Application of Market Basket Analysis with the Apriori Algorithm to Discover Consumer Behavior Patterns Through Transaction Data - Nurdin S.Kom., M.Kom (SCOPUS ID=ID: 57201646662); Muthrib Abdurraafi; Ar-Razi Ar-Razi (Universitas Islam Indragiri, 2026)
Market Basket Analysis (MBA) examines itemsets that are purchased together by customers in a single transaction and is commonly used to analyze consumer behavior patterns based on transaction data. Kaffah Mart is a supermarket that sells daily necessities and household products. However, the store has not yet identified consumer shopping patterns within customers’ shopping baskets. This study aims to identify product association patterns formed through the application of Market Basket Analysis and to determine appropriate marketing strategies based on the generated association rules using the Apriori algorithm. The findings of this research are expected to support the development of more effective marketing strategies, thereby increasing product sales profitability at Kaffah Mart. The research methodology consists of the following stages: data collection, system flowchart design, implementation of the Apriori algorithm, and system deployment. The results show that, for the 3-itemset rules, customers who purchase sweet soy sauce and chili sauce are also likely to purchase instant noodles. Similarly, customers who buy a toothbrush and mouthwash are also likely to purchase toothpaste, with a confidence value of 100%. For the 2-itemset rule, customers who purchase shampoo are also likely to purchase bath soap, with a confidence value of 96.87%.