Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal The Journal of Information Technology, Computer Science, and Electrical Engineering
Rahma Yuni Simanullang
universitas Pembangunan Panca Budi

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

Found 1 Documents
Search

 1 
Implementation of the K-Means Algorithm on Smart Systems in Grouping Gadget Accessory Purchase Patterns Rahma Yuni Simanullang; Maha Valne Datin Mahfujah Tambunan; Puspita Wanny; Utari; Khairunnisa'; Siska Mayasari Rambe
Journal of Information Technology, computer science and Electrical Engineering Vol. 2 No. 3 (2025): October 2025 - January 2026
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v2i3.232

Abstract

The development of the gadget accessories retail industry demands adaptive marketing strategies to understand consumer behavior patterns more effectively. The main problem faced is the difficulty in grouping customers based on the characteristics of diverse purchasing behaviors. To overcome this, this study aims to implement the K-Means Clustering algorithm in intelligent systems to group customer data of gadget accessories into several groups that have similar purchasing patterns. The K-Means algorithm is used because of its ability to detect patterns and segment based on the similarity of customer attributes through an iterative process until convergence is achieved. The results of the study show that this method has succeeded in forming three main clusters, namely high-value customers with a high purchase frequency and dominance of premium products (C1), customers with low activity who require a special promotional approach (C2), and potential customers with medium activity who have the potential to increase their loyalty (C3). The results of this segmentation prove that the K-Means algorithm is effective in analyzing consumer behavior and can be the basis for data-driven decision-making for a more efficient marketing strategy and product recommendation system in the gadget accessories retail sector.
Co-Authors Khairunnisa' Maha Valne Datin Mahfujah Tambunan Puspita Wanny Siska Mayasari Rambe Utari