Application of Data Mining to Analyze Sales Patterns of Merchandise in MSMEs in Sait Buttu Saribu Tourism Village Using the Apriori Algorithm

The development of information technology in the era of globalization has brought significant changes to various aspects of life, including business and trade activities. Information is a crucial component in supporting fast, precise, and accurate decision-making, both at the operational and strategic levels. This study aims to apply the Apriori algorithm to analyze the sales patterns of MSMEs in the Sait Buttu Saribu Tourism Village and to develop a web-based system that can support business decision-making. MSMEs play a vital role in the local economy, but sales data utilization is still suboptimal. Sales transaction data from 2023–2024 from 57 active MSMEs were used as the research object. The research method used is Research and Development (R&D) with the system development using the Waterfall method. The Apriori algorithm was applied to find association patterns between products based on support and confidence values. The results show that the Apriori algorithm is able to identify product combinations that are frequently purchased together so that they can be utilized for sales strategies such as product bundling, product arrangement, and inventory control. The developed system is expected to help MSMEs manage sales data more effectively and support data-driven decision-making. Therefore, this study applies the Apriori algorithm to analyze the sales patterns of MSME merchandise in Sait Buttu Saribu Tourism Village and builds a web-based system as a decision- making tool.