Factors Affecting the Amount of Investment Loans in Commercial Banks with the Application of Linear Regression Analysis Methods

Several factors can affect the amount of investment credit issued by the bank. This study discusses the effect of interest rates, inflation rates, capita income, and the number of medium-large industries on the number of investment loans, using the method of linear regression analysis. The independent variables examined to determine the influence of each and all the independent variables on the number of investment loans in commercial banks, namely interest rates, inflation rates, capita income, and the number of medium-large industries using the parameter estimation method, OLS (Ordinary Least Square).


Introduction
Investment Credit is credit issued by a bank for the purpose of purchasing business capital goods. Several factors can affect the amount of investment credit issued by the bank. In this study only investigated the influence of interest rates, inflation rates, capita income, and the number of large medium industries to the amount of investment credit [3].
Banking has an important role because in accordance with its function is to collect and channel funds in the community, while the aim is to support the implementation of national development in order to increase equity in economic growth and national stability towards improving people's welfare [3].
Knowing the factors that are very influential on investment credit, people are easier to take investment loans. The world of banking through investment credit will later play a direct or indirect role in the economy of society, the state, and the banking world itself [1].
Banking activities are also needed to conduct a business activity in which banks also provide investment credit services as an effort to launch a business that is being undertaken. This investment credit service is an easy solution for new entrepreneurs who create jobs and to support them. Loans increase the expansion of employment, reduce unemployment and credit can increase income distribution in the implementation of development [5].

Methodology
The stages of analysis used are illustrated in the flowchart as follows,

Figure 1. Flowchart of data processing methods
The flowchart above is a brief explanation of the steps taken in analyzing the amount of investment credit in Indonesian commercial banks [2]. The full description of the sequence of analysis steps will be explained as follows: 1. Test data by performing a classic assumption test consisting of 4 assumption tests, namely multicollinearity assumption test, heteroscedasticity assumption test, normality assumption test, and autocorrelation assumption test.
2. The data that meets the test requirements of the assumption will be directly determined by the regression model, while the data that does not meet the assumption test requirements will be addressed first so that the data can meet the assumption test and the estimation model can be estimated [7]. 3. Determine the estimated model so that the regression model is obtained 4. Test the regression model that has been obtained by the significance test or significance test of the regression model. Simultaneous test (F test) to find out whether the regression model can be used as an estimator, and partial test (t test) to find out the closeness relationship between the independent variable and the dependent variable.

Test for Assumption of Heteroscedasticity
From the analysis of the output of IBM SPSS Statistics 19 (scatterplot image) above, we find points spread below and above the Y axis, and do not have a regular pattern. So, the conclusion is that the independent variables above do not occur heteroscedasticity or are homoskedasticity. Then it can be concluded that the above data does not occur autocorrelation.

Results of Linear Regression Analysis
To determine the linear regression coefficient, the equation is used [4] ̂= ( ′ ) −1 ′ .
The results are as follows.  From the results of the calculation above, the value of 2 is 0.36112711. The decision to accept the model obtained is good or not can be seen from the coefficient of determination and the results of the F test together, then in this study it can be concluded that the effect of the independent variable in this study is the interest rate (X1), inflation rate (X2), capita income (X3) and the number of large and medium industries for the number of investment loans in Indonesian commercial banks is 36.11%, which means that 63.89% is influenced by other independent variables not included in this study. The results of the F test also show that the interest rate (X1), inflation rate (X2), capita income (X3) and the number of large and medium industries (X4) have a significant effect on the amount of investment credit in Indonesian commercial banks (Y). From the calculation of the coefficient of determination and the F test, it can be concluded that the variables X1, X2, X3 and X4 simultaneously have a significant effect on the Y variable, but

Conclusion
The results of the research can be summarized as follows: Based on testing (simultaneous / concurrent) shows that there is a simultaneous influence between factors