RANCANG BANGUN SISTEM PREDIKSI KETERSEDIAAN BARANG MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING UNTUK MENINGKATKAN EFISIENSI STOK PADA UMKM ALYA FOTOCOPY - Bangkit Sunarno; Maulana Ardhiansyah (LPPM Politeknik Pratama Kendal, 2026)
This study aims to design and build a web-based inventory availability prediction system using the K-Means Clustering algorithm to improve stock management efficiency at Alya Fotocopy MSME. The system processes historical inventory data to classify items into fast-moving, medium-moving, and slow-moving categories. The results show that the K-Means algorithm can assist business owners in making stock control decisions more accurately and efficiently. Keywords: K-Means, Inventory Prediction, Data Mining, MSME