Abstract

The presence of insurance can provide coverage for all risks that occur for owners or motorists. Insurance will provide various forms of coverage in accordance with their respective products, so that vehicle owners or drivers will get protection, benefits or compensation for losses from various risks that occur above by buying an insurance policy of course. In Indonesia, motor vehicle insurance is included in the group of liability insurance. One of these insurance coverages is third-party legal liability. This is a protection against liability or third party legal responsibility or Third Party Liability, because the benefits provide protection against claims and losses experienced by third parties, in this case victims involved in accidents. Insurance premiums that can be provided by insurance companies to policyholders can be calculated based on the distribution model of claim frequency and claim size. Claim frequency is the number of insurance claims that occur in one period. Claim frequency data is often overdispersed. Poisson mixture distribution is often used as an alternative method for modeling claim frequency data when overdispersion occurs. This thesis will discuss the Poisson-Aradhana distribution modeling of motor vehicle insurance claim frequency data in Indonesia in 2019. The maximum likelihood estimation method is used to estimate the parameters of the Poisson-Aradhana distribution. The fit test used in this study is the Chi-Square test. The research material used is secondary data on the frequency of motor vehicle insurance claims recorded by PT. X from 8 categories and 3 regions in 2019. The results of the application of the Poisson-Aradhana mixed distribution on the frequency data of motor vehicle insurance claims for TPL coverage with comprehensive coverage at PT. X in 2019, most of the claim frequency data comes from a population with a Poison-Aradhana mixed distribution except for claim frequency data in category 1 region 3 and category 4 region 2

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