The Effect of BCA, BRI and Bank Mandiri Performance on The Indonesia Composite Index

Artikel Info Abstrak Article history: Received May 15, 2020 Revised June 24, 2020 Accepted June 25, 2020 Available online June 29, 2020 The Indonesia Composite Index (ICI) serves as a tool to measure and compare stock price movements in the capital market. The purpose of the research is to analyze the impact of the Operational Efficiency, Net Interest Margin, and Non-Performing Loan Ratios on Bank BCA, BRI, and Bank Mandiri as independent variables. Data used in this research was taken from the Financial Services Authority. The result from the F test shows a significant relationship in Operational Efficiency, Net Interest Margin, and Non-Performing Loan on the Bank BCA, BRI, and Mandiri towards the Indonesia Composite Index. Meanwhile, the t-test shows a significant relationship between Non-Performing Loan on the Bank BCA, Net Interest Margin on the Bank BRI, and all variables on the Bank Mandiri to Indonesia Composite Index. Based on Adjusted R Square; Operational Efficiency Ratio, Net Interest Margin, and Non-Performing Loan towards to Indonesia Composite Index is 88% while the rest of it 12% were influenced by other factors Keyword: Net Interest Margin; NonPerforming Loan; Operational Efficiency.


INTRODUCTION
The Indonesia Composite Index (ICI) serves as a tool to measure and compare stock price movements in the capital market (Setiawan & Mulyani, 2020). One factor which may affect the ICI are banks as a financial institution that is run by the government or privately as a means to manage and channeling funds. Therefore, the ratio in the bank can affect the ICI (Hanafi & Imelda, 2020). Several bank ratios can affect the ICI one of which is the Operational Efficiency Ratio (OER) as a comparison between operating costs and operating income. If there is an increase in the OER ratio in a bank, then it can be said that the performance of a bank is bad because it is inefficient and ineffective in managing its operational expenses against operating income, so this can cause a decrease in the ICI (Suryadi, Mayliza, & Ritonga, 2020). The second variable is the Net Interest Margin (NIM) is a ratio to measure the ability to manage a bank's assets. If the NIM ratio decreases at a bank this can cause a decline in income of a bank, which in turn causes a decrease in the ICI (Andarista, Winarni, & Finanto, 2020) and the last variable is Non-Performing Loan (NPL) which measures the ability of credit management performance in a bank. The increase in NPL ratio can cause losses to banks due to inefficient management in managing bad loans. This can cause a decrease in ICI (Munawar & Maulana, 2018). (Sitoresmi & Herawaty, 2020)  In the previous research, the independent variable only focused on the stock price index and stock returns, while this research will examine the effect of the performance of 3 banks on the ICI because the 3 banks above are the largest in Indonesia, but needs further research through this research. The purpose of this research was to determine the effect of the ratio of OER, NIM, and NPL at Bank BCA, BRI, and Bank Mandiri on ICI as a performance analysis of Bank BCA, BRI and Bank Mandiri in ICI.

Data Collection Technique
The data used in this research uses secondary data obtained from (Otoritas Jasa Keuangan, 2020) from 2010 to 2019.

Data Analysis Techniques
The analysis technique used in the study used multiple regression analysis models utilizing SPSS version 17, this test was carried out based on the classical assumption tests such as normality test, autocorrelation test, heteroscedasticity test, simultaneous F test, partial t-test and coefficient of determination.

Multiple Regression Analysis
Multiple regression analysis is an analysis of the influence of one or more independent variables (X) with one or more related variables (Y). Regression analysis can be determined by the multiple regression equation formula. The similarity is = + 11 + 22 + 33 + е (Kadir & Wahyudi, 2019).

Normality Test
This test is conducted to determine whether the data in this study are normally distributed or not using the normal PP Plot graphical method of standardized residual cumulative probability (Praptiningsih & Yetty, 2020).

Autocorrelation Test
Autocorrelation test is used to test whether there is a correlation between the independent variable and the dependent variable by looking at the value of the Durbin Watson (DW) (Munawara & Hadianib, 2020).

Heteroscedasticity Test
This test is carried out to determine the presence or absence of heteroscedasticity using scatterplot regression (Saragih & Girsang, 2020).

Multicollinearity Test
Multicollinearity test is a test used to find out whether there is a correlation between independent variables by looking at the tolerance value and the VIF value (Destiana & Jubaedah, 2017).

F Test (Simultaneous)
Simultaneous F test is a test used to determine the effect of all independent variables on the dependent variable by comparing the F calculate value with the Ftable and the significant value (Yusmalina, Lasita, & Haqiqi, 2020).

The T-test (Partial)
The partial t-test is a test used to determine the effect of independent variables on the dependent variable individually by looking at significant values (Rianto, 2018).

Coefficient of Determination
The coefficient of determination is used to determine the percentage (%) of the influence of the relationship between the independent variables on the dependent variable by looking at the adjusted R square value (Alfaruq, Achmad, & Mahendra, 2019).

Multiple Regression Analysis
The multiple regression analysis equations are = + 11 + 22 + 33 + е and can be explained as follows: 1. The constant (α) of 6803.330 shows the constant of ICI (Y), assuming the value of each independent variable (X 1 , X 2 , X 3 , X 4 , X 5 , X 6 , X 7 , X 8 , X 9 ) is constant. 2. The regression coefficient OER BCA(X 1 ) of −25.850 indicates a negative relationship, which means that between OER with ICI shows the opposite relationship, meaning that any increase in the value of OER will result in a decrease in the value of ICI and any decrease in OER will increase ICI. 3. The regression coefficient NIM BCA (X 2 ) of 141.536 indicates a positive relationship, which means that between NIM with ICI showed a unidirectional, meaning that any increase in the value of NIM with ICI will increase the value of ICI and any decrease in NIM will result in a decrease in the value of ICI. 4. The regression coefficient NPL BCA (X 3 ) of 3241.527 indicates a positive relationship, which means that between NPL with ICI showed a unidirectional, meaning that any increase in the value NPL with ICI will increase the value ICI and any decrease in NPL will result in a decrease in the value ICI. 5. The regression coefficient OER BRI (X 4 ) of 48.925 indicates a positive relationship, which means that between OER with ICI showed a unidirectional, meaning that any increase in the value OER with ICI will increase the value ICI and any decrease in OER will result in a decrease in the value ICI.
6. The regression coefficient NIM BRI (X 5 ) of −497.898 indicates a negative relationship, which means that between NPL with ICI shows the opposite relationship, meaning that any increase in the value NIM with ICI will result in a decrease in the value ICI and any decrease in NIM will increase the value ICI. 7. The regression coefficient NPL BRI (X 6 ) of −670.297 indicates a negative relationship, which means that between NPL with ICI shows the opposite relationship, meaning that any increase in the value NPL with ICI will result in a decrease in the value ICI and any decrease in NPL will increase the value ICI. 8. The regression coefficient OER Bank Mandiri (X 7 ) of −102.648 indicates a negative relationship, which means that between OER with ICI shows the opposite relationship, meaning that any increase in the value OER with ICI will result in a decrease in the value ICI and any decrease in OER will increase the value ICI. 9. The regression coefficient NIM Bank Mandiri (X 8 ) of 927.412 indicates a positive relationship, which means that between NIM with ICI showed a unidirectional, meaning that any increase in the value NIM with ICI will increase the value ICI and any decrease in NIM will result in a decrease in the value ICI. 10. The regression coefficient NPL Bank Mandiri (X 9 ) of 1478.617 indicates a positive relationship, which means that between NPL with ICI showed a unidirectional, meaning that any increase in the value NPL with ICI will increase the value ICI and any decrease in NPL will result in a decrease in the value ICI.

Normality test
If the points spread around the diagonal line and follow the direction of the diagonal line, the data is normally distributed (Praptiningsih & Yetty, 2020).

Figure 1. Normal P-Plot
The results normal P-P Plot graph display of standardized residual cumulative probability shows that the points spread around the diagonal line

The Effect of BCA, BRI and Bank Mandiri Performance on The Indonesia
Composite Index

Latifah, Sumantri
44 and follow the direction of the diagonal line, which means the data is normally distributed.

Autocorrelation Test
If the DW value is between -2 to +2, it can be concluded that there is no autocorrelation between the independent variables and the dependent variable (Munawara & Hadianib, 2020).

Heteroscedasticity Test
If the pattern of points spreads above and below the number 0 on the X and Y axis, it can be concluded that there is no heteroscedasticity (Saragih & Girsang, 2020).

The Effect of BCA, BRI and Bank Mandiri Performance on The Indonesia
Composite Index

Latifah, Sumantri
In the scatterplot graph in this research shows the pattern of points spread above and below the number 0 on the X and Y axis, it can be concluded that there was no heteroscedasticity in this research.

Multicollinearity Test
If the tolerance value>0.10 and VIF value<10, it can be concluded that there is no multicollinearity between independents variables (Destiana & Jubaedah, 2017). Based on the SPSS test results above, it shows that the OER, NIM and NPL variables from BCA Bank have a tolerance value>0.1 and a VIF value<10. In the OER, NIM and NPL variables from BRI Bank have a tolerance value>0.1 and a VIF value<10. In the OER, NIM and NPL variables from Mandiri Bank have a tolerance value>0.1 and a VIF value<10. So it can be concluded that there is no multicollinearity between independent variables that have been regressed.

F Test (Simultaneous)
If the F-calculate value>F-table and a significant value<0.05, it can be concluded that there is a significant influence between the independent variables on the dependent variable (Yusmalina et al., 2020).

The Effect of BCA, BRI and Bank Mandiri Performance on The Indonesia
Composite Index

T Test (Partial)
If the value of sig<0.05 then the independent variable (X) has a partial effect on the dependent variable. However, if the value of sig>0.05 then the independent variable there is no partial effect on the dependent variable (Rianto, 2018).

Coefficient of Determination
The coefficient of determination can be seen by using the value of the adjusted R square (Alfaruq et al., 2019).  (Y) is influenced by the independent variables OER, NIM, and NPL from BCA, BRI, and Mandiri Bank by 88 %, while the remaining 12 % is influenced by other factors outside the model. Based on the above research it can be seen that at BCA only it's NPL variables that affect the ICI, and has a positive influence, meaning that any increase in NPL value at the BCA can cause an increase in the ICI value and any decline in NPL value at the Bank BCA can cause a decrease on the value of the ICI. BRI has an influence on the ICI only NIM, NIM at Bank BRI has a negative influence on the ICI, which means that any increase in the value of the NIM at the BRI will cause a decrease in the ICI value and any decline in the value of the NIM at the BRI can cause an increase on the value of the ICI. Meanwhile, at Mandiri Bank, all variables affect the ICI. However, the NIM and NPL variables of Mandiri Bank have a positive influence on the ICI, which means that any increase in the value of NIM and NPL in Mandiri Bank can cause an increase in the ICI value, while the OER variable in Mandiri Bank has a negative influence on the ICI, which means that each increase in the value of OER Mandiri Bank can cause impairment of ICI and any decline in the value of OER at the Mandiri Bank can cause an increase in the value of the ICI. This is the opposite direction from research (Nureny, 2019) which concluded that the Net Interest Margin (NIM), Non-Performing Loans (NPL), and Operational Efficiency Ratio (OER) partially NIM, NPL and OER did not significantly influence the index stock price.

CONCLUSION
The results of the simultaneous test (F test), indicate that there is a significant influence between the independent variables on BCA, BRI, and Mandiri Bank on the ICI. Based on the t-test, it was found that BCA had the NPL variable influencing the ICI. Meanwhile, BRI Bank has an influence on ICI only for NIM and all variables of Mandiri Bank affect the ICI. Based on the test Adjusted R Square result shows that the independent variables (OER, NIM, and NPL) at BCA, BRI, and Mandiri Bank influence the dependent variable (ICI) at 88%. While the remaining 12% is influenced by other factors outside the model. From the test results above it was found that the Mandiri Bank has the most influential independent variables towards ICI, so we can conclude that Mandiri Bank has more influence on ICI compared to BRI and BCA.