Predicting the Feasibility of Providing Loans to Customers Using the Decision Tree Classification Algorithm, case study of the Maju Mandiri Savings and Loans Cooperative
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Abstract
Savings and loan cooperatives play an important role in providing financial access for the community. One of the main challenges faced is determining a customer's eligibility to receive a loan. This research aims to apply the Decision Tree classification algorithm in predicting the feasibility of providing loans to Maju Mandiri Savings and Loans Cooperative customers. The data used in this research includes various relevant financial variables. It is hoped that the findings of this research will help the Maju Mandiri Savings and Loans Cooperative in improving the efficiency and accuracy of the customer eligibility assessment process. In this way, cooperatives can reduce the risk of bad credit and improve the welfare of their members. This research also contributes to the academic literature by demonstrating the practical application of Decision Tree algorithms in the financial sector.
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