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All Journal Informatik : Jurnal Ilmu Komputer
Erlan Fauzi Reza
Universitas Pembangunan Nasional Veteran Jakarta
Computer Science & IT

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Sales Information System Using FP-Growth Algorithm Based on Consumer Purchasing Patterns Erlan Fauzi Reza; Iin Ernawati
Informatik : Jurnal Ilmu Komputer Vol 22 No 1 (2026): April 2026
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v22i1.12456

Abstract

The advancement of technology has driven businesses to innovate digitally to improve operational efficiency and effectiveness, including in the food and beverage industry. Two Much Coffee & Roastery is one of the cafes that still operates in a semi-digital manner, recording transactions manually using Microsoft Excel. The cafe faces challenges in optimizing sales strategies, particularly in implementing cross-selling strategies, as there is no system that provides automatic product recommendations. This study aims to implement data mining techniques using the FP-Growth algorithm to identify consumer purchasing patterns from historical transaction data. The algorithm was applied with a minimum support of 0.01 and a lift of 1.0, resulting in 30 association rules. These rules were integrated into a web-based system used by the cashier to support cross-selling strategies. The system not only records transactions but also provides product recommendations based on previous purchasing patterns, which is expected to effectively and efficiently increase the cafe’s sales.
Co-Authors Iin Ernawati