REGRESI LOGISTIK BAYESIAN DAN ALGORITMA C4.5 DALAM KLASIFIKASI RISIKO PENGGUNAAN BPJS KESEHATAN KOTA MADIUN

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%.

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Publication Details

Journal
Jurnal Lebesgue Jurnal Ilmiah Pendidikan Matematika Matematika dan Statistika
Published
2024-12-12
DOI
https://doi.org/10.46306/lb.v5i3.814
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
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article

REGRESI LOGISTIK BAYESIAN DAN ALGORITMA C4.5 DALAM KLASIFIKASI RISIKO PENGGUNAAN BPJS KESEHATAN KOTA MADIUN

Muhammad Qolbi Shobri, Rhavida Anniza Andyani, Maikel Jeksen
Jurnal Lebesgue Jurnal Ilmiah Pendidikan Matematika Matematika dan Statistika
Data Mining and Machine Learning Applications
article

REGRESI LOGISTIK BAYESIAN DAN ALGORITMA C4.5 DALAM KLASIFIKASI RISIKO PENGGUNAAN BPJS KESEHATAN KOTA MADIUN

Muhammad Qolbi Shobri, Rhavida Anniza Andyani, Maikel Jeksen
article en

Abstract

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%.

Jurnal Lebesgue Jurnal Ilmiah Pendidikan Matematika Matematika dan StatistikaVol. 5(3)
Universitas Merdeka Madiun (ID)
Openalex Percentile: Top 61%
Data Mining and Machine Learning Applications
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REGRESI LOGISTIK BAYESIAN DAN ALGORITMA C4.5 DALAM KLASIFIKASI RISIKO PENGGUNAAN BPJS KESEHATAN KOTA MADIUN — Muhammad Qolbi Shobri, Rhavida Anniza Andyani, et al. · Jurnal Lebesgue Jurnal Ilmiah Pendidikan Matematika Matematika dan Statistika (2024) | TGRS Research Map | TGRS