Segmentasi pelanggan penjualan online menggunakan Metode K-Means Clustering

Hafidz Ardana, Candra, Khoyum, Adlian Aldita Alif Aisyah Ainur and Faisal, Muhammad ORCID: https://orcid.org/0000-0003-4884-7254 (2024) Segmentasi pelanggan penjualan online menggunakan Metode K-Means Clustering. JISKA (Jurnal Informatika Sunan Kalijaga), 9 (1). pp. 1-9. ISSN 2527 – 5836

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Abstract

Customer segmentation is an essential strategy in the online selling industry to understand customer preferences and behavior. This article proposes applying the K-means clustering method in online sales customer segmentation. The method used is the descriptive method. The steps of the research method include literature studies and data processing to be analyzed using the K-means clustering method. The K-means clustering method is then applied to customer data to group it based on relevant attributes. The segmentation results are evaluated and scored using the clustering evaluation metric. The main objective is to explain the use of the K-means clustering method in online sales customer segmentation, focusing on obtaining more profound insights into customer behavior. Efficient customer segmentation allows companies to target customer groups more precisely and efficiently. This article provides practical insights and guidance for e-commerce companies in implementing customer segmentation using K-means clustering to increase efficiency in targeting segmented customers.

Item Type:	Journal Article
Keywords:	Customer Segmentation; Online Sales; E-Commerce; K-means Clustering; Clustering
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0806 Information Systems
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Muhammad Faisal
Date Deposited:	17 May 2024 14:23

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