IMPLEMENTASI ALGORITMA RANDOM FOREST TERHADAP PREDIKSI GOOD LOAN/BAD LOAN KREDIT NASABAH BANK DI JAKARTA

Sultan Farel Syah Reza, . (2023) IMPLEMENTASI ALGORITMA RANDOM FOREST TERHADAP PREDIKSI GOOD LOAN/BAD LOAN KREDIT NASABAH BANK DI JAKARTA. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Credit is the granting (guarantee) of goods or services by one party with money to meet all the needs, wants and aspirations of society, based on increasingly competitive society. Credit risk is the risk of loss associated with the inability and/or unwillingness of the borrower to fulfill its obligation to repay the loan in full on or after the maturity date. In granting credit, banks must identify, manage and ensure credit risk in all products and must go through an appropriate risk management control process. Therefore, a system is needed which is able to predict the credit risk posed by bank customers who are unable to pay off credit loans so that the bank does not lose money. Using data obtained from ID/X to created a machine learning model using the Random Forest algorithm. The output generated from the model that has been made is the classification of bank customers into good loans / bad loans. The classification model obtained will be evaluated using accuracy, precision, recall, and F1-Score values. The best evaluation results are obtained with a model ratio of 70% training data and 30% testing data, achieving an accuracy of 84.32%, precision of 96.79%, recall of 86.44%, and F1-score of 91.3%.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 1910511105] [Pembimbing: Widya Cholil] [Penguji 1: Yuni Widiastiwi] [Penguji 2: Anita Muliawati]
Uncontrolled Keywords: Credit, Risk Management, Machine Learning, Prediction, Random Forest
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Sultan Farel Syah Reza
Date Deposited: 18 Jul 2023 04:23
Last Modified: 27 Jul 2023 06:22
URI: http://repository.upnvj.ac.id/id/eprint/25253

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