Implementasi Data Mining pada Penjualan Barang dengan Tekhnik K Means - Permata Sari, Dian; Buana, Wira; Febri Mayang Sari, Mike (Pustaka Galeri Mandiri, 2025)
One of the data mining techniques is the K-Means Clustering Algorithm, which is a method that partitions data into one or more clusters or groups. The K-Means algorithm groups data that have different characteristics into other groups. In this study, the K-Means algorithm is grouped into three groups, namely best-selling items, sold items, and less sold items. The grouping is based on the variables of item name, initial stock, and final stock, the case study of which is at the Eli daily shop based on the level of best-selling sales in the last month, namely January 2025. The purpose of using the K-Means algorithm technique is to implement sales strategies and provision of stock of goods that aim to reduce the risk of loss. With this research, it is hoped that it can become a marketing strategy that can provide profit and reduce the risk of sales losses.