Penerapan K-Means Clustering Berbasis Model LRFM Untuk Segmentasi Pelanggan Pada PT Fazri Putra Mandiri - Nuraini, Nabilah Hasna; Umaidah, Yuyun; Maulana, Iqbal (Peneliti.net, 2026)
The opportunities of shipping service business nowadays has led to an intense competition between businesses which has an impact on decreasing revenue for PT Fazri Putra Mandiri. The company must plan for marketing strategies and provide best services for potential and loyal customers to retain customers. To achieve this goal, customer segmentation is conducted to identify groups of customers with distinct characteristics. By understanding these characteristics, companies can develop more effective strategies aimed at customers who demonstrate high potential value and loyalty. The LRFM model is an approach in the marketing field that can be used in the clustering process to analyze potential and loyal customer segments. In this research, customer segmentation is carried out using the K-means clustering algorithm based on the LRFM model (Length, Recency, Frequency, Monetary). Determination of the k value using the Elbow method resulted in three best clusters with a silhouette score of 0.572. Cluster 0 consists of 611 customers, Cluster 1 consists of 600 customers, and Cluster 2 consists of 400 customers. The segments derived from the analysis are classified as New Customers, Lost Customers, and Loyal Customers.