Profit-Based HUI-Miner for Discovering Consumer Shopping Patterns in a Retail Store - I Putu Noven Hartawan; I Gede Sudiantara; Ni Kadek Bumi Krismentari; Gede Rudiharta Pratama Giri; I Made Dwi Putra Asana (Yayasan Sraddha Panca Widya Nusantara, 2026)
Retail transaction logs often reveal products that are frequently purchased together, but frequency alone does not show their economic contribution. This study applies a profit-oriented High Utility Itemset approach using HUI-Miner to identify valuable shopping patterns at YSL Grocery Store. The analysis followed CRISP-DM on 266,394 sales records from 2022. After attribute selection and missing-value removal, 251,225 records containing transaction, item, quantity, and price were processed. Item utility was represented by quantity multiplied by selling price, while the mining stage used a minimum utility of IDR 5,000,000, minimum support of 2%, and minimum confidence of 10%. Positive associations were retained when lift exceeded 1. The procedure produced 248 frequent itemsets, 77 confidence-qualified rules, 64 positive-lift rules, and 23 rules that satisfied all criteria. The strongest association linked two Sedaap instant-noodle variants with a lift of 3.26. The findings also show that support is not proportional to total utility: some cross-category combinations generated substantially greater utility despite lower occurrence. Therefore, retail decisions should combine utility, support, confidence, and lift when prioritizing shelf placement, bundles, promotions, and stock.