factors, such as Capital
Adequacy Ratio (CAR) (X
1
) and Financing to Deposit Ratio (FDR) (X
2
). External bank
factors include Inflation (X
3
) and Gross Domestic Product (GDP) (X
4
). The dependent
variable in this study is Non-Performing Financing (NPF).
Descriptive Analysis
Putri Novia Rahmawati, Gita Syafira Setiady, Mardi, Itah Miftahul Ulum
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3906
Descriptive analysis is a research method used to describe, present, and summarize
the data.
Panel Data Regression Model Selection Test
1. Chow Test
This test compares and determines whether to use the Common Effect Model or
Fixed Effect Model for panel data analysis, based on the hypothesis:
H0: Common Effect Model.
H1: Fixed Effect Model.
The null hypothesis (H0) is rejected and the alternative hypothesis (H1) is accepted,
as the value of F hit > Fα, indicating the Fixed Effect Model (FEM) is the chosen model.
2. Hausman Test
In this step, statistical tests are used to determine the most suitable model between
the Fixed Effect Model and the Random Effect Model. The hypothesis is as follows:
H0: Fixed Effect Model.
H1: Random Effect Model.
The result shows H hit < Chi-Square, leading to the selection of the Random Effect
Model (REM).
Lagrange Multiplier (LM) Test
The Lagrange Multiplier (LM) Test is used to determine whether the Random Effect
Model is more suitable than the Common Effect Model for panel data analysis. The
hypothesis is as follows:
H0: Random Effect Model.
H1: Common Effect Model.
The Breusch-Pagan probability value is 0.0000 < 0.05, indicating that the best
model to use is the Random Effect Model (REM).
Random Effect Model (REM)
Panel data is estimated using this model, where the disturbance variables may be
correlated between individuals or across time. Each company accommodates error terms
within the REM. The advantage of using REM is that it eliminates heteroskedasticity.
This model is also known as the Error Component Model (ECM) or Generalized Least
Square (Basuki, 2021).
Panel Data Regression Equation
The panel data regression equation for this research is:
NPF
it =
α
it
+ β
1
CAR
it
+ β
2
FDR
it
+ β
3
INFLATION
it
+ β
4
GDP
it
€
it
i = Cross-sectional unit
t = Period year
Classical Assumption Test
Since this research uses the Generalized Least Square (GLS) estimation method,
the classical assumption tests used are only normality and multicollinearity.
Normality Test
The Influence of Internal and External Factors on Non-Performing Financing at Islamic
Commercial Banks in 2018-2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3907
This test ensures that the linear regression model can be used for confirmation or
prediction. It is important to test the normality of the residual data distribution.
Multicollinearity Test
Multicollinearity indicates a strong correlation (r > 0.90) between two or more
independent variables within a model.
Hypothesis Testing (T-Test)
After formulating the hypothesis, hypothesis testing is conducted. This involves
using sample data to test the statistical hypothesis of a population (Niuryadi et al., 2017).
Coefficient of Determination (R²)
The coefficient of determination (Adjusted R²) is a measure of how much the
independent variables explain the dependent variable's behavior (Ghazali, 2018). The
larger the value of the coefficient of determination, the better the independent variables
explain the dependent variable's behavior.
This study employs the following research model:
Figure 2
Research Model
Results and Discussion
Descriptive Analysis
Capital Adequacy
Ratio (CAR)
X
1
Financing to Deposit
Ratio (FDR)
X
2
Inflation
X
3
Gross Domestic
Product (GDP)
X
4
Non-Performing
Financing (NPF)
Y
Putri Novia Rahmawati, Gita Syafira Setiady, Mardi, Itah Miftahul Ulum
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3908
Table 5
Descriptive Analysis Results
a. As seen in the table above, the CAR variable (X
1
) has a minimum value of 0.1234 and
a maximum value of 1.4968. The mean value is 0.2950, and the standard deviation is
0.2033.
b. The FDR variable (X
2
) has a minimum value of 0.3833 and a maximum value of
1.9673. The mean value is 0.8497, and the standard deviation is 0.2193.
c. The Inflation variable (X
3
) has a minimum value of 0.0156 and a maximum value of
0.0421. The mean value is 0.0280, and the standard deviation is 0.0093.
d. The GDP variable (X
4
) has a minimum value of -0.0207 and a maximum value of
0.0531. The mean value is 0.0342, and the standard deviation is 0.0283.
Panel Data Regression Model Selection Test
Table 6
Chow Test Results
a
ffect Test
Statistic
Cross-s
i
ection F
15.897316
Cross-s
i
ection Chi-
sq
i
uar
i
e
80.214525
Based on the data analysis, the fixed effect model is more appropriate than the
common effect model. This is based on the results of the Chow test, which shows a
probability value of 0.000 < 0.05, indicating that the null hypothesis is rejected.
Furthermore, the probability values of cross-section F and Chi-square are both less than
alpha 0.05, suggesting that the fixed effect model is better suited for explaining the
analyzed data. A Hausman test is conducted to confirm this conclusion and ensure that
the fixed effect model is the most appropriate.
Hausman Test
Table 7
Hausman Test Results
NPF
CAR
FDR
I
INFLATION
GDP
Mean
0.015938
0.295040
0.849710
0.028080
0.034260
Median
0.011650
0.240300
0.865850
0.030300
0.050200
Max.
.
0.049500
1.496800
1.967300
0.042100
0.053100
Min.
.
0.000200
0.123400
0.383300
0.015600
-
0.020700
Std. Dev.
0.015123
0.203348
0.219361
0.009385
0.028361
Skewness
0.662028
4.306034
2.294996
0.
107289
-
1.355107
Kurtosis
2.116673
25.62854
15.04901
1.788644
3.027963
Jaque
-
Bera
5.277898
1221.288
346.3473
3.152971
15.30425
Prob
.
0.071436
0.000000
0.000000
0.206700
0.000475
Sum
0.796900
14.75200
42.48550
1.404000
1.713000
Sum Sq. Dev.
0.011207
2.026162
2.357842
0.004316
0.039413
Observation
50
50
50
50
50
The Influence of Internal and External Factors on Non-Performing Financing at Islamic
Commercial Banks in 2018-2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3909
Test S
i
ummary
Chi-Sq.
Statistic
Chi-Sq. d.f.
Prob.
Cross-section
Random
0.397601
4
0.9827
Through the Hausman test, we can compare and select the most suitable model
between fixed effect and random effect models. This decision is based on the probability
value of the cross-section random test. If the p-value < 0.05, the chosen model is the
random effect model. The Hausman test is used to compare or choose the best model
between the fixed effect and random effect models, done by looking at the probability
value for the cross-section random to select the best model.
Lagrange Multiplier (LM) Test
Table 8
Lagrange Multiplier (LM) Test Results
According to the table above, the Breusch Pagan (BP) probability value is 0.0000,
lower than the alpha value of 0.05. This indicates the rejection of the null hypothesis. As
a result, based on the LM test, the random effect model is the most appropriate to use.
Panel Data Regression Equation Y = 0.009507 + (-0.016577) X
1
+ 0.014109 X
2
+
0.021398 X
3
+ (-0.037019) X
4
a. The constant value is 0.009507, meaning that without the CAR (X
1
), FDR (X
2
),
Inflation (X
3
), and GDP (X
4
) variables, the NPF (Y) variable will increase by 1%.
b. Based on the data processing results, the partial beta coefficient value of the CAR
variable (X
1
) is -0.016577. If other variables remain constant and decrease by 1%, NPF
(Y) will decrease by 2%. Conversely, if X
1
increases by 1%, NPF (Y) will increase by
2%.
c. The beta coefficient value of the FDR variable (X
2
) is 0.014109. If other variables
remain constant and X
2
increases by 1%, NPF (Y) will decrease by 1%. Conversely,
if X
2
decreases by 1%, NPF (Y) will increase by 1%.
d. The beta coefficient value of the Inflation variable (X
3
) is 0.021398. If other variables
remain constant and X
3
increases by 1%, NPF (Y) will decrease by 2%. Conversely,
if X
3
decreases by 1%, NPF (Y) will increase by 2%.
Cross-section
Test Hypothesis Time
Both
Breusch-Pagan
54.06833
(0.0000)
2.594293
(0.1072)
56.66262
(0.0000)
Honda
7.353117
(0.0000)
-1.610681
(0.9464)
4.060515
(0.0000)
King-Wu
7.353117
(0.0000)
-1.610681
(0.9464)
2.738608
(0.0031)
Standarized Honda
7.924388
(0.0000)
-0.958856
(0.8312)
2.495227
(0.0063)
Standarized King-Wu
7.924388
(0.0000)
-0.958856
(0.8312)
1.236342
(0.1082)
Gourieroux, et al
-
-
54.06833
(0.0000)
Putri Novia Rahmawati, Gita Syafira Setiady, Mardi, Itah Miftahul Ulum
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3910
e. The beta coefficient value of the GDP variable (X
4
) is -0.037019. If other variables
remain constant and X
4
decreases by 1%, NPF (Y) will decrease by 4%. Conversely,
if X
4
increases by 1%, NPF (Y) will increase by 4%.
Normality Test
Figure 3
Normality Test Graph
Multicollinearity Test
Table 9
Multicollinearity Test Results
X
1
X
2
X
3
X
4
X
1
1.000000
0.000346
0.132462
0.025448
X
2
0.000346
1.000000
-0.065809
-0.184226
X
3
0.132462
-0.065809
1.000000
0.579489
X
4
0.025448
-0.184226
0.579489
1.000000
The correlation coefficient between X
1
and X
2
is 0.000346 < 0.85, X
1
and X
3
is
0.132462 < 0.85, X
2
and X
3
is 0.065809 < 0.85, X
2
and X
4
is -0.184226 < 0.85, and
finally, X
3
and X
4
is 0.579489 < 0.85. Thus, it can be concluded that the data is free from
multicollinearity.
Table 10
Hypothesis Testing Results
Variable
Co
i
effici
i
ent
Std.
e
rror
t-Statistic
Prob.
C
0.009507
0.008071
1.177928
0.2450
X
1
-0.016577
0.006195
-2.675772
0.0104
X
2
0.014109
0.006590
2.140911
0.0377
X
3
0.021398
0.136403
0.156875
0.8760
X
4
-0.037019
0.045873
-0.806989
0.4239
a. The t-test results for the CAR variable (X
1
) show a t-count value of 2.675772 > t-table
value of 2.010635, and the significance value is 0.0104 < 0.05, indicating that H0 is
rejected and H1 is accepted, meaning that CAR has a significant negative effect on the
NPF of Islamic Commercial Banks in Indonesia.
0
2
4
6
8
10
-0.01 0.00 0.01 0.02 0.03
Series: Standardized Residuals
Sample 2018 2022
Observations 50
Mean 2.10e-18
Median -0.003086
Maximum 0.028946
Minimum -0.017219
Std. Dev. 0.013812
Skewness 0.592835
Kurtosis 2.007304
Jarque-Bera 4.981789
Probability 0.082836
The Influence of Internal and External Factors on Non-Performing Financing at Islamic
Commercial Banks in 2018-2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3911
b. The t-test results for the FDR variable (X
2
) show a t-count value of 2.140911 > t-table
value of 2.010635, and the significance value is 0.0377 < 0.05, indicating that H0 is
rejected and H2 is accepted, meaning that FDR has a significant positive effect on the
NPF of Islamic Commercial Banks in Indonesia.
c. The t-test results for the Inflation variable (X
3
) show a t-count value of 0.156875 < t-
table value of 2.010635, and the significance value is 0.8760 > 0.05, indicating that
H0 is accepted and H3 is rejected, meaning that inflation does not significantly affect
the NPF of Islamic Commercial Banks in Indonesia.
d. The t-test results for the GDP variable (X
4
) show a t-count value of 0.0806989 < t-
table value of 2.010635, and the significance value is 0.4239 > 0.05, meaning it does
not significantly affect the NPF of Islamic Commercial Banks in Indonesia.
Coefficient of Determination (R
2
) Test
Table 11
R
2
Test Results
With a coefficient of determination value of 0.187309, or 18.73%, the independent
variables consisting of CAR, FDR, inflation, and GDP can explain 18.73% of the NPF
variable in Islamic commercial banks. Other variables not included in this research model
account for 81.27% (100-adjusted R-squared).
Effect of Capital Adequacy Ratio (CAR) on Non-Performing Financing (NPF)
The Capital Adequacy Ratio (CAR) variable has a significant negative effect on
Non-Performing Financing (NPF), with a significance value of 0.0104 < 0.05. The NPF
will decrease with a higher CAR. CAR is a bank's solvency ratio that shows how
effectively a bank achieves its goals. The higher the CAR, the more credit can be provided
to the public and to finance productive assets, reducing the impact of bad credit or NPF
on the health of Islamic Commercial Banks in Indonesia.
Effect of Financing to Deposit Ratio (FDR) on Non-Performing Financing (NPF)
Based on the research results, the FDR variable has a significant positive effect on
NPF, with a significance value of 0.0377 < 0.05. This aligns with (Wijaya, 2023), who
found that FDR positively affects NPF. A higher FDR leads to an increase in NPF for
Islamic Commercial Banks. The higher the FDR, the better a bank’s liquidity, while a
lower FDR indicates inefficiency in distributing financing. The Financing Deposit Ratio
(FDR) is a benefit for banking, but business involves risks and profits. If the FDR is
managed carefully, it can be profitable. The level of FDR in Islamic banking is highly
influenced by high levels of Non-Performing Financing (NPF). Without proper oversight,
financing can become more difficult or slower.
Effect of Inflation on Non-Performing Financing (NPF)
R
-
squared
Adjusted R
-
squared
S.E. of
regression
F statistic
Prob(F
-
statistic)
0.253651
0.187309
0.007040
3.823371
0.009284
Putri Novia Rahmawati, Gita Syafira Setiady, Mardi, Itah Miftahul Ulum
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3912
The results show that inflation does not significantly affect NPF, with a significance
value of 0.8760 > 0.05. Inflation reflects rising costs of goods and services. In this study,
inflation does not affect NPF significantly, as Islamic banks generally have a profit-
sharing system that can be adjusted according to customer needs. Islamic banks also use
fixed installment credit that does not follow inflation, helping customers plan their
finances and avoid payment defaults, thus not burdening customers with rising inflation.
Effect of Gross Domestic Product (GDP) on Non-Performing Financing (NPF)
The GDP variable, based on the partial test results, shows no significant effect on
NPF, with a significance value of 0.4239 > 0.05. This aligns with previous studies by
(Safitri & Suselo, 2023) and (Purwaningtyas et al., 2020), which found that GDP does
not influence NPF. GDP reflects the increase and decrease in public income, which
impacts the economy. According to the research, GDP does not affect NPF. Household
consumption has increased as a result of Indonesia's economic growth, including major
components of spending on education and health. Therefore, when linked to NPF, GDP
has no effect because most household spending in Indonesia is allocated to education and
health. Based on this analysis, GDP growth does not affect the size of NPF as the growth
is uneven across sectors, meaning that GDP does not impact NPF.
Conclusion
Based on the analysis and discussion, the Capital Adequacy Ratio (CAR) hurts
Non-Performing Financing (NPF). This indicates that the higher the CAR of a bank, the
more credit can be provided to the public. The bank can finance its assets with a higher
CAR without the risk of bad credit affecting the health of Islamic banks. The Financing
to Deposit Ratio (FDR) has a positive effect on Non-Performing Financing (NPF). This
shows that a higher FDR indicates better liquidity, while a lower FDR indicates
inefficiency in financing distribution. Inflation does not affect NPF. This is explained by
the fact that Islamic banks have a profit-sharing system and fixed installments, so
customers are not burdened with rising inflation. Gross Domestic Product (GDP) does
not affect NPF, as household consumption is mostly allocated to education and health,
and thus GDP fluctuations have no significant impact on NPF.
The Influence of Internal and External Factors on Non-Performing Financing at Islamic
Commercial Banks in 2018-2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 3913
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