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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi)
Pramana, Made Dimas Aldi Dwi
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Computer Science & IT

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Medical Costs Estimation Using Linear Regression Method Dwikasari, Ni Made Dita; Sutramiani, Ni Putu; Putri, Komang Sri Yanisa; Kusuma, Nyoman Tri Rahaditya; Pramana, Made Dimas Aldi Dwi; Darma, I Wayan Agus Surya
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 11 No 3 (2023): Vol. 11, No. 3, December 2023
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2023.v11.i03.p03

Abstract

Medical costs are a significant issue in the health sector. High healthcare cost lead to the need to anticipate financial risks for individuals and insurance providers. Therefore, medical cost data analysis is necessary to estimate future medical expenses. This research implements data mining techniques using Simple and Multiple Linear Regression methods to estimate medical costs. The dataset used consists of insurance claim data obtained from Kaggle, which includes attributes such as age, gender, body mass index, number of children, smoking habits, region, and medical charges. The research findings that Multiple Linear Regression outperforms Simple Linear Regression in estimating the provided dataset, with R2 value of 80% and lower ?? MSE and MAE values than Simple Linear Regression. The application of linear regression in insurance claim data analysis can provide significant benefits for patients, hospitals, and insurance providers. Overall, this research highlights the effectiveness of data mining techniques, specifically linear regression, in estimating healthcare costs.
Co-Authors Dwikasari, Ni Made Dita I Wayan Agus Surya Darma Kusuma, Nyoman Tri Rahaditya Ni Putu Sutramiani Putri, Komang Sri Yanisa