REGRESI LOGISTIK BAYESIAN DAN ALGORITMA C4.5 DALAM KLASIFIKASI RISIKO PENGGUNAAN BPJS KESEHATAN KOTA MADIUN - Shobri, Muhammad Qolbi; Andyani, Rhavida Anniza; Jeksen, Maikel (Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, 2024)
Social Security Agency for Health (SSAH) Madiun branch office incurred healthcare costs amounting to Rp1.5 trillion in 2023. Seeing the large amount of expenses incurred, it shows that the people of Madiun city largely trust SSAH with their health insurance. In the cost claim process, not all claims are accepted, which is caused by several factors, such as the type of work and medical records. This research will examine the risk and opportunities of utilizing SSAH insurance services in Madiun city. The methods used are Bayesian Logistic Regression and the C4.5 Algorithm. The purpose of this research is to identify the risk factors for utilizing SSAH services in Madiun City and to determine the best methods for classification. This research is expected to assist the SSAH in Madiun City in understanding the risks for SSAH participants in using insurance services and to serve as a reference for other researchers in using the best methods for classification. The research results show that medical history and gender have an influence on the risk of utilizing SSAH services in the city of Madiun. The best method in that classification is the C4.5 Algorithm method with an average accuracy rate of 66.82%.