Application of Data Mining Using Methods K-Means Clustering for Clustering Baby Goods Rental Patterns (Case Study: Baby Kha House Store)

Roja' Putri Cintani; Shafa Aurelia Putri; Desti Fitriati

doi:10.34288/jri.v6i2.265

Authors

Roja' Putri Cintani Universitas Pancasila
Shafa Aurelia Putri Universitas Pancasila
Desti Fitriati Universitas Pancasila

(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v6i2.265

Keywords:

Rental Pattern, Data Mining, Clustering, K-Means Clustering

Abstract

A baby item rental business is a practical option for parents who want to fulfill their baby's needs without buying them. Babykhahouse is one of the stores that offer rental services for various kinds of mother, baby, and child equipment. As the volume of data related to rental transactions increases, it is also increasingly difficult to know and understand the rental patterns found at the Babykhahouse store. This research aims to get a rental pattern that can later be a consideration for the store in determining promos and adding stock items. In handling these problems, data mining methods, especially clustering, are applied to group data and classify it based on certain groups. The clustering method used in this research is K-Means Clustering, which generates clusters to find similar rental patterns. In this study, 2 (two) types of clusters were formed, where, based on the 2 (two) clusters, it will be known which products have high and low rental rates. Based on the research, the results are 100 data in cluster 0, or the unsold cluster, and 64 in cluster 1, or the sold cluster. Products included in cluster 1 or in-demand clusters are products with a high level of sales.

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