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All Journal Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences
Andara Rahma Danurisa
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Religion Arts Humanities Economics, Econometrics & Finance Social Sciences

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Customer Clustering Using the K-Means Clustering Algorithm in the Top 5 Online Marketplaces in Indonesia Andara Rahma Danurisa; Jerry Heikal
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 5, No 3 (2022): Budapest International Research and Critics Institute August
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v5i3.6450

Abstract

Tokopedia, Shopee, Lazada, Bukalapak and Orami are 5 marketplaces in Indonesia that focus on shopping activities using applications. The number of customer visits is very volatile so it is difficult to determine customer interest in purchasing a product. The purpose of this study is to identify the characteristics, product categories and merchant in the top 5 online marketplaces in Indonesia using the K-Means Clustering algorithm. There are three variables, namely customer characteristics, product categories, and merchant. Data processing is assisted by the application of SPSS V.25. Loyal customers of marketplace are cluster 10. In addition, the marketplace also has loyal customers in cluster 5. Loyal customers of marketplace the Shopee cluster 8. Then, marketplace also has loyal customers in 6 clusters, including cluster 2, cluster 3, cluster 4, cluster 6, cluster 7, and cluster 9. Loyal customers of marketplace the Lazada cluster 6. However, in cluster 6, the marketplace still excels as marketplace that is often used in cluster 6. The loyal customers of marketplace the Bukalapak cluster 7 However, in cluster 7, marketplace still excels as marketplace that is often used in cluster 7. Orami marketplace loyal customers are cluster 1.
Co-Authors Jerry Heikal