Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022

International Journal of Social Science and Human Research ISSN (print): 2644-0679, ISSN (online): 2644-0695 Volume 08 Issue 11 November 2025 DOI: 10.47191/ijsshr/v8-i11-28, Impact factor8.007 Page No: 8747-8758 IJSSHR, Volume 08 Issue 11 November 2025 www.ijsshr.in Page 8747 Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022 Sumarni Pascasarjana UIN Saifudin Zuhri Purwokerto ABSTRACT: This study aims to determine the macroeconomic impact such as inflation, BI rate, exchange rate, and Money Supply (JUB) on the share of financing, namely profit-sharing investment of Islamic banks in Indonesia which includes all Sharia Commercial Banks (BUS) and Sharia Business Units (UUS) in Indonesia. The analysis used is multiple linear regression with the Ordinary Last Square (OLS) method to identify the impact of the independent variable on the dependent variable. During the monthly period 2020-2022, secondary data was collected from the Sharia Banking Statistics (SPS) of OJK, Central Statistics Agency (BPS), and Bank Indonesia (BI). Partial data shows that only the Money Supply (JUB) has an influence on the share of Islamic bank financing in Indonesia, while three other factors, such as inflation, BI rate, and interest rates, have no effect. However, simultaneously, macroeconomic conditions have a significant impact of 27.4% on the share of Islamic bank financing in Indonesia. KEYWORDS: Inflation, BI rate, exchange rate, money supply, Islamic Bank Financing. I. INTRODUCTION The report on the development of Islamic finance in Indonesia released by the Financial Services Authority (OJK) in 2022 stated that the Global Economy grew by 3.4% amid a sustainable economic recovery. Economic activity began to gradually improve after previously being affected by the pandemic. However, the impact of global production has not fully recovered, pushing up an imbalance between supply and demand, thus driving inflation. Global economic challenges in 2022 have been exacerbated by Russia's military offensive into Ukraine. The global Islamic finance profile says that global Islamic financial assets have reached US$ 3.96 trillion in 2021. This figure increased from the previous year, which was US$ 3.39 trillion. This indicates that the global Islamic finance industry is growing well in the midst of economic growth. This growth is also supported by the development of the Islamic finance industry in Indonesia. The Sharia economy in Indonesia began in 1992 which was marked by the establishment of Bank Muamalat. The growth of financial institutions, especially Islamic commercial banks in Indonesia, has increased significantly in recent decades. Based on a report by the Financial Services Authority (OJK) in September 2023, the growth of Sharia financial assets in December 2022 for Sharia Commercial Banks amounted to 531,860 trillion, while asset growth in June 2023 increased by 543,072 trillion. The growth of Sharia Commercial Bank (BUS) offices in 2023 is 13 units, and 20 units of Sharia Business Unit (UUS) and Sharia People's Financing Bank (BPRS) offices are 171 units. Table 1. Development of Islamic Finance in Indonesia in 2022 Source: Indonesia's Sharia Finance Development Report 2022 Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022 IJSSHR, Volume 08 Issue 11 November 2025 www.ijsshr.in Page 8748 The rise and fall of financing in Sharia banks is influenced by internal factors originating from the bank itself as well as external factors originating from macroeconomic conditions (Mumtazah, 2016). The macroeconomic factors in question include inflation, interest rates (BI rate), the rupiah exchange rate against the US dollar, the amount of money in circulation in the community, and so on. According to (Mumtazah, 2016) High inflation leads to a continuous increase in the price of goods and services in general (not just one kind of goods and momentary) (Iswardono, hlm 214). The impact of inflation on Islamic banks is the high risk of default. This risk will increase the Non-Performing Financing (NPF) of Islamic banking. If the financing is based on profit sharing, if the debtor suffers business losses, this loss is also borne by Islamic banks or risk sharing. If the type of financing is a sale and purchase agreement, then high inflation can make sharia financing products in general relatively more expensive (Saekhu, 2015). The second macroeconomic factor is interest rates (BI Rate). According to Karim (2015: 59), The higher the interest, the less credit amount from conventional banks to invest. In Sharia Commercial Banks, when the BI-Rate is high, Sharia Commercial Banks are not allowed to increase the percentage of profit sharing in financing, because it has been agreed at the beginning of the contract. The relationship between BI-rate and murabahah financing margin was presented by Veittzal dan Rivai (2008) that many factors affect interest rates include factors that affect the mark-up in murabahah. This shows that the BI-rate affects or is considered in determining the murabahah margin. The third macroeconomic factor is the rupiah (Rp) exchange rate against the dollar ($). The decline in the rupiah exchange rate (depreciation) and the increase in the rupiah exchange rate (appreciation) affect a country's exports. When the rupiah exchange rate against the dollar experiences a total depreciation, a country's exports will rise. Rising exporters' earnings will boost the country's gross domestic income (Samuelson & Nordhaus, 1997: 182). When export revenues increase, exporters try to finance in banks, thus affecting the distribution of Islamic bank financing (Lie & Malelak, 2015: 69). The fourth macroeconomic factor is the development of the money supply (JUB) (Halim, 2013). The size of the JUB will affect the real purchasing power of the community and also the availability of community needs (Setyawan & Baratakusumah, 2005: 11). The amount of money in circulation in the hands of the community must develop reasonably, in order to have a positive influence on the economy. However, if the JUB increases sharply, it will trigger inflation and have a negative effect on the economy (Untoro, 2007). The policy has been carried out by Bank Indonesia in an effort to improve the quality of banknotes in circulation in Indonesia by printing or updating new banknote models. This policy can affect the amount of money in circulation in the community and can trigger an increase in the inflation rate and the rupiah exchange rate will also depreciate. The following is a table of developments in Inflation, rupiah exchange rate, money supply, BI Rate and share of Islamic bank financing in Indonesia over the last 3 years, namely the 2020-2022 period. Table 2. Inflation Developments, Rupiah Exchange Rate, Money Supply, BI Rate and Share of Sharia Bank Financing in Indonesia in 2020-2022 Period Inflation Rupiah Exchange Rate Money Supply Bi Rate Share of Sharia Bank Financing 2020 1.68 % 14 165.68 6 905 939.30 3,75 % 39,03 % 2021 1.87 % 14 327.09 7 870 452.85 3,5 % 38,85 % 2022 5.51 % 14 340.67 8 528 022.00 5,5 % 38,72 % Source: 2023 data processed From table 2, it is explained that inflation, Rupiah Exchange Rate, Amount of Money Supply (JUB), the share of Islamic Bank financing in Indonesia fluctuated from year to year. Fluctuations can be seen in terms of inflation, which is always increasing. The Rupiah Exchange Rate and the Money Supply (JUB) always increase every year. The BI Rate decreased in 2021 but rose significantly in 2022 by 5.5% and the Financing Share of Islamic Banks actually decreased from year to year. The increase in the JUB will lower interest rates. Interest rate cuts will increase investment in the economy. This increase in investment will have an impact on the operational activities of Islamic banks. (Koniah, 2023). Based on the background description above, the researcher is interested in examining the Impact of Macroeconomic Conditions on the Financing Share of Sharia Commercial Banks in Indonesia. a. Research Objectives 1. To find out and explain whether there is a significant influence of the bi rate, inflation, rupiah exchange rate against the dollar, and the amount of money in circulation, on the share of Sharia Bank financing in Indonesia. 2. To find out and explain whether there is a joint and significant influence of the variables of the bi rate, inflation, rupiah exchange rate against the dollar, and the amount of money in circulation on the share of Sharia Bank financing in Indonesia. Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022 IJSSHR, Volume 08 Issue 11 November 2025 www.ijsshr.in Page 8749 b. Scope of Research The scope of this research is Sharia Banks registered with Bank Indonesia in the OJK annual report for 2020-2022. c. Theoretical Foundations 1) Financing share The weakness and strength of Islamic financial institutions is caused by macroeconomic indicators that affect the stability of the financial system (Herijanto, 2013: 148). Some of the factors that affect the demand and provision of financing are the level of bad loans, lack of capital, community funds, rupiah exchange rate, inflation and interest rates (Herijanto, 2013: 144). In addition, financing disbursement must be analyzed according to the right facts and information, in order to minimize the banking crisis that begins with credit disbursement with excessive risk (over leverage) and economic shock (major changes in the macroeconomy) (Herijanto, 2013: 158). Based on the explanation above, macroeconomic factors that affect Islamic banking financing in Indonesia are inflation, rupiah exchange rate, inflation rate and money supply. The size of the market share will change at any time, this change can be caused by consumer tastes or the transfer of consumer interest from one product to another (syachfuddin, 2017). 2) Inflation Inflation is briefly defined as a tendency to increase the price of goods and services in general and continuously (Suseno, 2009). There are three important things that must be emphasized from the definition of inflation, namely: a. There is a tendency for prices to increase b. The price increase continues c. The price level in question is the price level in general, or not only on one commodity. Inflation is one of the problems in the economy that is always faced by every country. 3) BI Rate According to Keynes, interest is an interet for the use of money. Interest is a reward for the owner of capital, due to the existence of capital in others, where the owner of capital loses the opportunity to use his capital if he wishes. (Alma dan Priansa, 2009:273). Islamic banks and conventional banks compete with each other in terms of fund distribution and fund collection. According to Adiwarman (2010), states that Islamic banks will face market risks including interest rate risk and profit sharing risk of other Islamic banks that are competitors, interest rate risk is a risk that arises as a result of interest rate fluctuations, even though Islamic banks do not set interest rates, both in terms of funding and financing. 4) Rupiah exchange rate against the US dollar The influence of exchange rates on macroeconomic conditions is related to the prevailing price level and affects customer behavior in saving and financing requests. Mankiw (2001: 125) stated that if the real exchange rate is high, goods from abroad are relatively cheaper and domestic goods are more expensive and vice versa. If the rupiah exchange rate weakens against the currency of another country, then the goods or services produced by that country become more expensive based on the currency of that other country. As a result, the demand for goods or services decreases and substitutions can occur that suppress demand. As demand decreases, producers will lower supply and reach a new equilibrium. Supply reductions are carried out by reducing production so that the economy experiences a slowdown. As a result, the need for funds for working capital and investment has decreased, making it difficult for banks to distribute financing and vice versa (Cahyono, 2009; 31-32). 5) Money Supply (JUB) Money Supply (M2) is the overall value of money in the hands of the community. The amount of money in circulation in a narrow sense (narrow money) is the amount of money in circulation consisting of currency and demand money. Dimana: M1: the amount of money in circulation in a narrow sense C : Currency D : Bills or checks Money supply in a broad sense (M2) is plus time deposits. Information: M2: Money Supply in a broad sense TD: Time deposits M1=C + D M2= M1 + TD Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022 IJSSHR, Volume 08 Issue 11 November 2025 www.ijsshr.in Page 8750 Technically, what is calculated as the amount of money in circulation is money that is actually in the hands of the community. Money in the hands of banks, as well as banknotes and metals owned by the government are not counted as money in circulation (Tohari: 2010). d. Previous Research No Name Headings and variables Result 1 Binti Koniah, Dhiyah Shabnatul Lisan, Fatiyatul Mubawaroh, Agus Eko Sujianto (2023) Pengaruh Jumlah Uang Beredar Terhadap Profitabilitas Bank Syariah Di Indonesia Tahun 2011-2021 Variabel: X : JUB Y : ROA Results of linear regression test simply based on the value of the regression coefficient with a negative value, it can be interpreted that JUB (X) has a negative effect on ROA (Y). (Koniah, 2023) 3 Yanti, Husnul Khotimah (2022) Pengaruh Inflasi terhadap Pembiayaan Perbankan Syariah di Indonesia Periode 2016-2020 Variabel: X : Inflasi Y : Kinerja Bank Syariah Hasil dari penelitian ini shows that inflation has an influence positive or negative to Financing to Depocit Ratio (FDR) and NonPerforming Financing (NPF). (Khotimah, 2022) e. Hypothesis Based on the existing theoretical foundation and theoretical framework, the hypothesis of this study is: H0 : Inflation, BI Rate, rupiah exchange rate against the dollar, and the amount of money in circulation do not have a significant and simultaneous effect on the share of Islamic Bank Financing in Indonesia. H1 : Inflation, BI Rate, rupiah exchange rate against the dollar, and the amount of money in circulation have a significant and simultaneous effect on the share of Islamic Bank Financing in Indonesia. f. Framework of Thought a. Types and Approaches of Research This research is quantitative descriptive, namely explaining the relationship between variables by analyzing numerical data (numbers) using statistical methods through hypothesis testing. This research is a case study study on Sharia Banks in 2020-2022 b. Data Collection Methods 1) Data Source The data used in this study is secondary time series data in the form of quantitative data for 2020-2022 obtained from Bank Indonesia's financial statements (www.bi.co.id), Financial Services Authority (www.ojk.co.id), Central Statistics Agency (www.bps.co.id) economic indicators published by the Central Statistics Agency, Bulletins, OJK Reports or research journals and other related sources. 2) Population and Sample The population in this study is statistical data on Islamic banking financing published by the Financial Services Authority (OJK) in its monthly report. The statistical data on Islamic banking financing funds used in this study started from 2020 to 2022. JUB Inflation The Value of the Rupiah Against the Dollar AS BI Rate Financing Share Bank Syariah Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022 IJSSHR, Volume 08 Issue 11 November 2025 www.ijsshr.in Page 8751 Total Profit-Sharing Based Financing Total Financing The sample determination technique in this study is purposive sampling. Where the sample taken uses all the existing population numbers, namely 36 samples (data) which is monthly inflation data, Pembiayaan Perbankan Syariah, BI rate, Rupiah Exchange Rate against the US Dollar, and Money Supply (M2) from 2020 to 2022. 3) Data Collection Methods The data collection techniques used in this study are documentation methods and literature methods in accordance with the theories above. The collection of data related to research matters or variables is based on statistical data published in general by the OJK and the Central Statistics Agency, and has been processed in such a way that it can make it easier to analyze. c. Research Variables and Definition of Research Variables 1. Dependent Variable The financing share referred to in this study is the proportion of profit-sharing investment of Islamic banks. The proportion of profit-sharing investment is taken from OJK's annual report data . According to Hasan, the financing share is a comparison between the amount of financing distributed by Islamic banks and the amount of credit distributed by national banks in general (Hasan, 2010:57). Financing share data is expressed in percentages taken from Sharia Banking Statistics. The formula used to find the financing share is as follows (www.ojk.co.id): Investment = 2. Independent Variable a) Inflation Inflation is briefly defined as a tendency to increase the price of goods and services in general and continuously (Suseno, 2009). An indicator that is often used to measure the inflation rate is the Consumer Price Index (IHK). The inflation variable in this study is calculated using the monthly CPI. The inflation data used is the development of inflation per month from 2020 to 2022. The formula used is as follows: Inf = (IHK n) – (IHK n-1) x 100% (IHK n-1) Information: Inf : Inflation IHK n : IHK the month in question IHK n-1 : IHK previous month b) BI Rate BI Rate is a policy interest rate that reflects the monetary policy stance set by Bank Indonesia and announced to the public. c) Rupiah Exchange Rate against Dollar Exchange rate is a comparison of the exchange rate of a country's currency with the currency of a foreign country or a comparison of exchange rates between countries. Meanwhile, the rupiah exchange rate against the US dollar is a comparison of the rupiah exchange rate against the US dollar. d) Amount of Money in Circulation (JUB) Money Supply (M2) is the overall value of money in the hands of the community. The amount of money in circulation in a narrow sense (narrow money) is the amount of money in circulation consisting of currency and demand money. Keterangan: M1: The amount of money in circulation in a narrow sense C : Currency D : Bills of lading or checks Money circulation in a broad sense (M2) is plus time deposits. Information : M2 : Money Supply in a broad sense M1=C + D M2= M1 + TD X 100% 100% Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022 IJSSHR, Volume 08 Issue 11 November 2025 www.ijsshr.in Page 8752 TD : Time deposits d. Data Analysis Techniques 1. Classical Assumption Test Classic assumption testing includes the following: Classical Assumption Test Face Information Source Normality Test Test Jarque Bera If the Jarque-Bera Probability Value is greater than 0.05 then it indicates that the data is normally distributed. A good regression model is normally distributed data Ghozali (2006:147) Uji Autokorelasi Aji TelescopeWatson A good regression model that is free of autocorrelation Ghozali (2006: 99) Multicollinearity Test Uji VIF Ho: Tidak terjadi multikolinearitas dalam model H1: Terjadi multikolinearitas dalam model Model regresi yang baik adalah bebas multikolinearitas Ghozali (2006: 95) Uji Heteroskedastisidas Uji White Ho: tidak terjadi heteroskedastisitas H1: terjadi heteroskedastisitas Model regresi yang baik adalah bebas heteroskedastisitas Ghozali (2006:125) 2. Uji Kecocokan Model (Goodness Of Fit) a) Uji Determinasi (R2) Ghozali (2006: 87) said that the determination coefficient (R2) essentially measures how far the model is able to explain the variation of dependent variables. The value of the determination coefficient consists of only zero (0) and one (1). b) Uji F Ghozali (2006: 88) states that the statistical test F basically shows whether all independent or independent variables included in the model have a cohesive influence on the dependent or bound variables. c) Uji T The t-statistical test shows how far the influence of each independent variable individually in explaining the variation of the dependent variable (Ghozali, 2006: 91). d) Model regresi The data analysis technique used in this study is a test of multiple linear regression equation models. Systematically regression equations can be made as follows: PBS = α0+ β1Inf + β2BIrate + β3Kurs + β4JUB + e Where: PBS : Sharia Bank Financing Inf : Inflation You choose : Suku Bunga BI Exchange Rate : Rupiah to Dollar Exchange Rate JUB : Money Supply β1, β2, β3, β4, : The regression coefficient of each independent variable α0 : Constant e : Error Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022 IJSSHR, Volume 08 Issue 11 November 2025 www.ijsshr.in Page 8753 1. RESULTS AND DISCUSSION 1.1. Research Results a) Normality Test The normality test aims to find out whether each variable is normally distributed or not. One way to test the normality of the data is to look at the Jarque-Bera Probability value. If the Jarque-Bera Probability Value is greater than 0.05, then it indicates that the data is normally distributed and thus the regression model meets the assumption of normality. Here are the results of the normality test: 0 1 2 3 4 5 6 7 8 9 -100 -50 0 50 100 150 Series: Residuals Sample 2020M01 2022M12 Observations 36 Mean 1.89e-14 Median -5.288165 Maximum 151.4763 Minimum -113.1690 Std. Dev. 51.12187 Skewness 0.706548 Kurtosis 4.197125 Jarque-Bera 5.144921 Probability 0.076347 Figure 3.1.a: Normality Test Results Source: Eviews12 Output Based on figure 3.1.a, it is known that the probability value of JB is 0.076347 > 0.05 which means that the data in this study has a normal distributed data distribution, so that this data can be used in the study b) Autocorrelation Test The Autocorrelation test aims to see if in a linear regression model there is a correlation between the disruptive error in period t and the disruptive error in the period t-1 (previous). One way that can be used to detect the presence or absence of autocorrelation is with the serial Corelation LM Test. Here are the results of the Autocorrelation test: Figure 3.1.b Autocorrelation Test Results Breusch-Godfrey Serial Correlation LM Test: F-statistic 3.593513 Prob. F(2,29) 0.0403 Obs*R-squared 7.149882 Prob. Chi-Square(2) 0.0280 Sumber: Output Eviews12 Based on Figure 3.1.a, it can be explained that the probability value in Obs *R-squared is 0.0280 < 0.05, so it can be concluded that there is a problem in serial autocorrelation. Therefore, a healing method is carried out using the transformation of first difference data Gambar 3.1.b. First Difference Hasil Uji Autokorelasi setelah dilakukan transformasi data first difference Breusch-Godfrey Serial Correlation LM Test: F-statistic 0.7520 14 Prob. F(2,28) 0.4807 Obs*R-squared 1.7841 97 Prob. Chi-Square(2) 0.4098 Sumber: Output Eviews12 Based on figure 3.1.b. First Difference, after the first difference data transformation is carried out, the probability value of Obs* R-squared has a value of 0.4098 > 0.05, so it can be concluded that the assumption of the autocorrelation test has been fulfilled or has passed the autocorrelation test. Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022 IJSSHR, Volume 08 Issue 11 November 2025 www.ijsshr.in Page 8754 c) Multicollinearity Test The multicollinearity test was performed to show whether or not there is a linear relationship between independent variables in the regression model. Testing for the presence or absence of symptoms of multicollinearity can be done by detecting the value of Variance Inflating Factor (VIF). A VIF value of less than 10 indicates that multicollinearity does not occur. The following table shows the results of the multicollinearity test. Tabel 3.1.c Uji Multikolinieritas Variance Inflation Factors Date: 10/16/23 Time: 01:56 Sample: 2020M01 2022M12 Included observations: 36 Coefficient Uncentered Centered Variable Variance VIF VIF C 80182.19 978.2742 NA X1 0.085377 91.81713 21.37143 X2 770.3428 87.72099 20.88595 X3 0.000358 929.8881 1.062254 X4 3.28E-10 210.4882 1.705441 Sumber: Output Eviews12 Table 3.4 shows the results of the multicollinearity test as follows: 1. variable X1 (Inflation) has a Centered VIF value of 21.37143 > 10 (Symptoms of Multicollinearity occur) 2. Variable X2 (BI Rate) has a Centered VIF value of 20.88595 > 10 (Symptoms of Multicollinearity) 3. Variable X3 (Rupiah Exchange Rate) has a Centered VIF value of 1.062254 < 10 (Passed the Multicollinearity Test) 4. Variable X4 (JUB) has a Centered VIF value of 1.705441 < 10 (Passed the Multicollinearity Test) The results of this multicollinearity test show that in the regression model used in this study there is multicollinearity, in Variable X1 (Inflation) and Variable X2 (BI Rate) so that the regression model must be cured by transforming log data. Figure 3.1.c. Log data Multicollinearity Test Results with LOG data transformation Sumber: Output Eviews12 Based on Figure 3.1.c. log data, after the log data transformation is carried out, the test results are as follows: 1. Variable X1 (Inflation) has a Centered VIF value of 9.015219 < 10 (Passed the Multicollinearity test) 2. Variable X2 (BI Rate) has a Centered VIF value of 8.426360 < 10 (Passes Multicollinearity) 3. Variable X3 (Rp Exchange Rate) has a Centered VIF value of 1.062254 < 10 (Passes Multicollinearity) 4. Variable X4 (JUB) has a Centered VIF value of 1.705441 < 10 (Passes Multicollinearity) The results of the four variables show a number of less than 10, so it can be concluded that there is no multicollinearity problem in this study. Variance Inflation Factors Date: 10/16/23 Time: 03:23 Sample: 2020M01 2022M12 Included observations: 36 Coefficient Uncentered Centered Variable Variance VIF VIF C 114411.3 1383.926 NA LOG(X1) 3172.518 1141.759 9.015219 LOG(X2) 2332.350 27.97259 8.426360 X3 0.000359 924.5723 1.056182 X4 2.99E-10 189.8837 1.538496 Impact of Macroeconomic Conditions on the Share of Sharia Bank Financing in Indonesia in 2020 – 2022 IJSSHR, Volume 08 Issue 11 November 2025 www.ijsshr.in Page 8755 d) Htereoskenasticity Test The heteroscedasticity test showed that the variable variants were not the same for all observations. The heteroscedasticity test aims to "test for variance disparity from the residual of one observation to another. If the variant from the residual of one observation to another remains constant, then it is called homoscedasticity. A good regression model is one that is homogeneous or heteroscedasticity does not occur" (Ghozali, 2011:139). To determine whether or not there are symptoms of heteroscedasticity, the White Test can be used in the Eviews12 test as follows Gambar 3.1.d Heteroskedasticity Test: White Heteroskedasticity Test: White F-statistic 2.391652 Prob. F(14,21) 0.0345 Obs*R-squared 22.12415 Prob. Chi-Square(14) 0.0761 Scaled explained SS 26.22494 Prob. Chi-Square(14) 0.0242 Sumber: Output Eviews12 The test results using the White Test show the Prob Value . Chi-Square is 0.0761 > 0.05 so that this study is free from Heteroscedasticity. Model Fit Test (Goodness Of Fit) 1. Uji Determinasi (R2) The Coefficient of Determination (R2) is used to measure how far an independent variable is able to explain the dependent variable. The value of the coefficient of determination is between zero and one. The results of the determination coefficient (R2) in this study can be seen in the following Table 3.1.1: Dependent Variable: Y Method: Least Squares Date: 10/16/23 Time: 00:59 Sample: 2020M01 2022M12 Included observations: 36 Variable Coefficient Std. Error t-Statistic Prob. C 3964.885 283.1646 14.00205 0.0000 X1 0.304019 0.292193 1.040473 0.3062 X2 -7.321637 27.75505 -0.263795 0.7937 X3 0.027758 0.018918 1.467241 0.1524 X4 -7.23E-05 1.81E-05 -3.989798 0.0004 R-squared 0.356647 Mean dependent var 3907.333 Adjusted R-squared 0.273634 S.D. dependent var 63.73561 S.E. of regression 54.32002 Akaike info criterion 10.95591 Sum squared resid 91470.59 Schwarz criterion 11.17584 Log likelihood -192.2064 Hannan-Quinn criter. 11.03267 F-statistic 4.296271 Durbin-Watson stat 1.167585 Prob(F-statistic) 0.007010 Figure 3.1.1. Multiple Regression Sumber: Output Eviews12 Based on Figure 3.1.1, it can be explained that the value of the determination coefficient (R-Squared) is 0.356647. So, it can be concluded that the influence of inflation, BI rate, rupiah exchange rate and money supply on the share of Islamic bank financing in Indonesia is 35.66%, while 64.34% is influenced by other variables that are not described in the model. 2. Test F The F test is performed to find out whether all independent variables together (simultaneously) have an effect on the bound variable. In this study, there are two hypotheses in the F test, namely H0 : Simultaneously, inflation, BI Rate, Rupiah Exchange Rate, and Money Supply (JUB) do not have a significant influence on the Financing Share of Sharia Banks.