Application Of Market Basket Analysis For Sales Transaction Analysis Using Association FP-Growth Algorithm - Wini Audiana; Tahyudin, Imam (LPPM Universitas Potensi Utama, 2025)
In an increasingly competitive business world, leveraging transaction data has become crucial for understanding consumer behavior and designing effective marketing strategies. This study aims to apply the FP-Growth algorithm in Market Basket Analysis (MBA) to identify consumer purchase patterns at KS Swalayan. The data analyzed in this research was taken from sales transactions that occurred during October 2024, with key attributes including product codes, product names, quantity, unit price, total price, and discounts. This research follows the Knowledge Discovery in Databases (KDD) framework, which includes stages of data selection, data cleaning, transformation, pattern collection, and result evaluation. The research findings indicate that the FP-Growth algorithm successfully identified significant associative relationships between various products. For example, there is a relationship between the products