Klasterisasi Karakteristik Pengguna E-Commerce Berdasarkan Profil Pengguna Menggunakan Algoritma K-Prototypes
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Accurate customer segmentation supports more personalized e-commerce marketing. However, the Recency, Frequency, Monetary (RFM) model focuses on transaction history and may not fully capture shopping motivation or the share of a consumer’s spending allocated to e-commerce (Share of Wallet/SoW). This study aims to cluster e-commerce users based on transaction profiles and consumer behavior using the K-Prototypes algorithm. Data were collected from 198 e-commerce users in Palembang, Indonesia. The clustering variables included RFM, SoW, shopping motivation, and product-category preferences, while age category was used for follow-up analysis. The Elbow Method and Silhouette Score supported a four-cluster solution. The resulting personas were High-Value Promo Hunters, Routine Pragmatic Shoppers, Passive Micro-Spenders, and Urgent Big-Ticket Buyers. The Chi-square test indicated a significant association between age category and persona, with Cramér’s V of 0.274. This suggests that age is associated with shopping patterns but does not fully determine consumer profiles. The findings can inform more targeted promotions and user-experience design. The study is limited to 198 respondents from Palembang, so the findings may not represent e-commerce users in other regions.
Author Biographies
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Sriwijaya, Kota Palembang, Provinsi Sumatera Selatan, Indonesia.
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Sriwijaya, Kota Palembang, Provinsi Sumatera Selatan, Indonesia.
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Sriwijaya, Kota Palembang, Provinsi Sumatera Selatan, Indonesia.
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Sriwijaya, Kota Palembang, Provinsi Sumatera Selatan, Indonesia.
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Sriwijaya, Kota Palembang, Provinsi Sumatera Selatan, Indonesia.
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Sriwijaya, Kota Palembang, Provinsi Sumatera Selatan, Indonesia.
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