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All Journal Variance : Journal of Statistics and Its Applications Enthusiastic : International Journal of Applied Statistics and Data Science
Patricia, Mitha
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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PENENTUAN PREMI MURNI DARI DATA KLAIM ASURANSI KENDARAAN RODA EMPAT DENGAN JENIS PERLINDUNGAN COMPREHENSIVE Yulita, Tiara; Patricia, Mitha; Hidayat, Agus Sofian Eka
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 1 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss1page75-86

Abstract

Produk asuransi kendaraan bermotor sudah banyak digunakan oleh banyak orang karena semakin banyak yang membutuhkan untuk meminimalkan risiko yang didapat oleh pihak tertanggung. Sehingga pihak tertanggung perlu membayarkan kewajiban berupa premi serta mengikuti syarat dan ketentuan yang telah disepakati bersama sebelumnya, untuk mendapatkan haknya berupa pembayaran klaim ketika terjadi suatu kejadian yang merugikan tertanggung. Besarnya premi dapat dilihat dari berbagai faktor seperti jenis perlindungannya yaitu Total Loss Only dan Comprehensive, usia kendaraan, riwayat klaim sebelumnya, dan faktor-faktor lainnya. Pada penelitian ini perhitungan yang dilakukan adalah perhitungan premi yang menggunakan data riwayat klaim dari asuransi kendaraan roda empat periode 2020-2022 dengan jenis perlindungan comprehensive dengan menggunakan metode compound model. Dimana data banyak klaim mengikuti model distribusi Negative Binomial, dan data besar klaim mengikuti model distribusi Lognormal. Selanjutnya nilai ekspektasi dari kedua distribusi ini akan dikalikan untuk menentukan premi murni dari asuransi kendaraan roda empat.
Determination Premiums Motor Vehicle Insurance Using Bonus-Malus Optimal Listiani, Amalia; Patricia, Mitha; Yulita, Tiara
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 6 Issue 1, April 2026
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol6.iss1.art2

Abstract

The increasing number of motor vehicles in Sumatera has heightened accident risks, emphasizing the need for motor vehicle insurance to distribute risk between policyholders and insurers. Determining fair and risk-based premium requires consideration of each policyholder’s claim history. This study aimed to determine motor vehicle insurance premiums using the optimal bonus-malus system based on claim data for the minibus category with comprehensive coverage in Sumatera during 2022. The proposed model extended the Bayesian bonus-malus framework by incorporating the trust region reflective (TRR) method for estimating claim severity and the Newton-Raphson method for estimating claim frequency, thereby enhancing parameter estimation accuracy and numerical stability. This approach offers a more equitable and precise premium adjustment mechanism aligned with individual risk levels, contributing to improved risk-based pricing, reduced underwriting losses, and greater transparency for policyholders. The results showed that the claim frequency followed the Poisson-Lindley distribution, while claim severity followed the lognormal-gamma distribution. Based on these models, the premium was computed by multiplying the basic premium by the relative value of the subsequent year and dividing it by the base relative value. Premium decrease in the absence of claims and increase when claims occur.
Co-Authors Hidayat, Agus Sofian Eka Listiani, Amalia Yulita, Tiara