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International Journal of Global Operations Research
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Determination of Pure Health Insurance Premiums Using Generalized Linear Models (GLM) with Poisson Distribution

descriptionPublicationkeyboard_double_arrow_right Article 27 May 2024Publisher:Indonesian Operations Research AssociationJournal:International Journal of Global Operations Research, volume 5, pages 88-92 (issn: 2723-1747, eissn: 2722-1016, Copyright policy )
Authors: Devani Oktaviani; Nabila Zahra; Nurfadhlina Abdul Halim;

doi: 10.47194/ijgor.v5i2.308

Determination of Pure Health Insurance Premiums Using Generalized Linear Models (GLM) with Poisson Distribution

Abstract

Insurance companies need a method to help companies determine premium prices that are appropriate to the risks they face. In other words, it is also necessary to know the variables that influence premium prices using Generalized Linear Models (GLM) by generalizing the linear regression model to model the relationship between the dependent variable and the independent variable. The aim of this research is to determine the variables that influence premium prices and determine the pure health insurance premium using the GLM method.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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