Nadhira Jasmine Nurrahma, . (2025) IMPLEMENTASI K-MEANS CLUSTERING DALAM ANALISIS RISIKO KREDIT NASABAH BERMASALAH DI PT. BPR SUPRADANAMAS. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Problematic loans are a major challenge for PT. BPR Supradanamas in managing credit risk. This study aims to segment customers of PT. BPR Supradanamas based on their credit payment behavior using the K-Means algorithm. The clustering is conducted to categorize customers into three risk levels: minimal risk, controlled risk, and uncontrolled risk. The process includes data preprocessing, normalization, and determining the optimal clusters using the Elbow Method and Silhouette Score. Clustering results indicate differences customer characteristics across cluster in terms of outstanding amounts, delay duration, and payment success rates. The optimal number of clusters was determined to be three based on the Elbow Method, indicated by a significant drop in the Sum of Squared Errors (SSE). Visualization and recommendation system developed using the Streamlit framework display the clustering of customer credit risk from 2022–2024. The study help company understand customer risk clusters. With clustering, company can minimize problematic credit risks, identify eligible customers for new credit, and optimize future credit strategies.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2110512138] [Pembimbing 1: Ruth Mariana Bunga Wadu] [Pembimbing 2: Catur Nugrahaeni Puspita Dewi] [Penguji 1: Ika Nurlaili Isnainiyah] [Penguji 2: Bambang Tri Wahyono] |
| Uncontrolled Keywords: | K-Means, Credit Risk, Payment Behavior, Non-Performing Loans. |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1) |
| Depositing User: | NADHIRA JASMINE NURRAHMA |
| Date Deposited: | 07 Aug 2025 01:25 |
| Last Modified: | 07 Aug 2025 01:25 |
| URI: | http://repository.upnvj.ac.id/id/eprint/37505 |
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