Application of the FP-Growth Algorithm to Determine Sales Patterns at Najah Mart

This research aims to apply the FP-Growth algorithm at Najah Mart with a focus on identifying significant sales patterns. By recognizing products that are frequently purchased together, this study is expected to help Najah Mart optimize inventory management, enhance customer shopping experiences, and design more efficient marketing strategies. The methodology employed in this study includes collecting sales transaction data and preprocessing to ensure optimal data quality. Subsequently, the FP-Growth algorithm is applied to uncover patterns and associations within the sales data. The analysis focuses on identifying strong product correlations based on customer purchasing patterns. The research findings reveal relevant and significant purchasing patterns, such as combinations of specific products frequently bought together. These insights can be utilized to improve marketing strategies and inventory management. This study not only provides practical benefits for Najah Mart in enhancing operational effectiveness and supporting strategic decision-making but also contributes to the advancement of knowledge by expanding the application of the FP-Growth algorithm in the retail sector, particularly in sales data analysis to support business growth.