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Open access Jurnal SINTA 3

POISSON REGRESSION MODELLING OF AUTOMOBILE INSURANCE USING R

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 16 No. 4 (2022) · pp. 1399–1410

DOI
10.30598/barekengvol16iss4pp1399-1410
ISSN
2615-3017, 1978-7227
Published
2022-12-15
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Automobile insurance benefits are protecting the vehicle and minimizing customer losses. Insurance companies must provide funds to pay customer claims if a claim occurs. Insurance claims can be modelled by Poisson regression. Poisson regression is used to analyze the count data with Poisson distributed data responses. this paper, the data model of sample is automobile insurance claims from the companies in one year (in 2021) of observation which contains three types of insurance products, i.e., Total Loss Only (TLO), All Risk, and Comprehensive. The results of data analysis show that the highest number of claims comes from Comprehensive insurance products, especially if the premium value gets more extensive. In contrast, the least comes from TLO insurance products.

Collaboration network of the authors

14 authors · 31 co-authorship links

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  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Edwin Setiawan NugrahaAffiliation unknown7
Sisilia SylvianiAffiliation unknown6
Marsah Rahmawati UtamiAffiliation unknown2
Risnawita RisnawitaAffiliation unknown2
Fitriani AgustinaAffiliation unknown2
Ebenezer BonyahAffiliation unknown2
Agna OliviaAffiliation unknown1
Fauziah Nur Fahirah SuddingAffiliation unknown1
Husty Serviana HusainAffiliation unknown1
Sapto Wahyu IndratnoAffiliation unknown1
Ari Ratna GumilangAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">POISSON REGRESSION MODELLING OF AUTOMOBILE INSURANCE USING R</dc:title>
	<dc:creator>Vantika, Sandy</dc:creator>
	<dc:creator>Yudhanegara, Mokhammad Ridwan</dc:creator>
	<dc:creator>Lestari, Karunia Eka</dc:creator>
	<dc:description xml:lang="en-US">Automobile insurance benefits are protecting the vehicle and minimizing customer losses. Insurance companies must provide funds to pay customer claims if a claim occurs. Insurance claims can be modelled by Poisson regression. Poisson regression is used to analyze the count data with Poisson distributed data responses.  this paper, the data model of sample is automobile insurance claims from the companies in one year (in 2021) of observation which contains three types of insurance products, i.e., Total Loss Only (TLO), All Risk, and Comprehensive. The results of data analysis show that the highest number of claims comes from Comprehensive insurance products, especially if the premium value gets more extensive. In contrast, the least comes from TLO insurance products.
&amp;nbsp;
&amp;nbsp;</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2022-12-15</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/6555</dc:identifier>
	<dc:identifier>10.30598/barekengvol16iss4pp1399-1410</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications; 1399-1410</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol16iss4year2022</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/6555/5155</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Sandy Vantika, Mokhammad Ridwan Yudhanegara, Karunia Eka Lestari</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>