Implementasi Metode Decision Tree Dalam Memprediksi Kelayakan Pengajuan Kredit Di Koperasi Serviam

DA CRUZ, Jeanilka Lovenza Xavier Lopez (2022) Implementasi Metode Decision Tree Dalam Memprediksi Kelayakan Pengajuan Kredit Di Koperasi Serviam. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.

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Abstract

This system aims to make it easier for cooperatives to evaluate credit recipients more effectively as a preventive measure to reduce the risk of bad credit by predicting prospective borrowers first as a reference and consideration before loan funds are distributed. Before applying for a loan, cooperative members who want to apply for a loan can predict whether or not they are eligible to receive a loan to optimize the performance of the credit officer. Observations of this problem were carried out at KSP CU Serviam Kupang. The design displayed in this system uses the PHP7 programming language and MySQL as the database server. The method used in this system is the decision tree method with calculations using the C4.5 algorithm. The C4.5 algorithm is a group of decision tree algorithms. This algorithm has input in the form of training data and testing data. The data used in this study is the historical borrowing data as much as 195 data which is divided into 158 training data and 37 testing data, with 6 predictor attributes. The results of the research on the creditworthiness prediction system using the C4.5 algorithm resulted in 6 rules with an accuracy value of 83.78%. The results of the feasibility prediction from the prospective borrower are a recommendation whether the prospective borrower is eligible or not eligible for a loan.

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