Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Sistem Komputer dan Informatika (JSON)
Muhammad Tegar Juleo Wicaksana Juleo
Universitas Muria Kudus
Computer Science & IT Control & Systems Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Customer-Centric Retail Analytics Using RFM Segmentation and Segment-Level FP-Growth for Product Recommendation Muhammad Tegar Juleo Wicaksana Juleo; Anteng Widodo; Andy Prasetyo Utomo
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 8 No. 1 (2026): September (2026)
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v8i1.10090

Abstract

Retail transaction data are often used only for sales recording, leaving customer value and product affinity disconnected from managerial decisions. This study develops a web-based retail analytics framework that integrates RFM, K-Means, and global and segment-level FP-Growth to generate product-bundle, availability-check, and shelf-placement recommendations for SRC Inka Jaya. The analysis used 198,879 non-tobacco transaction lines representing 67,284 invoices, 2,565 products, and 1,257 identified customers from 1 January 2025 to 22 June 2026. RFM variables were transformed using , standardized, and evaluated for k=2–6. A four-cluster solution was selected as a trade-off between statistical quality and managerial usefulness, with a silhouette score of 0.371 and a Davies-Bouldin index of 0.934. Champion customers represented 28.48% of identified customers but contributed 54.35% of their monetary value. The primary FP-Growth scenario produced 963 rules, including 188 global and 775 segment-level rules, consolidated into 86 bundles, 46 availability-priority products, and 69 shelf-placement recommendations. Temporal validation achieved a 60.61% rule-match hit rate. Combining store-wide and segment-specific patterns produced more contextual recommendations and supported traceable delivery through an active-dataset dashboard.
Co-Authors Andy Prasetyo Utomo Anteng Widodo