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THE APPLICATION OF LINEAREMPIRICALBAYESIAN (LEB) METHOD TO DETERMINETHEPREMIUM IN MOTOR VEHICLE INSURANCE

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dc.contributor.author TAMAELA, FALAH RAHMADIYAN
dc.date.accessioned 2025-04-17T01:32:51Z
dc.date.available 2025-04-17T01:32:51Z
dc.date.issued 2024
dc.identifier.uri http://repository.president.ac.id/xmlui/handle/123456789/12591
dc.description.abstract Insurance is necessary nowadays, because insurance can cover a loss or damagethat occurs. The way insurance works in order to cover losses, a personcansubmit a claim provided that the person is registered as a customer and is obligedto pay dependents. In this case the dependents are called premiums. The amount of premium obtained comes from many factors, for example in motor vehicleinsurance seen from the condition of the vehicle, claim frequency, and claimamount. Then the data obtained is calculated using a method that supports thedetermination of premiums, one of which is the Linear Empirical Bayesianmethod. In this study, calculations were carried out to determine the amount of premium using the Linear Empirical Bayesian method, where this methodwasused to find the estimated expected value of XYZ insurance data in the formof claim frequency in 2020 and claim amount in 2015 and 2020. In the analysis, theestimated expectation of the claim frequency E(K)=0.89393 and the optimal expectation of the claim amount E(X)=$434.11 are obtained, then the results aremultiplied to determine the amount of premium in the future, with the formulaP=E(K)×E(X), P=0.89393 × $434.11 and the result is $388.07. en_US
dc.language.iso en_US en_US
dc.publisher President University en_US
dc.relation.ispartofseries Accounting;021201900011
dc.subject Motor Vehicle Insurance en_US
dc.subject Linear Empirical Bayesian Method en_US
dc.subject Premium Price en_US
dc.subject Expected Claim Frequency en_US
dc.subject Optimal Estimated of ClaimAmount en_US
dc.title THE APPLICATION OF LINEAREMPIRICALBAYESIAN (LEB) METHOD TO DETERMINETHEPREMIUM IN MOTOR VEHICLE INSURANCE en_US
dc.type Thesis en_US


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