Product Sales Analysis based on sales level using the K-Means Clustering method - Kinasih, Aisha Bethary; Christianto, Paminto Agung; Amalia, Nurul (Journal of Artificial Intelligence and Software Engineering, 2026)
Micro, Small, and Medium Enterprises (MSMEs) play a highly strategic role in driving Indonesia’s economic growth. Nevertheless, most business actors have not yet utilized digital technology to its full potential. One such example is Toko Nabila Daster, which recorded 475 sales transactions during the period of January–June 2025, but has not conducted an analysis to identify products with high, medium, or low sales levels. This situation may result in stock accumulation and ineffective promotional strategies. The objective of this study is to group products based on their sales levels using the K-Means Clustering method. The optimal number of clusters is determined through the Elbow Method, while the quality of clustering is assessed using the Davies-Bouldin Index (DBI). The results of the analysis indicate the formation of product clusters that distinguish best-selling, moderately selling, and low-selling categories. These findings are expected to serve as a foundation for business decision-making, particularly in designing promotional strategies and managing inventory more efficiently.