Analisis Persediaan Barang Menggunakan Clustering K-Means Pada PT. Brothersindo Saudara Sejati - Rosi Kusuma Serli; Imron Imron; Bambang Wijonarko; M. Sinta Nurhayati (TEKNIKA, 2023)
Product sales at PT. Brothersindo Brother Sejati experiences many variations. To maintain business growth, companies must maintain an inventory of goods needed by customers so that these goods can be met so that there is no failure to meet customer needs. Inventory carried out inaccurately will result in goods being stored that are too high and uneconomical, due to shortages or excesses of certain products. This research aims to group sales products sold at PT. BrotherIndo Brother Sejati is divided into 2 (two) clusters to find out the products that sell the most so the number of stock requests must be increased, and the products that sell the least so the number of stock requests must be reduced. The method used in this research is the K-Means method which is one of the best and most frequently used methods in clustering algorithms where K-Means searches for the optimal partition of the data by minimizing the criterion of the sum of squared errors with an optimal iteration procedure. Based on the research results of inventory analysis using the K-Means method, it can be concluded that data grouping provides significant benefits for companies in managing their inventory. With information about the best-selling and least-selling items, companies can avoid product accumulation in the warehouse and maintain an organized layout.