Rancang Bangun Sistem Data Mining Untuk Analisis Tren Penjualan Dengan Algoritma K-Means (Studi Kasus: Toko Mainan Berkah 3R)

Ryan Sugiarto (universitas pamulang)
Nanang (Universitas Pamulang)

OKTAL : Jurnal Ilmu Komputer dan Sains
Vol 5 No 03 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains

This study aims to analyze sales trends and classify products based on their sales performance using the K-Means clustering method at Toko Mainan Berkah 3R. The main issue addressed is the absence of a structured data analysis system to support decision-making related to stock management and marketing strategies. The research utilized sales transaction data from a specific period, which underwent data cleaning and normalization before the clustering process. The K-Means algorithm was applied by defining three clusters to categorize products into high, medium, and low sales groups. The findings indicate that the clustering results provide a clearer overview of product distribution and sales patterns, enabling store owners to prioritize inventory management and evaluate low-performing products. Therefore, the implementation of the K-Means method proves effective in supporting data-driven decision-making in retail businesses.