Implementasi Algoritma K-Means Clustering untuk Pengelompokan Pola Permintaan Barang dalam Sistem Manajemen Inventori PT Semen Padang - Ifdal Lisyukri; Melri Deswina (Asosiasi Riset Teknik Elektro dan Informatika Indonesia, 2025)
This research aims to implement the K-Means Clustering algorithm in clustering patterns of goods demand in the inventory management system at PT Semen Padang. With the development of industrial technology and the need for an efficient inventory management system, this research identifies problems faced by the company, such as manual records that are prone to errors and delays. The developed web-based system allows real-time data integration, automation of the goods request process, and analysis of demand patterns using the K-Means algorithm. The results show that the implementation of this system can improve the efficiency of inventory management, minimize recording errors, and support better decision-making in the procurement of goods.