Optimization of Kaayana Store Inventory through Transaction Pattern Analysis Using the Apriori Algorithm - Suhardiansyah, Suhardiansyah; Muhammad Iqbal (Journal Of Data Science, 2025)
This study aims to optimize inventory management at Kaayana Store by analyzing sales transaction patterns using the Apriori algorithm. The transaction data collected shows that products with the codes ACC (accessories) and BJU (clothing) dominate purchases, accounting for 71.4% of total transactions. The analysis results identify a strong relationship between these products, which are frequently purchased together by consumers. Based on these findings, Kaayana Store needs to ensure the availability of ACC and BJU stocks to meet high demand, avoid stockouts, and improve operational efficiency. Proposed inventory management strategies, such as more precise product placement and bundling promotions, are expected to enhance customer satisfaction and support the sustainability of Kaayana Store's business