Product Sales Grouping Application Design Using K-Means Clustering Algorithm - Sondang, Sondang (Journal of Intelligent Decision Support System (IDSS), 2025)
This research aims to design and develop a product sales grouping application at Minimarket Diky using the K-Means Clustering algorithm. Product grouping based on sales patterns is one of the effective methods to improve marketing strategies, stock management, and more efficient business decision making. By using the K-Means algorithm, product sales data is processed to group products based on the initial number of items, the number sold, and the amount of stock. The designed application is able to identify sales patterns that are difficult to find manually, so as to provide deeper insights to minimarket management. This grouping process helps minimarkets in developing a more targeted product procurement strategy, managing stock more efficiently, and identifying products that have very good sales, good sales, and not good sales. The application development method used in this research is the web-based RAD (Rapid Application Development) method using the PHP programming language and MySQL database