DETERMINANTS OF
BANK PERFORMANCE THROUGH CAMEL RATIO, DIGITALIZATION, AND BANK SIZE
Indah
Kayani, Hakiman
Faculty of Economic and Business,
Magister Management, Universitas Mercu Buana, Indonesia
Email: [email protected], [email protected]
|
KEYWORDS BOPO; CAR; NPL; Digitalization; Bank Size |
ABSTRACT In general, this research aims to analyze the
effect of CAMEL’s factors, namely BOPO, CAR, NPL, and LDR on the bank's
financial performance. As well as the external factors of Digitalization and
Bank Size on the bank's financial performance. In this case, the bank's
financial performance is proxied by ROA. The population in this study are
conventional banks registered with the Financial Services Authority totaling
107 banks. The sampling technique used purposive sampling with a total sample
of 10 banks that met the criteria. The approach used is panel data regression
with a random effect model as the best model. Data analysis software uses
E-Views 12. The results of this study found that BOPO and CAR have a negative
effect on financial performance. LDR, Digitization, and Bank Size each have a
positive effect on financial performance. But, NPL does not affect bank
performance. From these results, banks are expected to be able to improve
financial performance and bank management performance so that creditors have
a good perception of bank performance in the future. And must be able to
maintain the soundness of the bank by considering all possible risks that
will arise. In research, bank digitization has shown quite good results.
However, banks must continue to innovate on digital banking while continuing
to be accompanied by an increase in the number of customers and pay attention
to the infrastructure costs of digitalization. |
INTRODUCTION
The
Financial Services Authority (OJK) regulates the assessment of the soundness
level of commercial banks through OJK Regulation No. 4/POJK.3/2016 concerning
the rating of the soundness level of Commercial Banks According to this
regulation, the soundness level of a bank is measured through an assessment of
the condition of the bank which includes two main aspects namely bank risk and
bank performance. These two aspects are interrelated because the risk to the
bank can affect the overall financial performance of the bank. By measuring the
financial performance of banks through these two aspects, OJK aims to assess
the soundness and financial stability of banks and to supervise that banks
continue to operate within safe and sustainable limits.
Historically,
ROA has fluctuated which is reflected in the chart below. In the period from
2016 to 2020, banks are still classified under the BUKU group. In 2020, there
was a sharp decline in ROA, especially for BUKU 4 banks. This situation was
likely caused by the impact of the Covid-19 pandemic which put heavy pressure
on the country's economy and created uncertainty in the market. global finance.
Despite the decline, banks generally remained in good health. By Bank Indonesia
Regulations stipulate that a healthy ROA should not be below 0.5%.
Figure 1.1.
Bank Financial Performance 2016-2021
Source: OJK Data and
Statistics Banking Channel (Processed Data)
Based on the
explanation above, the purpose of this research is to analyze the influence of CAMEL’s
factors, namely BOPO, CAR, NPL, and LDR on the bank's financial performance (Anton et al., 2021). As well as
the external factors of Digitalization and Bank Size on the bank's financial
performance. In this case, the bank's financial performance is proxied by ROA.
Previous
Research and Hypothesis
Agency Theory
Agency
theory was first coined by Jensen and Meckling (1976), in this theory there is
information asymmetry, namely the conflict of interest between principals and
agents due to different goals. Syakhrun et al., (2019) explained
that the wish of the principal to know information about the funds invested in
the company is by holding the agent accountable, in this case, the financial
statements. This agency theory underlies financial performance. Where investors
or customers want to assess the bank's financial performance to understand the
company's prospects in the future.
Return on Asset
(ROA)
Bank
Indonesia Regulation No 6/10/PBI/2004 explains that a ROA below 0.5% indicates
an unhealthy bank. ROA talks about how a company uses its assets. ROA is very
important for both internal and external stakeholders in decision-making.
Because ROA is related to production performance or distribution performance.
ROA itself is the ratio of profit before tax to total assets
Operating
Expenses and Operating Income (BOPO)
Bank
Indonesia Circular No. 6/23/DPNP/2004 states that the efficiency level is quite
healthy with BOPO ratios ranging from 94% to 96%. A higher BOPO ratio indicates
a lower level of bank efficiency. The BOPO ratio is used by banks as a means of
controlling and evaluating operational activities. BOPO aims to describe how a
company manages its operational expenditures to achieve maximum profit. When
operational costs increase, profits will decrease so performance also
decreases. This is to the findings by (Maudhita & Thamrin, 2018) and (Yusuf & Ichsan, 2021) which state
that BOPO has a negative effect on ROA.
H1:
BOPO has a negative effect on the bank’s financial performance
Capital Adequacy
Ratio (CAR)
OJK Circular
No. 14/SEOJK.03/2017 states that the calculation of capital and RWA is guided
by the provisions of the Financial Services Authority regarding the minimum
capital requirement for commercial banks. Harjadi, (2013:221), explains that
based on Bank Indonesia regulations, a healthy bank is a bank that has a
minimum CAR value of 8%. IBI (2014: 28), states that the higher the CAR ratio,
the bank's ability to support business growth will increase, including covering
unexpected losses. the higher the CAR, the greater the bank's ability to
improve performance, and vice versa. This reasoning is in line with previous
research conducted by (Juwita et al., 2018), and (Rahman et al., 2022) which
argued that CAR has a positive effect on financial performance.
H2:
CAR has a positive effect on the bank's financial performance
Non-Perdorming
Loan (NPL)
NPL can be an indicator when a bank is in trouble
which if there is no solution will be detrimental to the bank. IBI (2014:29),
the net NPL which is the reference for Bank Indonesia is a maximum of 5%. If it
is above 5%, the bank is considered to have a high credit risk. A high NPL
indicates that most loans have the potential to experience bad credit risk,
which can have a negative impact on bank finances and overall financial system
stability. The higher the debtor's credit rating, the higher the credit risk
that the bank will face. Debtors with high-risk credit have the potential to
cause problems in payments, which have an impact on increasing bank NPLs. For
banks, managing credit risk is very important to ensure the continuity of
operational activities and stability.
H3:
NPL has a negative effect on the bank's financial performance
Loan to Deposit
Ratio (LDR)
Based on Bank Indonesia regulation Number
12/19/PBI/2010, LDR is a ratio that measures the proportion of credit extended
by banks to third parties in the form of Rupiah and foreign currencies. LDR is
used as an indicator of bank liquidity, which describes the amount of credit
provided by banks compared to funds obtained from third parties. If the LDR is
high, it means that the bank relies on more funds from third parties to finance
loans. In assessing the soundness of banks using the CAMELS method, Bank
Indonesia indicates a healthy LDR ratio in the range of 78% to 85%. If the LDR
exceeds this range, then the bank is considered to have a high liquidity risk
due to its heavy dependence on third-party funds to finance credit. Banks need
to monitor and manage LDR so that it remains within a healthy range and can
maintain good liquidity.
H4: LDR has a positive effect on the bank's financial performance
Digitalization
Financial Services Authority Regulation No.
12/POJK.03/2021 concerning commercial banks aims to strengthen institutional
rules, one of which is on operational aspects including digital services. This
is OJK's effort to provide a clear framework for banks in carrying out digital
transformation to increase efficiency, innovation, and service to customers. In
addition, PJOK No. 13/POJK.03/2021 has the goal of accelerating digital
transformation and innovation of bank digital products and services. This
regulation provides guidelines for commercial banks to adopt digital technology
and increase innovation in products and services to increase competitiveness
and meet the demands of customers who are increasingly digitally savvy. Digital
banking can reduce operational costs on average and the adoption of fintech
must be matched by an increase in the number of customers. (Risman et al., 2021) explains that fintech refers to technological
innovation in the financial industry. Digital finance in payment and transfer
services can reduce the risks associated with cash transactions. Thus,
digitalization can improve banking performance if implemented properly and
accompanied by the right strategy to achieve success in digital transformation.
H5: Digitalization has a positive effect on bank financial
performance
Bank Size
As explained by (Bousrih, 2023), there are several factors used to measure company
size, including total assets, total sales, tax expense, profits, and others.
Banks with a large number of assets are usually considered stronger and more
reliable because they can carry out operational activities freely. Larger
assets can increase credibility in the eyes of related parties, provide the
ability to make larger investments and expansions, and provide flexibility in
obtaining additional funding. (Hidayat, 2014) explains that the level of efficiency is influenced
by size because economically it can determine the extent to which a bank with
production technology and similar quality management can work to an optimum
scale.
H6: Bank Size has a positive effect on the bank's
financial performance
RESEARCH
METHOD
The method
used is quantitative with secondary data sources. This type of research is
comparative with panel data. The independent variables of this study are the
ratio of BOPO, CAR, NPL, LDR, bank digitization, and bank size. The dependent
variable of banking financial performance is proxied by ROA. In this study, the
population used was all conventional banks registered with the Financial
Services Authority during the study period, namely 107 banks. As well as the
sampling technique using purposive sampling. The sample in this study was 10
conventional banks, consisting of 6 KBMI III banks and 4 KBMI IV banks. The
data analysis tool used is e-views 12.
RESULTS AND
DISCUSSION
Analisis Statistik Deskriptif
The following is the
output of descriptive test data statistics with Eviews 12.
Table 1. Descriptive
Statistics Test Output
Source: Eviews
Processing Output 12, 2023
The results of the data processing above show that the
research data totaled 60 observations, namely from a total of 10 (ten) banks in
KBMI III and IV during the research period (2016 to 2021). Table 1 below shows
the overall mean is positive.
The dependent variable (ROA) has a maximum value of 4%
owned by PT. Bank Central Asia (Persero), Tbk. in 2016, 2018, and 2019.
Meanwhile, the minimum value of -4.9% occurred at KBMI III, namely PT. Bank
Permata Tbk. (BNLI) in 2016. This shows that the company is unable to generate
profits or it could also be due to poor bank management in terms of costs. It
was explained in its annual report, BNLI's performance in 2016 suffered a loss
due to the creation of a high allowance for impairment losses on financial
assets. On average, KBMI III and IV banking during the study period were able
to optimize asset value, where every 1rupiah asset could generate a profit of
1.9647%.
The maximum BOPO value of 151% is owned by PT. Bank
Permata Tbk. (BNLI) in 2016. This occurred in line with an increase in the
burden of provision for impairment of credit which was explained in its 2016
annual report. Meanwhile, the minimum BOPO value in this study was 54.20% at
the KBMI IV bank, namely PT. Bank Central Asia (Persero) Tbk. (BBCA) in 2021.
Banks that have a maximum value of 35.70% and a
minimum of 15.60% in Capital Adequacy Ratio (CAR) are PT. Bank Permata, Tbk.
(BNLI) occurred in 2020 and 2016 respectively. It was explained in the 2021
annual report, that BNLI's strong capital was the basis for providing complete
services for customers to accelerate business growth. In 2016, the condition of
BNLI was still sufficient because statistically, it had exceeded the minimum
standard set by Bank Indonesia, which was 8%.
The maximum value of the NPL ratio of 2.960% is owned
by PT. State Savings Bank (Persero), Tbk. (BBTN) in 2019. As described in the
2019 annual report, BBTN has changed its business plan in the context of
implementing PSAK 71 which was effective from 1 January 2020 as well as
challenges to banking liquidity which increased NPLs. The minimum NPL value is
0.3%, which belongs to PT. Bank Central Asia (Persero), Tbk. 2016. The mean is
1.2418% which is lower than Bank Indonesia regulations and PJOK No. 15
/POJK.03/2017, which is 5%. So it can be said that the bank has good credit
quality so that the risk of non-performing loans can be reduced.
The LDR variable has a maximum value of 113.50% at PT.
State Savings Bank (Persero), Tbk. 2019. This was due to challenges from tight
banking liquidity conditions. While the minimum LDR value in this study was 62%
at PT. Bank Central Asia (Persero), Tbk. (BBCA) in 2021. The conditions in 2021
cannot be separated from the growth in the collection of demand deposits and
savings funds (CASA) which is greater than the credit growth that occurred
during the Covid-19 pandemic.
The maximum digitization value of 443,000,000,000
transactions is owned by Bank Pan Indonesia, Tbk. (PNBN) in 2021. As an effort
to carry out digital transformation, PNBN invests in sophisticated Information
Technology architecture and infrastructure and prepares digital talent. To
strengthen digital transformation, PNBN launched an omnichannel mobile
application. Meanwhile, the minimum value of 12,807,485 transactions belongs to
PT. Bank Danamon Indonesia, Tbk. (BDMN) in 2016. An integral part of BDMN is
technology and digital development. Comprehensively developed digital services
include SMS banking, Internet banking, and mobile banking.
The maximum size value is Rp. 1,725,611,128,000,000, -
owned by PT. Bank Mandiri (Persero), Tbk. (BMRI) in 2021. While the minimum
value is Rp. 709,330,000,000, - owned by PT. Bank Negara Indonesia (Persero),
Tbk. 2017. Bank size can be used to provide an overview of a bank's ability to
face competition. The increasing value of assets shows the investment made
increases.
Panel Data
Regression Model
The election results show that the REM model is
selected as the best model, along with the panel data regression equation with
the Random Effect Model.
Table 2. Basic Panel Data Regression Equations
Source: Eviews Processing Output 12, 2023
From the results of the selection of the panel data
regression model above, which shows that the REM model was chosen as the best
model, here is the panel data regression equation with the Random Effect Model.
|
Financial Performance (ROA) |
= |
0.064899 - 0.084674 BOPO - 0.039181 CAR - 0.001147 NPL + 0.030647 LDR + 0.000807 Digitalization + 0.025086 Size |
The panel data regression equation above
simultaneously has a probability value of 0.000000 less than 5% with F count
70.65207 greater than F table 2.19. This output shows that simultaneously the
independent variables namely BOPO, CAR, NPL, LDR, Digitalization, and Bank Size
influence the bank's financial performance which in this study is proxied by
ROA. In the regression equation, if BOPO increases by 1%, the bank's financial
performance will decrease by -0.084674. This result proves that BOPO has a
negative effect on performance. The regression coefficient value on the CAR
variable is -0.039181. This means that when CAR increases by 1%, the bank's
financial performance decreases by 0.039181. These results prove that CAR has a
negative effect on performance. At RWA, the value of these assets that have the
greatest risk is credit. Increased risk from bank operational activities,
especially related to credit, can reduce bank profitability. The regression
coefficient value on the NPL variable is -0.001147. This means that when there
is an increase of 1% of NPL, the bank's financial performance decreases by
0.001147. A high NPL indicates that most loans have the potential to experience
bad credit risk, which can have a negative impact on bank finances and overall
financial system stability.
The regression coefficient value on the LDR variable
is 0.030647. This means that if the LDR increases by 1%, the bank's financial
performance will increase by 0.030647. illustrates the amount of credit
provided by banks compared to funds obtained from third parties. When a bank
provides a loan, the bank will earn interest on the loan which can then
increase bank profitability. The regression coefficient value on the
digitization variable is 0.000807. This means that if there is a 1% increase in
digitization, the bank's financial performance will increase by 0.000807.
Digital banking can reduce operational costs on average and the adoption of
fintech must be matched by an increase in the number of customers. The
regression coefficient value on the size variable is 0.025086. This means that
when the size increases by 1%, the bank's financial performance increases by
0.025086. The asset value obtained by the bank comes from efficient credit
distribution with timely credit repayments so that it can influence the
positive direction for profitability.
Based on the explanation above, BOPO is the most
dominant variable affecting a bank's financial performance. BOPO is a ratio
that describes operating expenses to a bank's operating income. When expenses
increase, the bank's income will decrease and this can affect a decrease in
ROA. ROA itself is a comparison ratio of net income to total assets.
Hypothesis Testing
This
hypothesis test was carried out by the Wald Test to analyze the effect of each
independent variable on the dependent variable. The first independent variable
is BOPO. BOPO is a ratio that describes the comparison between the operational
costs and the operating income of a bank. Bank Indonesia Circular No. 6/23/DPNP/2004
stipulates the range of BOPO that is considered quite healthy ranging from 94%
to 96%, which indicates the level of efficiency expected in bank operations.
The value research output shows that the probability of BOPO is below 5%, which
is 0.0000 and the t value is -14.96293. So, the hypothesis that BOPO has a
negative effect on the bank's financial performance is acceptable. In its
relationship with the Agency Theory introduced by Jensen and Meckling (1976),
when customers know in financial reports that operational costs are high, it is
considered that bank management may be inefficient in managing costs and
resources, which can reduce investor and other stakeholder confidence in the
bank. the. The results of the research are in line with research from (Sudarmawanti & Pramono, 2017), Juwita et
al (2018) Maudhita and Thamrin (2018), (Suwarno & Muthohar, 2018), (Santoso et al., 2020), Saputra
and Lina (2020), (Yuhasril, 2019), (Arif & Masdupi, 2020), (Cahyana & Suhendah, 2020), stated
that BOPO had a negative effect on banking performance. BOPO has a negative
effect on a bank's financial performance because when operational costs increase,
the profit before tax generated by banks tends to decrease. This decrease in
profit has an impact on the decline in bank profitability and ultimately
affects the overall financial performance.
OJK Circular
No. 14/SEOJK.03/2017 states that the calculation of capital and RWA is guided
by the provisions of the Financial Services Authority regarding the minimum
capital requirement for commercial banks. Harjadi, (2013: 221), the minimum CAR
standard set by Bank Indonesia and the Bank for International Settlements is
8%. The Capital Adequacy Ratio has a probability value of 0.0379 which is less
than 0.05 with a t-value of -2.128653. The results showed that CAR had a
negative effect on the bank's financial performance. So it can be said the
hypothesis is rejected. The results of the research are in line with previous
studies conducted by (Kinanti & Purwohandoko, 2017), Santoso et
al (2020), and Al-fadzar et al., (2021) which prove
CAR has a negative effect on ROA. The bank's basic capital is used to maintain
investment in fixed assets and liquidity. In the CAR ratio, capital is divided
by RWA. Where the value of these assets that have the greatest risk is credit.
Increased risks from bank operational activities, especially those related to
credit, can reduce bank profitability and ultimately affect overall financial
performance. It is important for banks to carefully consider risk management in
managing credit and ensure adequate capital levels to support operational
activities and sustainable growth. An adequate CAR value is important to ensure
banking stability and soundness, but a high level of capital must also be
balanced with good risk management to achieve optimal financial performance.
NPL is an
indicator of whether a bank is in trouble. Copy of OJK Circular No.
14/SEOJK.03/2017 explains credit risk. According to IBI (2014: 29), the net NPL
which is the reference for BI is a maximum of 5%. The output of data processing
gives the result that the NPL probability value is 0.4834 greater than 0.05
with a negative t value (-0.705851). Hereby state that there is no significant
effect of NPL on the bank's financial performance. That is, the research
results reject the hypothesis. In agency theory, when customers see a high NPL
indicating that most loans have the potential to experience bad credit risk,
this can have a negative impact on bank finances and overall financial system
stability. The results of this study are in line with research conducted by (Soekapdjo, 2020), (Parvin et al., 2019), and
Fietroh and Fitriyani (2022). In this study, fluctuations in the level of
non-performing loans (NPL) do not significantly affect the rate of return on
bank assets (ROA), because they are carried out in banks that have large
capital so that they can cover all risks.
The last
CAMEL factor in this study is the Loan to Deposit Ratio. Based on Bank
Indonesia regulation Number 12/19/PBI/2010, LDR is a ratio that measures the
proportion of credit extended by banks to third parties in the form of Rupiah
and foreign currency. The research output shows that LDR has a probability
value of 0.0002, which is smaller than 0.05 with a t-value of 3.953920. So, the
LDR hypothesis that has a positive effect on the bank's financial performance
is acceptable. In assessing the soundness of banks using the CAMELS method,
Bank Indonesia indicates a healthy LDR ratio in the range of 78% to 85%.
relationship with agency theory that is, customers can see good prospects for
the bank's future performance because the bank has been able to channel its credit
effectively. The results of this study are in line with research conducted by
Sudarmawanti and Pramono (2017), Juwita, et al (2018), Soekapdjo (2020), and Al-fadzar et al., (2021) which prove
LDR has a positive effect on financial performance. As banks make more loans,
the interest income generated from these loans also increases. Banks get
interest from loans given to customers. LDR will increase and bank profits will
also increase. However, the lower the LDR the bank can lose the opportunity to
make a profit.
In the
current era of industrial reform 5.0, digitization plays an important role,
especially in banking. Bank digitization makes it easier for customers in
various transactions. (Risman et al., 2021) explains
that fintech refers to technological innovation in the financial industry. The
research output shows that digitization has a probability value of 0.0463 which
is less than 0.05 with a t value of 2.040416. These results prove that the
digitalization hypothesis affecting bank financial performance is acceptable.
Operational-related uses including bank digital services are regulated in
Financial Services Authority Regulation No. 12/POJK.03/2021. As well as the
Financial Services Authority Regulation No. 13/POJK.03/2021 encourages the
acceleration of digital transformation and innovation of bank digital products
and services. The results of this study are in line with research conducted by
Ginting et al (2022) and (Bousrih, 2023) which
proves that the presence of banking digitalization has a positive impact on
bank performance. Digitalization is a significant trend in the banking world
because it provides various benefits for banks and customers. Digitalization
can assist banks in expanding market access and improving service quality to
customers. The use of digital technology in banking services makes it easier
for customers to make transactions, manage accounts, and access other banking
services quickly and easily. This increases customer satisfaction and can
encourage the growth of the bank's business. Findings in research prove that
digitization has a positive effect on bank financial performance. The
successful implementation of digitalization can provide benefits for banks in
the form of increased revenue from digital services and operational efficiency.
With increased income and efficiency, bank profitability can increase.
Bank Size
can be an important indicator in analysis related to a bank's financial
performance. As explained by Brigham and Houston (2010: 4), one of the factors
that can measure bank size is total assets. The research output shows that Bank
Size has a probability value of 0.0136, which is smaller than 0.05. With a t
value of 2.554301. The findings of this study prove that accepting the
hypothesis that Bank Size has a positive influence on a bank's financial
performance. The relationship with agency theory is that the size value
indicates that the bank is in good health and customers believe that the bank
has sufficient assets to improve performance in its operational activities. The
findings are in line with research conducted by (Parvin et al., 2019) and (Nguyen & Nguyen, 2020). Size can
be an indicator in measuring the size of the asset. The value of this asset is
an indicator of future development. The asset value obtained by the bank comes
from efficient credit distribution with timely credit repayments so that it can
influence the positive direction for profitability.
Table 3.
Hypothesis Test Output
Source: Eviews Processing Output 12, 2023
Determination
Coefficient Test
Testing the
coefficient of determination is carried out to find out how much the
independent variable can explain the dependent variable. Based on the figures
presented in the table below, it can be concluded that 88.8868% of the
variation in the dependent variable, namely the bank's financial performance,
can be explained by a combination of the independent variables (BOPO, CAR, NPL,
LDR, Digital, and Bank Size). The regression model has a fairly good fit to
explain the variation in ROA. However, the remaining 11.1132% could be
explained by other independent variables not included in the model, as well as
other factors that may not have been considered in the analysis, possibly
contributing to the remaining variation in the bank's financial performance.
Table 4.
Determination Coefficient Test Output
Source: Eviews Processing Output 12, 2023
CONCLUSION
Based on the
explanation above, the following is a summary of research findings, namely: (1)
BOPO is proven to have a negative effect on bank financial performance. If bank
operating costs increase, profit before tax can decrease, which will have an
impact on reducing bank profitability, (2) CAR is proven to have a negative
effect on bank financial performance. An increase in bank capital that is not
balanced with risks from bank operations can affect the efficiency and ability
of the bank to overcome losses, (3) NPL is not proven to affect the bank's
financial performance. A low NPL value indicates that the bank is capable of
managing non-performing loans and can reflect a healthy bank performance, (4)
LDR has a positive effect on the bank's financial performance. When banks can
distribute credit effectively, LDR increases, and income from loan interest can
increase bank profits, so banks are considered to be in good condition, (5)
Digitalization applied by banks has a positive effect on their financial performance.
Effective use of bank services can increase bank revenue from digitalization
services, (6) There is a positive effect of Bank Size on bank financial
performance. A large bank size indicates that the bank's performance is good
and it has sufficient assets to increase operational efficiency and bank
profitability.
Based on the
findings in this study, some suggestions can be given to banks, namely that
banks are expected to improve bank performance and management to create a good
perception of creditors about future bank performance. Banks must also maintain
soundness by taking into account possible risks that may arise. This research
shows that banks have made quite good innovations in digitalization. However,
banks are also expected to be able to continue to innovate on digital banking
while still being accompanied by an increase in the number of customers and
paying attention to the infrastructure costs of digitalization. For future
researchers, it is recommended to use transaction volume to proxy bank
digitalization and measure bank financial performance in different periods, as
well as consider macroeconomic variables that might affect bank financial
performance. More research conducted with various methodologies can provide a
deeper understanding of the factors that may affect a bank's financial
performance.
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Copyright holders:
Indah Kayani, Hakiman (2023)
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