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Zero-Inflated Integer Autoregressive (ZINAR) Approach in Modeling Major Earthquakes in Sumatra Region

Jurnal Matematika, Statistika dan Komputasi · Vol. 22 No. 2 (2026) · pp. 486–498

DOI
10.20956/j.v22i2.48219
ISSN
2614-8811, 1858-1382
Published
2026-01-10
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

Sumatra is one of the regions in Indonesia with the highest seismic activity due to the convergence of the Indo-Australian and Eurasian plates. Major earthquakes with magnitudes of more than 7 pose serious risks, making it essential to understand their frequency for effective disaster mitigation planning. This study aims to model the frequency of major earthquakes in Sumatra using the Zero-Inflated Integer Autoregressive (ZINAR) model, which accommodates discrete data with excess zeros and temporal dependence. The analysis indicates significant overdispersion and zero inflation, leading to the selection of the ZINAR model as the most suitable approach compared to alternative models such as INAR, NB-INAR, and NB-ZINAR. The ZINAR model demonstrates superior performance in capturing the occurrence patterns of large earthquakes and effectively identifies non-event periods, although its predictive accuracy for actual event timing remains limited. Overall, the ZINAR model proves effective for modeling complex earthquake data and provides valuable insights to support disaster mitigation efforts in the Sumatra region.

Keywords

Collaboration network of the authors

29 authors · 86 co-authorship links

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  • Hasanuddin University
  • Affiliation unknown
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Co-authorOrganisationJoint articles
Nur AfandiHasanuddin University2
Siska YosmarAffiliation unknown2
Dyah Setyo RiniAffiliation unknown2
Elisabeth Evelin KarunaAffiliation unknown2
Idhia SrilianaAffiliation unknown2
Pepi NoviantiAffiliation unknown2
Winalia AgwilAffiliation unknown2
Firdaus FirdausAffiliation unknown1
Raditya Janaloka NatishareviAffiliation unknown1
Wina Ayu LestariAffiliation unknown1
Septri DamayantiAffiliation unknown1
Vivin AcnesyaAffiliation unknown1
Tommy JomechoAffiliation unknown1
Cinta Rizky OktarinaAffiliation unknown1
Stevy Cahya PratiwiAffiliation unknown1
Esther Damayanti SihombingAffiliation unknown1
Riki CrisdiantoAffiliation unknown1
Athaya FairuzindahAffiliation unknown1
Ramya RachmawatiAffiliation unknown1
Muhammad Arib AlwansyahAffiliation unknown1
Cinta Rizki OktarinaAffiliation unknown1
Zulfia Memi MayasariAffiliation unknown1
Fachri FaisalAffiliation unknown1
Mulia AstutiAffiliation unknown1
Refpo RahmanAffiliation unknown1
Ressy Fitrizka HaryantiAffiliation 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://journal.unhas.ac.id/index.php/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Zero-Inflated Integer Autoregressive (ZINAR) Approach in Modeling Major Earthquakes in Sumatra Region</dc:title>
	<dc:creator xml:lang="en">Wahyuliani, Indah</dc:creator>
	<dc:creator xml:lang="en">Rizal, Jose</dc:creator>
	<dc:creator xml:lang="en">Nugroho, Sigit</dc:creator>
	<dc:subject xml:lang="en">Earthquake</dc:subject>
	<dc:subject xml:lang="en">Overdispersion</dc:subject>
	<dc:subject xml:lang="en">Zero-inflated</dc:subject>
	<dc:subject xml:lang="en">Integer Autoregressive model</dc:subject>
	<dc:description xml:lang="en">Sumatra is one of the regions in Indonesia with the highest seismic activity due to the convergence of the Indo-Australian and Eurasian plates. Major earthquakes with magnitudes of more than 7 pose serious risks, making it essential to understand their frequency for effective disaster mitigation planning. This study aims to model the frequency of major earthquakes in Sumatra using the Zero-Inflated Integer Autoregressive (ZINAR) model, which accommodates discrete data with excess zeros and temporal dependence. The analysis indicates significant overdispersion and zero inflation, leading to the selection of the ZINAR model as the most suitable approach compared to alternative models such as INAR, NB-INAR, and NB-ZINAR. The ZINAR model demonstrates superior performance in capturing the occurrence patterns of large earthquakes and effectively identifies non-event periods, although its predictive accuracy for actual event timing remains limited. Overall, the ZINAR model proves effective for modeling complex earthquake data and provides valuable insights to support disaster mitigation efforts in the Sumatra region.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2026-01-10</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://journal.unhas.ac.id/index.php/jmsk/article/view/48219</dc:identifier>
	<dc:identifier>10.20956/j.v22i2.48219</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 22 No. 2 (2026): JANUARY 2026; 486-498</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/48219/14000</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2026 Jurnal Matematika, Statistika dan Komputasi</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
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