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All Journal Theta: Journal of Statistics
Zilda Ainun Tazkia
Universitas Sultan Ageng Tirtayasa

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Customer Segmentation Analysis of Maxim Application Based on RFM Model and K-Means Clustering as the Basis for Marketing Strategy Zilda Ainun Tazkia; Zahra Mahendra Putri; Atira Keisha Belva Armanda Fadhilla; Atia Sonda; Aulia Ikhsan; Putri Dina Sari
Theta: Journal of Statistics Vol 2, No 1 (2026): Available Online in March 2026
Publisher : Faculty of Engineering, Univesitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/tjs.v2i1.39360

Abstract

The rapid development of online transportation services requires a data-driven understanding of customer behavior. This study aims to segment Maxim application customers using the Recency, Frequency, and Monetary (RFM) model combined with the K-Means clustering method among students of the Faculty of Engineering, Sultan Ageng Tirtayasa University. This research employs a descriptive quantitative approach with a sample of 100 respondents. The optimal number of clusters was determined using the Elbow method, resulting in four customer segments: Inactive Customers, Occasional Customers, Loyal Customers, and Priority Customers. The segmentation analysis was conducted separately for Maxim Bike and Maxim Car services. The results indicate that the Priority cluster has the highest transaction frequency and expenditure value despite consisting of relatively few customers, while the Inactive cluster shows the lowest level of transaction activity. In the Maxim Bike category, the Priority cluster represents the largest proportion of customers and shows the most recent transaction activity. In addition, the distribution of study programs indicates the dominance of Statistics students in the Loyal and Priority clusters across both service categories. Descriptive statistical analysis further shows that respondents' perceptions of Maxim services fall into the positive category, with average indicator scores above 3.20.
Co-Authors Atia Sonda Atira Keisha Belva Armanda Fadhilla Aulia Ikhsan Putri Dina Sari Zahra Mahendra Putri