DOI: https://doi.org/10.14710/jfma.v6i1.16505

BONUS MALUS SYSTEM FOR MOTORIZED VEHICLE INSURANCE USING GEOMETRIC DISTRIBUTIONS AND WEIBULL DISTRIBUTIONS

Grisselia Rizky Sevina  -  Mathematics Departement, Ahmad Dahlan University, Yogyakarta, Indonesia, Indonesia
*Joko Purwadi  -  Departrment Mathematics, Univeritas Ahmad Dahlan, Jl. Ringroad Selatan Kragilan Tamanan Banguntapan Bantul, Indonesia, Indonesia

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Abstract
The bonus malus system is one of the systems used to determine the premium amount for the next period based on the claim history of the policyholder. If the policyholder has no claims history or did not file a claim in the previous year, then the policyholder will get a bonus or in other words will get a reduction in the premium rate in the following period. Meanwhile, if the policyholder has a history of claims in the previous year, then the policyholder will be subject to a malus or must pay an increase in the premium rate in the following period. The purpose of this study is to calculate motor vehicle insurance premiums using the classic and optimal bonus malus method which takes into account the frequency of claims with a geometric distribution and the size of claims with a Weibull distribution. The results of this study indicate that the optimal bonus malus system is fairer for policyholders who renew their policies because the premium paid by the policyholder depends on the number of claims and the size of the claim, so that each policyholder will pay a different premium to the number of claims.
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Keywords: Premi, Sistem Bonus Malus, Distribusi Frekuensi Klaim, Distribusi Besar Klaim.

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Section: FUNDAMENTAL MATHEMATICS AND APPLICATIONS
Language : EN
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  2. J. Lemaire, Bonus –Malus systems in Automobile Insurance. New York: Springer Science+Business Media, LLc, 1995
  3. M. Denuit, X. Marchal, S. Pitrebois, and J.-F. Walhin, Actuarial Modelling of Claim Counts. 2007. doi: 10.1002/9780470517420
  4. H. H. Siregar, “Sistem bonus-malus dengan frekuensi klaim berdistribusi binomial negatif dan besaran klaim berdistribusi weibull,” Institut Pertanian Bogor, 2018
  5. M. Z. Rahmah and A. K. Mutaqin, “Uji Kecocokan Distibusi Binomial Negatif untuk Data Frekuensi Klaim Asuransi Kendaraan Bermotor di Indonesia,” Pros. Stat., pp. 187–191, 2021
  6. T. Makhmurian, L. Wachidah, and N. Hajarisman, “Distribusi Binomial Negatif-Lindley pada Data Frekuensi Klaim Asuransi Kendaraan Bermotor di Indonesia,” Statistika, pp. 186–193
  7. S. M. Widiari, “Penaksiran Parameter Dan Statistik Uji Dalam Model Regresi Poisson Inverse Gaussian ( Pig ) Parameter Estimation and Statistical Test in Modeling Poisson Inverse Gaussian Regression ( Pig ),” Tesis SS14 2501, 2016
  8. N. Rachmawati and D. Suhartono, “ANALISIS DAN PERANCANGAN PREMI SISTEM BONUS-MALUS PADA NON-LIFE INSURANCE DENGAN DISTRIBUSI POISSON-EKSPONENSIAL”
  9. L. G. Otaya, “Distribusi Probabilitas Weibull Dan Aplikasinya,” J. Manaj. Pendidik. Islam, vol. 4, no. 2, pp. 44–66, 2016
  10. R. I. Adisti and A. K. Mutaqin, “Perhitungan Premi Murni Pada Sistem Bonus Malus Untuk Frekuensi Klaim Berdistribusi Binomial Negatif Dan Besar Klaim Berdistribusi Weibull Pada Data Asuransi Kendaraan Bermotor Di Indonesia,” J. Gaussian, vol. 10, no. 2, pp. 170–179, 2021, doi: 10.14710/j.gauss.v10i2.30084
  11. L. J. Bain and M. Engelhardt, Introduction To Probability and Mathematical Statistics, Second. Brooks/Cole, Cengage Learning, 1992
  12. L. Susanti, “Sistem bonus malus dengan frekuensi klaim berdistribusi geometrik dan ukuran klaim berdistribusi weibull,” 2015

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