Parameter Estimation Using LU Decomposition in the Logistic Regression Model for Credit Scoring Analysis

Banking is a financial institution that has a very important role in economic and trade activities which is useful for channeling funds in the form of loans to the public who need fresh funds for business in the hope of helping to improve the people's economy. In the loan process, banks are often exposed to risks known as credit risk or non-performing loans. Therefore, a credit analysis is performed by estimating the parameters using LU Decomposition in the Logistic Regression model. In this paper, the data used are data about cooperative financial services in Indonesia. Variables taken in the study are including the age of debtors (X1), family dependents (X2), the amount of savings (X3), the value of collateral (X4), the amount of income per month (X5), given the credit limit (X6), take home pay (X7), and the loan term (X8).