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Open access Jurnal SINTA 3

COMPARISON OF ARIMA AND GARMA'S PERFORMANCE ON DATA ON POSITIVE COVID-19 CASES IN INDONESIA

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 16 No. 3 (2022) · pp. 919–926

DOI
10.30598/barekengvol16iss3pp919-926
ISSN
2615-3017, 1978-7227
Published
2022-09-01
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The development of methods in statistics, one of which is used for prediction, is overgrowing. So it requires further analysis related to the goodness of the method. One of the comparisons made to the goodness of this model can be seen by applying it to actual cases around us. The real case still being faced by people worldwide, including in Indonesia, is Covid-19. Therefore, research comparing the autoregressive integrated moving average (ARIMA) and the Gegenbauer autoregressive moving average (GARMA) method in positive confirmed cases of Covid-19 in Indonesia is essential. Based on the results of this research analysis, it was found that the best model with the Aikake's Information Criterion measure of goodness that was used to predict positive confirmed cases of Covid-19 in Indonesia was the Gegenbauer autoregressive moving average (GARMA) model.

Collaboration network of the authors

18 authors · 54 co-authorship links

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Co-authorOrganisationJoint articles
Danang AriyantoAffiliation unknown7
Riska Wahyu RomadhoniaAffiliation unknown5
Affiati OktaviarinaAffiliation unknown3
Dimas Avian MaulanaAffiliation unknown2
Rosalina Agista RianiAffiliation unknown2
Framitha Septian SubiantoroAffiliation unknown2
Asri MaharaniAffiliation unknown2
Mutia Eva MustafidahAffiliation unknown2
Kusman SadikAffiliation unknown1
Indahwati IndahwatiAffiliation unknown1
A’idah Nur HanifahAffiliation unknown1
Junaidi Budi PrihantoAffiliation unknown1
Mohammad Dian PurnamaAffiliation unknown1
Riskyana Dewi I PuspitasariAffiliation unknown1
Hernando OmbaoAffiliation unknown1
A'yunin Sofro SofroAffiliation 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">COMPARISON OF ARIMA AND GARMA'S PERFORMANCE ON DATA ON POSITIVE COVID-19 CASES IN INDONESIA</dc:title>
	<dc:creator>Sofro, A'yunin</dc:creator>
	<dc:creator>Khikmah, Khusnia Nurul</dc:creator>
	<dc:description xml:lang="en-US">The development of methods in statistics, one of which is used for prediction, is overgrowing. So it requires further analysis related to the goodness of the method. One of the comparisons made to the goodness of this model can be seen by applying it to actual cases around us. The real case still being faced by people worldwide, including in Indonesia, is Covid-19. Therefore, research comparing the autoregressive integrated moving average (ARIMA) and the Gegenbauer autoregressive moving average (GARMA) method in positive confirmed cases of Covid-19 in Indonesia is essential. Based on the results of this research analysis, it was found that the best model with the Aikake's Information Criterion measure of goodness that was used to predict positive confirmed cases of Covid-19 in Indonesia was the Gegenbauer autoregressive moving average (GARMA) model.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2022-09-01</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/6081</dc:identifier>
	<dc:identifier>10.30598/barekengvol16iss3pp919-926</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications; 919-926</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol16iss3year2022</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/6081/4615</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 A'yunin Sofro, Khusnia Nurul Khikmah</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>