Comparative Analysis of Data Customer Classification with C4.5 Algorithm

Authors

  • Siti Aisyah Universitas Prima Indonesia, Indonesia Author
  • Bondang Johanes Rumapea Universitas Prima Indonesia, Indonesia Author
  • M. Ghifari Halwan Universitas Prima Indonesia, Indonesia Author
  • Denny Hartanto Siahaan Universitas Prima Indonesia, Indonesia Author

Keywords:

Customers, Predictions, Data

Abstract

The problem that often occurs in insurance is the number of customers in arrears of paying premiums. Therefore, a system is needed to classify which prospective customers fall into the eligible group and which customers fall into the unfit group in filing as insurance customers to overcome the problem early. Self-protection is very important for both the safety of individual's life and their valuable assets in today's risky environment. The classification of prospective new insurance customers aims to facilitate the insurer in making decisions in terms of providing insurance coverage. The classification of prospective new insurance customers aims to avoid similar cases by only looking at the rules formed from the decision tree. The decision tree method using the C4.5 algorithm makes extracting information faster and more optimal with a larger data capacity. Therefore, errors caused in decision-making are greatly minimized. 

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Published

2020-12-01

How to Cite

Comparative Analysis of Data Customer Classification with C4.5 Algorithm. (2020). Internetworking Indonesia Journal, 12(2), 3-7. https://internetworkingindonesia.org/index.php/iij/article/view/73