ANALISIS SEGMENTASI PENGUNJUNG MENGGUNAKAN K-MEANS CLUSTERING BERDASARKAN MODEL RFM: STUDI KASUS PEGASUS KARTING CABANG PLUIT VILLAGE

Abstract

The experience-based entertainment industry, such as indoor karting, faces challenges in understanding customer behavior through a data-driven approach. Pegasus Karting at Pluit Village Mall recorded 1,833 transactions from 892 unique customers during October-December 2025 via its Smart TAG cashier system, yet this data remained underutilized for strategic decision-making. This study aims to implement K-Means Clustering based on the RFM (Recency, Frequency, Monetary) model to generate customer segments, analyze the characteristics of each segment, and formulate Customer Relationship Management (CRM) strategy recommendations and operational efficiency improvements. The methodology encompasses RFM value computation, Min-Max normalization, optimal cluster determination using the Elbow Method and Silhouette Score, and K-Means execution with k-means++ initialization. Results indicate that k = 3 is the optimal configuration, yielding a Silhouette Score of 0.5453 (above the 0.5 threshold), thus rejecting H₀ and accepting H₁. Segmentation produced two main groups: Champions (655 customers, 73.4%) with an average Recency of 24.25 days, Frequency of 2.2 visits, and Monetary of IDR 333,829, contributing 76.7% of total revenue; and Lost Customers (237 customers, 26.6%) with an average Recency of 77.83 days, contributing 23.3% of revenue. These findings serve as the basis for loyalty retention strategies for the Champions segment and win-back campaigns for Lost Customers.