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All Journal Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences
Naufal Ifsan Al-Azhar
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Religion Arts Humanities Economics, Econometrics & Finance Social Sciences

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Implementation of Data Mining to Determine Payment Delays for Mall Shopping Center Tenants Using K-Means Clustering Method Ary Suryo Bimantoro; Rafi Athallah; Naufal Ifsan Al-Azhar; Nilo Legowo
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.v5i3.6080

Abstract

With the rapid growth of their business, XYZ Company wanted to utilize their data to the upmost maximum. One of the methods to make the most out of their data is to do data mining. With the available data and RapidMiner as processing tool, researcher can build a clustering model to determine the accuracy of payment for their clients. It was discovered that the dataset can be divided into 3 clusters, namely on time, late, and very late. From the cluster discovered, a suggestion can be made on how to handle the payment for each group, so that there will be no more late payment in the future by applying a penalty for the tenants that are late paying their bills.
Co-Authors Ary Suryo Bimantoro Nilo Legowo Rafi Athallah