Integrasi Naive Bayes dalam Sistem Pendukung Keputusan berbasis Web untuk Kelayakan Kredit Koperasi Simpan Pinjam

Veronika Yusiana Yusefin; Suhirman Suhirman

doi:10.29408/edumatic.v9i3.32629

Authors

Veronika Yusiana Yusefin Program Studi Informatika, Universitas Teknologi Yogyakarta https://orcid.org/0009-0001-2335-7876
Suhirman Suhirman Program Studi Teknologi Informasi, Universitas Teknologi Yogyakarta https://orcid.org/0009-0008-7273-0586

DOI:

https://doi.org/10.29408/edumatic.v9i3.32629

Keywords:

confidence score, creditworthiness, decision support system, naive bayes, savings and loan cooperative

Abstract

assessment, which is still manual and subjective. This study aims to develop a web-based Decision Support System (DSS) using the Naive Bayes algorithm that not only validates the model but also integrates it into an operational system that can be used immediately. The research method used is development using the waterfall model with analysis, design, implementation and testing. The analysis was conducted by applying the Naive Bayes algorithm to generate confidence scores to improve prediction transparency and estimate monthly instalments to assess the repayment ability of prospective borrowers. The dataset included 6,883 historical loan data from 714 members with nine classification features, analysed using the Naive Bayes algorithm and validated using the k-fold cross-validation technique. Results The Naive Bayes classification model achieved 93% accuracy, 0.96 AUC, 94% precision, 96% recall, and a cross-validation score of 0.921 (±0.035). System testing showed that this web-based system functioned well without any errors. In addition, the average response time of this system was 1.95 seconds per input. The implementation of this web-based system successfully overcomes subjective assessment problems, facilitates real-time objective decision-making, and improves transparency and accountability in credit risk management at KSP Tepian Taduh.

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