Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal OKTAL : Jurnal Ilmu Komputer dan Sains
Ryan Sugiarto
universitas pamulang
Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Rancang Bangun Sistem Data Mining Untuk Analisis Tren Penjualan Dengan Algoritma K-Means (Studi Kasus: Toko Mainan Berkah 3R) Ryan Sugiarto; Nanang
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 03 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

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.
Co-Authors Nanang Nanang