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Open access Jurnal SINTA 3

COMPARATIVE STUDY OF FUNCTIONAL LINEAR REGRESSION AND AN INTERACTION MODEL FOR MODELING RAINFALL IN INDONESIA

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 20 No. 3 (2026) · pp. 1793–1806

DOI
10.30598/barekengvol20iss3pp1793-1806
ISSN
2615-3017, 1978-7227
Published
2026-04-08
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Regression is a widely used statistical modeling method. Its applications have evolved, including functional data analysis, which offers flexibility by modeling data over specific time intervals with varying case-specific observations. Functional regression has several categories, one of which is functional prediction regression. This study uses functional prediction regression to model comprehensive climate data from the World Bank Climate Change Knowledge Portal, specifically Indonesia’s average annual temperature and rainfall from 1951 to 2016. An advantage of functional prediction regression is its ability to model based on the dataset. We compare two models: the first with a functional linear effect and the second with a linear interaction combination effect. The models are estimated using boosting and the Generalized Additive Model for Location, Scale, and Shape (GAMLSS). Results show that the functional linear model better fits Indonesia's rainfall data, yielding a smaller Akaike's Information Criterion by 170.351.

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">COMPARATIVE STUDY OF FUNCTIONAL LINEAR REGRESSION AND AN INTERACTION MODEL FOR MODELING RAINFALL IN INDONESIA</dc:title>
	<dc:creator>Khikmah, Khusnia Nurul</dc:creator>
	<dc:creator>Sofro, A'yunin</dc:creator>
	<dc:description xml:lang="en-US">Regression is a widely used statistical modeling method. Its applications have evolved, including functional data analysis, which offers flexibility by modeling data over specific time intervals with varying case-specific observations. Functional regression has several categories, one of which is functional prediction regression. This study uses functional prediction regression to model comprehensive climate data from the World Bank Climate Change Knowledge Portal, specifically Indonesia’s average annual temperature and rainfall from 1951 to 2016. An advantage of functional prediction regression is its ability to model based on the dataset. We compare two models: the first with a functional linear effect and the second with a linear interaction combination effect. The models are estimated using boosting and the Generalized Additive Model for Location, Scale, and Shape (GAMLSS). Results show that the functional linear model better fits Indonesia's rainfall data, yielding a smaller Akaike's Information Criterion by 170.351.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2026-04-08</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/18869</dc:identifier>
	<dc:identifier>10.30598/barekengvol20iss3pp1793-1806</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 20 No 3 (2026): BAREKENG: Journal of Mathematics and Its Application; 1793-1806</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol20iss3year2026</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/18869/12666</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 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>