The Analysis of Macroeconomic and Microeconomic Factors in Non-Performing Financing of Sharia Bank in Indonesia

−This study aims to analysis of macroeconomic and microeconomic factors in non-performing financing of Sharia Bank in Indonesia. Inflation and the BI7DRR are macroeconomic factors. CAR and BOPO are indicators of microeconomic factors. NPF is a problematic financing indicator. Research methods with quantitative methods described in multiple linear regression analysis models. The population is obtained from the Bank Indonesia and Financial Ratios of Sharia Commercial Banks through the Sharia Indonesia Banking Statistics of the Financial Services Authority. The data is secondary in the form of monthly data for the period January 2018 to November 2022, so that a sample of 59 data was obtained for further analysis. Sampling techniques nonprobability by means of purposive sampling. The results of the study are as follows: (1) The estimation model shows an R 2 value of 0,738 which represents the value of the coefficient of determination. This means that 73,80% of the dependent variable variation is able to be explained by the independent variables in this model. The remaining 26,20% is explained by other causes that are not included in the model; 2) The regression model on the independent variable simultaneously influence the dependent variable, so that the independent variable regression model can be used to predict the dependent variable; and (3) This research produced output that the influential and significant ones are Inflation and BI7DRR as macroeconomic factors that can be used to analysis non-performing financing of Sharia Bank in Indonesia. This research also produced an output that CAR and BOPO have no influential as microeconomic factors that cannot be used to analysis non-performing financing of Sharia Bank in Indonesia. Although CAR and BOPO the results are significant.


INTRODUCTION
The main activity of the Bank in its operation as a financial institution is to function with full risk as an intermediary between the party that has excess funds and the party that has a deficit of funds. The risks inherent in financial institutions cannot be eliminated and will certainly always overshadow the Bank's operational activities at all times (Wahyudi et al., 2014). This is because every financing provided by the Bank to customers has the potential to be problematic or loss. Financing risk called Non Performing Financing (NPF) is a possible loss that will arise because the funds disbursed by Sharia Bank to customers cannot be returned (Ismail, 2016). In every Sharia Indonesia Banking Statistics report, NPF is defined as financing that is substandard, doubtful until it is loss (Djamil, 2012).
The ratio of non-performing financing (NPF) in Sharia Bank is lower than that of non-performing loan called NPLs in Conventional Bank from macroeconomic fluctuations (Poetry and Sanrego, 2011). There are at least three elements of factors that cause problematic financing: (1) From the Sharia Bank itself or the customer; (2) The borrower or customer; and (3) Other reasons, besides the customer and the Sharia Bank concerned. The performance of Sharia Bank that are microeconomic in nature is also the cause of customer factors. Meanwhile, the user of funds is the cause of the customer factor. Then, macroeconomic factors are factors outside of both (Popita, 2013). The Bank's performance assessment is carried out by analysing financial statement (Aprillia et al., 2015). Analysing financial statement start with basic financial statement, namely from the balance sheet, income statement calculation and cash flow statement (Fahmi, 2020).
The performance of Sharia Bank is macroeconomic in which Sharia Bank in Indonesia are institutions that also support national economic growth whose performance is influenced by macroeconomic conditions and policies set by the authority. In carrying out its function as an intermediation institution, the performance of Sharia Bank in Indonesia is influenced by various macroeconomic instruments, either directly or indirectly. Some of these macroeconomic instruments, such as inflation and the BI-7Day Reverse RepoRate (BI7DRR). Inflation is a condition in which there is an increase in the price of goods and services in general and continuously over a certain period of time. Stable and low inflation are absolute prerequisites for the country's economic growth. Another macroeconomic instrument is the BI7DRR which is one of the monetary policies set by Bank Indonesia (BI) and aims to strengthen the monetary operations framework by applying the benchmark interest rate or currently referred to as the BI7DRR (Widyastuti, 2022) which is effective since 19 August 2016 replacing the BI Rate. There are at least three main expected impacts, namely: (1) Strengthening monetary policy signals with the BI7DRR as the main reference in financial markets; (2) Increasing the effectiveness of monetary policy transmission through its influence on money market interest rate movements and banking interest rates; and (3) The establishment of deeper financial markets, particularly transactions and the establishment of an interest rate structure in the Interbank Money Market for a tenor of 3-12 months (Bank Indonesia, 2023).
Meanwhile, the performance of Sharia Bank which is microeconomic comes from operational activities within the Sharia Bank itself which is contained in financial performance. The financial performance of a Sharia Bank can be seen through its financial ratios as health indicators and as an analytical tool to predict the profits that will be generated, such as the Capital Adequacy Ratio (CAR) and The Ratio of Operational Expenses to Operational Revenue (BOPO) (Wahyuni et al., 2020). According to Kuncoro and Suhardjono (2012), CAR is a capital adequacy ratio that shows the ability of Sharia Bank to pay attention to capital that is sufficient for the ability of Sharia Bank management to identify, measure, supervise and control the risks that arise that can influence the amount of capital of Sharia Bank. While Hasibuan (2020) added that BOPO is a comparison or ratio of operating expenses in the last year to operating income in the same period.
The purpose of this study is to the analysis of macroeconomic and microeconomic factors in non-performing financing of Sharia Bank in Indonesia from January 2018 to November 2022. Inflation and the BI7DRR are macroenomic factors. CAR and BOPO are indicators of microeconomic factors. NPF is a problematic financing indikator. This research produced output that the influential and significant ones are Inflation and BI7DRR as macroeconomic factors that can be used to analysis non-performing financing of Sharia Bank in Indonesia. This research also produced an output that CAR and BOPO have no influential as microeconomic factors that cannot be used to analysis nonperforming financing of Sharia Bank in Indonesia. Although CAR and BOPO the results are significant.
The relevant research related to the research gap problem includes: (1) Ihsan and Haryanto (2011). Criteria for Sharia Commercial Bank that publish quarterly or quarterly financial statements during the observation period from 2005 to 2010. The results of the study found that Inflation did not have a significant influence on the NPF of Sharia Bank in Indonesia; (2) Akbar (2016). The population used in this study is all Sharia Commercial Bank in Indonesia listed in the Bank Indonesia Directory for the period 2010 to 2014. The results of the study are known that Inflation has no influence and is not significant on the NPF of Sharia Bank in Indonesia. Meanwhile, CAR has a negative and significant influence on the NPF of Sharia Bank in Indonesia; (3) Febrianti and Ashar (2016). Time series data used in this study include data from quarter 2006 quarter one to quarter 2014 quarter two from NPL of Conventional Commercial Bank, NPF of Sharia Commercial Bank and Sharia Business Unit, Real GDP Growth, Inflation, BI Rate and Exchange Rate. This study uses secondary data sourced from Bank Indonesia and the Central Bureau of Statistics. The results of the study found that the BI Rate (BI7DRR) significant influent NPL with a t-Statistic probability value of 0,0000 < 0,05. The coefficient for the BI Rate is 0,772711 with a positive relationship direction (+). Assuming cateris paribus where every increase in the BI Rate by 1 percent will increase NPLs by 0,772711 percent; (4) Wijoyo (2016). The study period used was monthly from January 2010 to December 2015. This research was conducted by taking secondary data from the results of publications by Bank Indonesia, the Financial Services Authority and the Central Bureau of Statistics. The results of the study found that macroeconomic factors in the form of Inflation in the long and short term did not have a significant influence on NPF. The Bank's specific condition factors in the form of BOPO in the long and short term both have a positive influence on NPF; and (5) Manafe (2017). This research data is based on time series obtained from quarterly financial statements published on the website of PT. Bank Syariah Mandiri in Indonesia in the period 2011 to 2015. The results of the analysis that have been carried out show positive and significant Inflation results on NPF.
Then, (6) Pradana (2018). This research was conducted on Sharia Commercial Bank in Indonesia registered from 2012 to 2015 from the Reports of Bank Indonesia and the Central Bureau of Statistics. Based on the results of the analysis that Inflation has no influence on the NPF of Sharia Commercial Bank in Indonesia; (7) Sanusi et al. (2019). The purpose of the study was to analysis the relationship between macroeconomic and Non-Performing Financing (NPF) in Syaria Financial Institutions in Indonesia. Data sources were obtained from the official websites of Bank Indonesia and the Financial Services Authority for the period January 2008 to June 2019. The results in this study show that the BI Rate (BI7DRR) has a significant positive influence. Meanwhile, Inflation has no significant influence; (8) Asmara (2019). The data used is quarterly time series data for the period 2014 to 2018 sourced from Sharia Financial Statistic and Development Reports. The results showed that Inflation and BOPO influence on NPF. While CAR has no influence on NPF; (9) Setiawan (2020). This type of research is quantitative research using secondary data in the form of monthly data published by the Financial Services Authority and Bank Indonesia for the period 2016 to 2019. The results of this study show that Inflation in the short term does not have a significant influence on NPF. While BOPO in the short and long term has a significant influence on NPF; and (10) Arfan (2020). Data is obtained from the Sharia Banking Statistic Report published by Bank Indonesia from January 2011 to December 2014. The test results revealed that the BI Rate (BI7DRR) has a significant positive influence on NPF. However, Inflation has a negative and insignificant influnce on NPF.
Then, (11) Harahap et al. (2020). This study aims to analysis the influence of exogenous variables, one of which is Inflation on NPF in Sharia Bank. This research used time series data from 2016 to 2018. The results showed that Inflation had a positive and significant influence on NPFs in Sharia Bank; (12) Windasari and Diatmika (2021). The population in this study is from the Indonesian Sharia Banking Statistic published by the Financial Services Authority and from Indonesian Economic and Financial Statistics data from Bank Indonesia.The sample used in this study from 2015 to 2018. The results of this study state that Inflation has a positive and significant influence on NPF; (13) Aviantari (2021). Research data in the form of secondary data on a monthly basis published by the Financial Services Authority for the period 2016 to 2019. The results of this study show that Inflation in the short and long term does not have a significant influence on NPF; (14) Sholehah et al. (2022). The data used in this study is panel data for the period of quarters I-IV of 2015 to 2018 sourced from the Sharia Rural Bank (BPRS) of Banten Province. The results showed that Inflation did not have a significant influence on NPF. While CAR has a negative and significant influence on NPF; and (15) Fahlevi (2022). The data used is secondary data obtained from financial statements obtained through the websites of the Financial Services Authority and Bank Indonesia for the period 2016 to 2020. The results showed that Inflation had a significant positive influence on NPF.
Therefore, this research is interesting to research and quite important. In addition, the expected benefit of the bidding solution to the problems encountered from the results of this study is the need for Sharia Bank to re-strategy so that the percentage of their NPF rate is not above 5% by managing financing risk exposure at an adequate level. This is because, if the NPF is not managed effectively, it will interfere with the business continuity of the Sharia Bank itself. This is very important to ensure that the financial performance of Sharia Bank is always in good condition. The financial performance of Sharia Bank refers to the assessment of the health level of Sharia Commercial Bank and Sharia Business Unit of Conventional Bank as regulated in the Financial Services Authority (POJK) Regulation Number 8/POJK.03/2014 dated June 11, 2014. The health of Sharia Bank is in the interest of all relevant parties, both owners, managers (management) and the public who use Sharia Bank services as customers. In the end, the results of this study are expected to contribute in terms of facts and rules, objective, reasonable and have empirical assumptions of scientific truth.

Research Approach
Research is the channeling of human curiosity in the scientific level. One would be convinced that there is a cause for every effect of every apparent symptom scientifically searchable. This is because the research is objective because the conclusions obtained will only be drawn based on convincing evidence and collected through clear, systematic and controlled procedures (Sunggono, 2015). The research method is the main style in obtaining goals and proving the answers to the problems posed by the researcher (Arikunto, 2019). The research approach that the author uses in this case is by quantitative methods. The data is in the form of numbers analyzed on the basis of statistical procedures (Noor, 2016).

Data Type and Data Source
The type of secondary research data sourced from the Bank Indonesia and Sharia Indonesia Banking Statistics of the Financial Services Authority (SPS OJK) is in the form of monthly data from January 2018 to November 2022. So, a sample of 59 data was obtained for further analysis. According to Rusiadi et al. (2014) secondary data are those obtained or collected by researchers from various existing sources.

Population, Sampling and Sampling Techniques
Population is a specific behavior that belongs to a combination of people, animals, plants or objects to be studied (Mulyatiningsih, 2014). The sample is a portion taken from the population (Sudjana, 2014). Sampling techniques nonprobability by means of purposive sampling. Because, each element of the population selected into the sample does not have the same opportunity to be selected. So, sampling techniques with certain considerations (Sugiyono, 2014). The research population was obtained from the Bank Indonesia and Financial Ratios of Sharia Commercial Banks through the Sharia Indonesia Banking Statistics of the Financial Services Authority (SPS OJK).

Research Models
Multiple regression is used by researchers if the researcher intends to predict how the state (ups and downs) of variable is dependent. Multiple regression analysis will be carried out if the number of independent variable is at least two variable (Sugiyono & Susanto, 2015) where this research model can be described in the equation of multiple linear regression analysis with the equation:

Research Framework
The framework of this study is based on the analysis of macroeconomic and microeconomic factors whether they are influential and significant in the non-performing financing of Sharia Bank in Indonesia. Inflation and the BI7DRR are

Research Results
In statistical testing, the coefficient of determination (R 2 ) is used to measure how far the model's ability to describe the variation of dependent variable is. The value of the coefficient of determination is between zero and one. The F test is called a simultaneous test aimed at testing whether there is a linear relationship between variables. The t-test is called a partial test aimed at testing whether a variable is independent to influence the dependent variable. Table 1 shows a summary of the regressions.

Accuracy Test Results R 2
Based on Table 1 the R 2 value is 0,738 which represents the value of the coefficient of determination. This means that 73,80% of the dependen variable variation is able to be explained by the independen variables in this model. The remaining 26,20% is explained by other causes that are not included in the model.

F Test Results
Based on Table 1 the analysis and conclusions obtained F as F calculated 37,974 greater than the F of the table of 2,543 (37,974 > 2,543) and a Sig. value of 0,000 smaller than 0,05 (0,000 < 0,05). In conclusion H0 is unacceptable (rejected) and Ha is acceptable (cannot be rejected). This means that regression models on independen variable simultaneously influence dependen variable, so the independen variable regression model can be used to predict dependen variable.

t Test Results
The analysis and conclusion of the t-test results based on Table 1 of the regression summary below are as follows: 1. The variable X1 has a calculated t value of 3,738 greater than the table t of 2,994 (3,738 > 2,994) or a Sig. value of 0,000 smaller than 0,05 (0,000 < 0,05). It can be concluded that H0 is unacceptable (rejected) and Ha is acceptable (cannot be rejected). However, the variable X1 has a negative direction of relationship to the variable Y. This means that the variable X1 has a negative and significant influence on variable Y. 2. The variable X2 has a calculated t value of 4,216 greater than the table t of 2,994 (4,216 > 2,994) or a Sig. value of 0,000 smaller than 0,05 (0,000 < 0,05). It can be concluded that H0 is unacceptable (rejected) and Ha is acceptable (cannot be rejected). However, the variable X2 has a negative direction of relationship to the variable Y. This means that the variable X2 has a negative and significant influence on variable Y. 3. The variable X3 has a calculated t value of 9,559 greater than the table t of 2,994 (9,559 > 2,994) or a Sig. value of 0,000 smaller than 0,05 (0,000 < 0,05). It can be concluded that H0 is unacceptable (rejected) and Ha is acceptable (cannot be rejected). However, the variable X3 has a negative direction of relationship to the variable Y. This means that the variable X3 has a negative and significant influence on variable Y. 4. The variable X4 has a calculated t value of 2,314 less than the table t of 2,994 (2,314 < 2,994) or a Sig. value of 0,025 less than 0,05 (0,025 < 0,05). It can be concluded that H0 is acceptable (cannot be rejected) and Ha is unacceptable (rejected). However, the variable X4 has a negative direction of relationship to the variable Y. This means that the variable X4 has no negative and significant influence on variable Y. -0,260 -9,559 0,000 X4 F = 37,974; Sig. = 0,000 -0,026 -2,314 0,025 R = 0,859; R 2 = 0,738

Discussion
Based on Table 1  Rating 5 (PK-5) is subject to administrative sanctions including freezing certain business activities; and/or the inclusion of the Bank's management and/or shareholders in the list of parties who received the predicate did not pass the fit and proper test. The Bank's Health Level Composite Rating is assigned based on a comprehensive and structured analysis. Nugrohowati and Bimo (2019) explained that the high value of NPF has shown indicators of the failure of Sharia Bank in managing the funds they distribute to customers. Of course, the impact influence the performance of the Sharia Bank itself. In fact, the NPF ratio of each Sharia Bank in accordance with the provisions of the Financial Services Authority (OJK) regulator as a government agency that has the task of regulating and supervising financial services must not exceed the 5% limit. Putranta (2019); and Fakhruddin and Purwanti (2015) explained that most of the NPF levels of Sharia Bank exceed the maximum limit that has been determined by the percentage, which is 5%. This has an impact on the possibility of a Sharia Bank in a non-performing financing condition is even greater. 2. The variable regression coefficient of INFLATION (X1) was obtained at -13,676. This means that low Inflation of 1% will have a negative influence on the decrease in the NPF of non-performing financing of Sharia Bank in Indonesia (Y) by 13,676%. Lidyah (2016) explained that the influence of changes in Inflation on NPF is that high Inflation will cause a decrease in people's real income as customers, so that people's living standards also fall. Before Inflation, a customer was still able to pay his financing installments. However, after Inflation occurred, prices experienced a fairly high increase. Meanwhile, the customer's income has not increased. This has an impact on the customer's ability to pay their financing installments to be weakened and the financing to be problematic. Because, most or even all of his income has been used to meet household needs as a result of rising prices. Huda (2018) explained that Inflation will reduce the real wages of every individual with a fixed income. The hypothesis of this study is that INFLASI (X1) has a negative and significant influence on the analysis of macroeconomic and microeconomic factors in the non-performing financing of Sharia Bank in Indonesia (Y). The results of this study are match the hypothesis. Although Pane (2011) explained that any decrease in Inflation will result in an increase in non-performing financing (NPF) in Sharia Bank. Conversely, any increase in Inflation will result in a decrease in non-performing financing ( will have a negative influence on the decrease in the NPF of non-performing financing of Sharia Bank in Indonesia (Y) by 22,535%. Hernawati and Puspasari (2018) explained that if there is an increase in BI7DRR, it will be followed by an increase in NPF for non-performing financing. On the other hand, if the BI7DRR experiences a decline, it will also be followed by a decrease in the NPF of non-performing financing. Hamzah (2018) explained that if the BI7DRR falls, the margin of Sharia Bank is higher than that of Conventional Bank. This results in customers preferring Conventional Bank. So, Sharia Bank also helped reduce the profit-sharing ratio and margins. Although Lestari (2016) explained that the direct influencing of BI7DRR on non-performing loans (NPLs) is that if the increase in BI7DRR will automatically increase loan interest rates where the interest burden borne by customers will be heavier, then the customer's ability to pay installments will weaken and will increase the number of non-performing loans (NPLs) at the Bank concerned. Although Sharia Bank do not recognize interest rates. However, according to Prastiwi (2021), the determination of profit-sharing ratio and margin at Sharia Bank is inseparable from the interest rate of Conventional Bank. The BI7DRR is a reference for Conventional Bank interest rates. This Conventional Bank interest rate is used as a reference by the Asset Liabilities Committee (ALCO) of Sharia Bank in determining the profit-sharing ratio and margin. The hypothesis of this study is that BI7DRR (X2) has a negative and significant influence on the analysis of macroeconomic and microeconomic factors in the non-performing financing of Sharia Bank in Indonesia (Y). The results of this study are match the hypothesis. Nurismalatri (2017) explained that the high BI7DRR has an impact on reducing non-performing financing. The results of this study support the research of Soebagio (2005); Osei-Assibey and Asenso (2015); Amelia (2019); and Anggraini (2021). 4. The variable regression coefficient of CAR (X3) -0,260 was obtained. This means that a low CAR of 1% have a negative influence on the increase in the NPF of non-performing financing of Sharia Bank in Indonesia (Y) by 0,260%. Yuliani (2016) explained the causes of low Sharia Bank CAR due to: (1) The erosion of Sharia Bank capital due to negative spreads; and (2) There is an increase in assets that are not supported by an increase in capital. This is because the calculation of CAR is based on the principle that every investment that contains risk must be provided with a certain amount of capital of a certain percentage (risk margin) to the amount of investment. The hypothesis of this study is that CAR (X3) has a positive and significant influence on the analysis of macroeconomic and microeconomic factors in the non-performing financing of Sharia Bank in Indonesia (Y). The results of this study do not match the hypothesis. According to Pratiwi (2012); Wibowo and Saputra (2017); and Supriani and Sudarsono (2018) if Sharia Bank have a high CAR, then Sharia Bank will have more ability to bear the risk of losses, especially losses caused by financing risk (NPF). Therefore, the capital owned by Sharia Bank can function as an absorber of Sharia Bank losses and reduce the percentage of NPF. Purwaningtyas and Hartono (2020); and Sari and Kusuma (2021) explained that this means that increasing the capital adequacy of Sharia Bank (CAR) will manage the risk of non-performing financing more easily which can reduce the value of NPF and anticipate potential losses caused by financing distribution. The results of this study do not support the research of Asnaini (2014); Alissanda (2015); Nugraini (2015); Firmansari and Suprayogi (2015); and Retnowati and Jayanto (2020). 5. The variable regression coefficient of BOPO (X4) was obtained at -0,026. This means that low Inflation of 1% will have a negative influence on the decrease in the NPF of non-performing financing of Sharia Bank in Indonesia (Y) by 0,026%. Isnaini et al. (2021) indicate that with good cost efficiency, of course, the smaller the BOPO ratio. Therefore, the bank's problematic condition is also getting smaller and vice versa. Rivai et al. (2013);and Firmansyah (2014) also explained that if the BOPO ratio is getting smaller, it will be better because the Bank concerned can cover operating expenses with its operating income. This means that the flexibility to minimize the occurrence of NPF for non-performing financing can be overcome. The above opinions are strengthened by Darmawanti and Suprayogi (2020) who explained that if the BOPO is bigger, the higher the NPF of nonperforming financing of Sharia Bank in Indonesia. The hypothesis of this study is that BOPO (X4) has a negative and significant influence on the analysis of macroeconomic and microeconomic factors in the non-performing financing of Sharia Bank in Indonesia (Y). The results of this study do not match the hypothesis. According to Sudarsono (2017) Sharia Bank in a problematic NPF condition if the Sharia Bank does not operate efficiently as indicated by a high BOPO ratio. The decline in non-performing financing influencing the decline in operating income of Sharia Bank. Janah and Siregar (2018) explained that the increase in BOPO shows a bad situation because every sales rupiah absorbed in high costs and those available for net profit are small. The results of this study do not support the research Suryanto's (2015); Shafii (2015); Setiawan et al., (2017); Haryanto and Widyarti (2017); and Mirawati et al. (2021).

CONCLUSION
The results of the study are as follows: (1) The estimation model shows an R 2 value of 0,738 which represents the value of the coefficient of determination. This means that 73,80% of the dependent variable variation is able to be explained by the independent variables in this model. The remaining 26,20% is explained by other causes that are not included in the model; 2) The regression model on the independent variable simultaneously influence the dependent variable, so that the independent variable regression model can be used to predict the dependent variable; and (3) This research results in the output that Inflation and BI7DRR are influential and significant as macroeconomic factors that can be used to analysis non-performing financing of Sharia Bank in Indonesia. This research also produced an output that CAR and BOPO have no influential as microeconomic factors that cannot be used to analysis non-performing financing of Sharia Bank in Indonesia. Although CAR and BOPO the results are significant. However, not on CAR is one of the microeconomic factors that have no influence. Although CAR results are significant. Although the findings of this study are interesting and workable. However, this research needs further deepening, so that this research is more meaningful and has a contribution. For these reasons, it is recommended that subsequent researchers continue this research. Although this research does not have to be exactly the same as previous research. In addition, there are several aspects that can be used as differences as novelty including research data; research variables; research methodology; and the object of study. However, still pay attention and base thoughts with the rules of scientific thinking.