KLASIFIKASI CALON DATA NASABAH ASURANSI KESEHATAN MENGGUNAKAN ALGORITMA C4.5

BONDANG JOHANES RUMAPEA, MHD GHIFARI HALWAN, DENNY HARTANTO SIAHAAN (2022) KLASIFIKASI CALON DATA NASABAH ASURANSI KESEHATAN MENGGUNAKAN ALGORITMA C4.5 , SKRIPSI, UNIVERSITAS PRIMA INDONESIA

ABSTRAK

The problem that often occurs in insurance is the number of customers who are in arrears in paying premiums, therefore a system is needed that can classify which prospective customers fall into the eligible group and which customers fall into the unfit group in filing as insurance customers, so that the insurer can overcome the problem early on. Self-protection, both life and valuable assets, is very important for the lives of individuals in today's risky environment. The classification of prospective new insurance customers aims to make it easier for insurers to make decisions in terms of providing insurance coverage. With the classification of prospective new insurance customers, if there is a problem with the same case, the insurance party just has to look at the rules that have been formed from the resulting decision tree. With the decision tree method using the C4.5 algorithm, it is expected that the process of extracting information is faster and optimal with a larger data capacity, so that errors caused in decision making are more minimized.

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