• DocumentCode
    3581276
  • Title

    Predicting bad utility consumers in Malaysia

  • Author

    Hoe, Alan Cheah Kah ; Dhillon, Jaspaljeet Singh

  • Author_Institution
    Dept. of Inf. Syst., Univ. Tenaga Nasional, Kajang, Malaysia
  • fYear
    2014
  • Firstpage
    234
  • Lastpage
    237
  • Abstract
    In many organizations, especially in most utility companies including Company X, revenue collection is a major issue when customers face difficulties in paying their utility bills before the deadline. There are many reasons for this problem but it becomes a serious financial issue for the organizations when the cumulative amount of bad debts reached a staggering figure. This paper reports a study of this issue for Company X involving its customers based in Bangi and Kajang, totaling upto 1,525 customers. The study is conducted to identify the factors of customers who would default payment of their bills. The identification of such factors is important to enable Company X to identify these customers and implement the necessary measures to mitigate the problem. The CRISP-DM (Cross-Industry Standard Process for data mining) model was employed in conducting the study. The results provide an intial understanding of the issue and the solution model generated could be used to resolve the issue for other areas in Malaysia.
  • Keywords
    data mining; financial data processing; CRISP-DM; Malaysia; bad utility consumer prediction; cross-industry standard process for data mining model; financial issue; revenue collection; Companies; Data mining; Data models; Information technology; Market research; Predictive models; CRISP-DM; data mining; data modeling clustering; data preparation; utility consumers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Multimedia (ICIMU), 2014 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICIMU.2014.7066636
  • Filename
    7066636