Predicting sales trends for school cooperative using Market Basket Analysis

This study explored applying Market Basket Analysis using the FP-Growth algorithm to boost sales projection and operational proficiency at a school cooperative. It focused on three key problems at SMK Seksyen 3 Bandar Kinrara: manual data administration, lack of forecasting tools, and recurring human mistakes. Historical sales records from the ANGKASA system and spreadsheet files were evaluated employing the CRISP-DM methodology. The FP-Growth algorithm was implemented to discover frequent item sets and purchasing patterns from transactional data. A Power BI dashboard was consequently developed to visualize these patterns and help strategic decisionmaking. The outcomes demonstrated that predictive analytics could improve customer satisfaction, back effective marketing strategies, and optimize inventory control. The study illustrated that data-driven approaches using FP- Growth could significantly contribute to the operation and sustainability of school cooperatives.