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NEGATIVE BINOMIAL REGRESSION AND GENERALIZED POISSON REGRESSION MODELS ON THE NUMBER OF TRAFFIC ACCIDENTS IN CENTRAL JAVA

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 16 No. 2 (2022) · pp. 471–482

DOI
10.30598/barekengvol16iss2pp471-482
ISSN
2615-3017, 1978-7227
Published
2022-06-01
Publisher
PATTIMURA UNIVERSITY
Language
eng

Abstract

Traffic accidents that always increase along with the increasing population growth and the number of vehicles impact the national economy. The number of traffic accidents is a count data that a Poisson distribution can approximate. The Poisson regression model often found violations of the overdispersion assumption by modeling the factors that affect the number of traffic accidents. Alternative models proposed to overcome the emergence of overdispersion in the Poisson regression model are the Generalized Poisson Regression and Negative Binomial Regression Models. Based on the analysis results, it was found that the overdispersion assumption violates the Poisson regression model, and the Generalized Poisson regression model is the best because it has the smallest AIC value of 485.50. Factors that significantly affect the number of traffic accidents in Central Java Province are the percentage of adolescents and the percentage of accidents occurring in the road area of the district/city.

Collaboration network of the authors

17 authors · 33 co-authorship links

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  • Universitas Muhammadiyah Semarang
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Anita Retno IndrianiAffiliation unknown2
Rochdi WasonoAffiliation unknown2
Rahmad Putra GautamaAffiliation unknown2
Bunga AyuningrumAffiliation unknown1
Hilma Hanna Mahanna HaqqAffiliation unknown1
Suci Mega Puji LestariAffiliation unknown1
Laily HimmaturrohmahAffiliation unknown1
Indah Manfaati NurAffiliation unknown1
Nun Maulida Suci AyomiAffiliation unknown1
Yulia FitriAffiliation unknown1
mohammad ridwanAffiliation unknown1
Ina AlfidayantiAffiliation unknown1
Muhammad Sam’anUniversitas Muhammadiyah Semarang1
Wulan SariAffiliation unknown1
Fatkhurokhman FauziAffiliation 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) 
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	<dc:title xml:lang="en-US">NEGATIVE BINOMIAL REGRESSION AND GENERALIZED POISSON REGRESSION MODELS ON THE NUMBER OF TRAFFIC ACCIDENTS IN CENTRAL JAVA</dc:title>
	<dc:creator>Haris, M Al</dc:creator>
	<dc:creator>Arum, Prizka Rismawati</dc:creator>
	<dc:description xml:lang="en-US">Traffic accidents that always increase along with the increasing population growth and the number of vehicles impact the national economy. The number of traffic accidents is a count data that a Poisson distribution can approximate. The Poisson regression model often found violations of the overdispersion assumption by modeling the factors that affect the number of traffic accidents. Alternative models proposed to overcome the emergence of overdispersion in the Poisson regression model are the Generalized Poisson Regression and Negative Binomial Regression Models. Based on the analysis results, it was found that the overdispersion assumption violates the Poisson regression model, and the Generalized Poisson regression model is the best because it has the smallest AIC value of 485.50. Factors that significantly affect the number of traffic accidents in Central Java Province are the percentage of adolescents and the percentage of accidents occurring in the road area of the district/city.
&amp;nbsp;</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2022-06-01</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/5004</dc:identifier>
	<dc:identifier>10.30598/barekengvol16iss2pp471-482</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan; 471-482</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol16iss2year2022</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5004/4475</dc:relation>
</oai_dc:dc>