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All Journal JT-IBSI (Jurnal Teknik Ibnu Sina)
Andikha
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Engineering

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Segmentasi Pelanggan Klinik Dokter Hewan Berbasis Algoritma K-Means dan Model RFM Rafi Dio; Meylia Vivi Putri; Dwila Sempi Yusiani; Andikha; Berta Erwin SLAM; Adyk Marga Raharja; Rifaldi Herikson
Jurnal Teknik Ibnu Sina (JT-IBSI) Vol. 10 No. 1 (2025): JT-IBSI (Jurnal Teknik Ibnu Sina)
Publisher : Fakultas Teknik Universitas Ibnu Sina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jt-ibsi.v10i1.1180

Abstract

This study aims to segment customers of a veterinary clinic using a combination of Recency, Frequency, Monetary (RFM) analysis and the K-Means clustering algorithm. Transactional data from December 2024 to April 2025 were processed to generate key customer features, followed by min-max normalization to ensure comparability across variables. The segmentation was conducted in AI Studio 2025, with cluster quality evaluated using cluster distance performance and Davies-Bouldin Index. The analysis resulted in four distinct customer segments: the majority were passive customers with low transaction frequency and spending, while a smaller group showed high purchasing activity and made a significant economic contribution. This study demonstrates the effectiveness of automated data mining tools in uncovering meaningful customer profiles in a veterinary service context. The results provide a practical basis for targeted marketing, customer retention strategies, and service improvement in veterinary clinics. This approach offers valuable insights for data-driven decision making and represents a novelty for veterinary service management in Indonesia. Keywords: Customer Segmentation, RFM Analysis, K-Means Clustering, Veterinary Clinic, Data Mining.
Co-Authors Dwila Sempi Yusiani Marga Raharja, Adyk Meylia Vivi Putri Rafi Dio Rifaldi Herikson SLAM, Berta Erwin