Penerapan Metode Apriori Untuk Menentukan Best Rule Pada Penjualan Pakaian

The Indonesian fashion industry is experiencing rapid and competitive growth, requiring businesses to be more responsive to consumer needs and preferences. Amezon Store, as a clothing retailer, faces challenges in stock management due to inaccurate forecasts of market demand. This mismatch between the quantity of goods provided and the items in demand by consumers can lead to stockpiling and hamper capital turnover. Therefore, a system capable of analyzing sales transaction patterns effectively is needed. This study applies the Apriori method to find the best rule or optimal purchasing pattern from clothing sales transaction data at Amezon Store. The Apriori method was chosen because of its ability to explore associations between frequently purchased items, thus supporting the decision-making process in inventory planning. The results of this study are expected to provide strategic recommendations to store management in providing products according to market needs, minimizing the risk of planning errors, and improving overall store operational efficiency. Based on the analysis conducted using RapidMiner, the best rule with 2 itemsets is obtained, namely IF buying Manset Then buying Hijab with support 0.0129 (1.29%) and confidence 0.564 (56.4%), the best rule with 3 itemsets is IF buying Long Pants, Pleated Skirt Then buying Distro T-Shirt with support 0.0101 (1.01%) and confidence 1 (100%) the best rule with 4 itemsets is IF buying Shirt, baby clothes, Short Pants Then buying One set with support 0.0101 (1.01%) and confidence 0.9167 (91.67%).