IMPLEMENTASI ALGORITMA K-MEANS UNTUK PENGELOMPOKAN CUSTOMER CHURN DALAM MENENTUKAN STRATEGI PEMASARAN BANK

RAHMADIANA, REVA NUR and Lestarini, Dinda (2025) IMPLEMENTASI ALGORITMA K-MEANS UNTUK PENGELOMPOKAN CUSTOMER CHURN DALAM MENENTUKAN STRATEGI PEMASARAN BANK. Undergraduate thesis, Sriwijaya University.

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Abstract

Customer churn, or the loss of customers, is a major challenge in the banking industry as it can lead to significant financial losses. This study aims to segment customers based on characteristics that influence churn risk using the K-Means algorithm. The data used is secondary data consisting of a bank customer churn dataset with 9,763 records obtained from the Kaggle platform, processed following the CRISP-DM framework. The clustering process was carried out using the RapidMiner application, with performance evaluation using the Davies Bouldin Index to determine the optimal number of clusters (K). The results indicate that the optimal value is achieved when K = 4. Centroid analysis shows that balance and estimated salary are the primary variables forming the clusters. Cluster 1 and Cluster 3 contain the highest number of churned customers. Cluster 1 consists of customers with high balances but low salaries, while Cluster 3 includes customers with both high balances and high salaries. This indicates that a high balance does not necessarily guarantee customer loyalty, and factors such as income play an important role in preventing customer churn. Based on these findings, the recommended strategies include offering low-risk investment products and encouraging customers to allocate idle funds into profitable investment instruments. This study demonstrates that the K-Means method is effective in generating relevant customer segmentation as a foundation for designing more targeted and efficient marketing strategies.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	customer churn, k-means, clustering, bank, segmentasi pelanggan
Subjects:	T Technology > T Technology (General) > T10.5-11.9 Communication of technical information T Technology > T Technology (General) > T351-385 Mechanical drawing. Engineering graphics > T353 General works T Technology > T Technology (General) > T57.6-57.97 Operations research. Systems analysis T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control)
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Reva Nur Rahmadiana
Date Deposited:	22 Jul 2025 02:40
Last Modified:	22 Jul 2025 02:40
URI:	http://repository.unsri.ac.id/id/eprint/179610

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