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Comparative Analysis of K-Means and K-Medoids Algorithms for Product Sales Clustering and Customer Yosia; Siregar, Bakti
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4053

Abstract

In today's rapidly evolving business landscape, effective product management is crucial for maintaining a company's competitive advantage. Comprehensive analysis is essential for providing insights that inform strategic business development decisions. This study examines the sales data of PT XYZ from July 2020 to May 2024 using the K-Medoids algorithm, with dimensionality reduction applied through Principal Component Analysis (PCA). The clustering results identified three customer segments: Cluster 1 with 46 customers, Cluster 2 with 76 customers, and Cluster 3 with 62 customers. For product segmentation, four clusters were identified: Cluster 1 with 52 products, Cluster 2 with 12 products, Cluster 3 with 20 products, and Cluster 4 with 53 products. The K-Medoids algorithm demonstrated superior performance compared to K-Means in terms of cluster separation and interpretability, with visualizations that enhance the understanding of customer and product distributions. This research aids the company in enhancing customer satisfaction, optimizing inventory, and increasing profitability.
Community Service Data Visualization at PT Surya Data Infocreasi in Retail Companies X, Y and Z Yosia; Januaviani, Trisha M.A
Jurnal Pengabdian Masyarakat Bestari Vol. 3 No. 2 (2024): February 2024
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/jpmb.v3i2.8050

Abstract

This Community Service (PKM) is carried out at PT Surya Data Infokreasi with a focus on data visualization using the Power BI platform. This service aims to increase the efficiency of understanding customer data and the company's business performance. Design and implement interactive reports using various Power BI visualizations such as graphs, maps, and dynamic tables. Interactive slicers and filters are applied to give users flexibility in exploring data in greater depth or detail. The main focus of visualization is sales analysis, customer trends, and inventory monitoring. Selection of performance metrics including total sales, customer returns, and profit analysis. The implication of this service is to help facilitate understanding of data in terms of patterns, trends and information contained in the data.