Laptop Purchasing Patterns Using the FP-Growth Algorithm at Harapan.Com Store Kutacane, Southeast Aceh - Syahrijal Alas Pagan; Derani Alfira; Cut Fitri Ani; Izzati Hanisa; Sinar Pika (STMIK Methodist Binjai, 2026)
Sales records can be transformed into purchasing patterns that support product bundling, inventory planning, and contextual accessory recommendations. This study applies FP-Growth to discover frequent itemsets and association rules for the laptop-sales context of Harapan.Com in Southeast Aceh. Because actual transaction history was not supplied, the analysis uses 100 deterministic simulated transactions comprising four laptop brands and seven complementary products. The process includes item normalization, frequency counting, FP-Tree construction, conditional pattern bases, frequent-itemset mining, and rule generation. Minimum support is set at 15%, confidence at 60%, and lift above 1. The simulation yields 38 frequent itemsets and 30 qualifying rules. Notable patterns include Cooling Pad to Headset with 18% support, 78.26% confidence, and 2.90 lift, and Extended Warranty to Office License with 23% support, 85.19% confidence, and 2.13 lift. These patterns suggest gaming, productivity, and accessory-recommendation bundles. The study contributes a transparent and reproducible workflow while explicitly separating simulated results from real transaction evidence.