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VECTOR AUTOREGRESSIVE WITH OUTLIER DETECTION ON RAINFALL AND WIND SPEED DATA

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 18 No. 1 (2024) · pp. 0117–0128

DOI
10.30598/barekengvol18iss1pp0117-0128
ISSN
2615-3017, 1978-7227
Published
2024-03-01
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Vector Autoregressive (VAR) is a multivariate time series model that analyzes more than one variable where each variable in the model is endogenous. VAR is one of the models used in forecasting rainfall and wind speed. In observations of rainfall and wind speed, there are usually a series of events whose values are far from other observations or can be said to be outliers. The purpose of this study is to compare the VAR model on rainfall and wind speed data before and after outlier detection. This study uses secondary data, namely monthly data on rainfall and wind speed from 2019 to 2021. From the analysis results, the smallest AIC value obtained in the VAR model before outlier detection was 4.94, then the smallest AIC value in the VAR model after outlier detection was 0.25. Thus, it can be concluded that the best model is obtained in the VAR model after outlier detection seen from the smallest AIC value of the two VAR models.

Collaboration network of the authors

31 authors · 82 co-authorship links

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Co-authorOrganisationJoint articles
Neva SatyahadewiAffiliation unknown18
Ray TamtamaAffiliation unknown5
Shantika MarthaAffiliation unknown3
Wirda AndaniAffiliation unknown3
Siti AprizkiyandariAffiliation unknown2
Dinda TiaraAffiliation unknown2
Dadan KusnandarAffiliation unknown1
Hani Dwi RetnaniAffiliation unknown1
Inggriani Millennia TaralyAffiliation unknown1
Steven Jansen SinagaAffiliation unknown1
Tiffany ArdhithaAffiliation unknown1
Indah OktavianiAffiliation unknown1
Widad ImtiyazAffiliation unknown1
Fritzgerald Muhammad ArsyiAffiliation unknown1
Aditya Nugraha PratamaAffiliation unknown1
Wiji UmiatiAffiliation unknown1
Ainun ZakiahAffiliation unknown1
Noerul HaninAffiliation unknown1
Della ZariaAffiliation unknown1
Muhammad FauzanAffiliation unknown1
Nabila Izza HarnantaAffiliation unknown1
Hendri AgustonoAffiliation unknown1
Rifki PebriyandiAffiliation unknown1
Risky GunawanAffiliation unknown1
Cinta Priscillia MaharaniAffiliation unknown1
David Jordy DhandioAffiliation unknown1
Nurhanifa NurhanifaAffiliation unknown1
Sania PujiantiAffiliation 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">VECTOR AUTOREGRESSIVE WITH OUTLIER DETECTION ON RAINFALL AND WIND SPEED DATA</dc:title>
	<dc:creator>Lestari, Lisa</dc:creator>
	<dc:creator>Sulistianingsih, Evy</dc:creator>
	<dc:creator>Perdana, Hendra</dc:creator>
	<dc:description xml:lang="en-US">Vector Autoregressive (VAR) is a multivariate time series model that analyzes more than one variable where each variable in the model is endogenous. VAR is one of the models used in forecasting rainfall and wind speed. In observations of rainfall and wind speed, there are usually a series of events whose values are far from other observations or can be said to be outliers. The purpose of this study is to compare the VAR model on rainfall and wind speed data before and after outlier detection. This study uses secondary data, namely monthly data on rainfall and wind speed from 2019 to 2021. From the analysis results, the smallest AIC value obtained in the VAR model before outlier detection was 4.94, then the smallest AIC value in the VAR model after outlier detection was 0.25. Thus, it can be concluded that the best model is obtained in the VAR model after outlier detection seen from the smallest AIC value of the two VAR models.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2024-03-01</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/10010</dc:identifier>
	<dc:identifier>10.30598/barekengvol18iss1pp0117-0128</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application; 0117-0128</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol18iss1year2024</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/10010/7555</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Lisa Lestari, Evy Sulistianingsih, Hendra Perdana</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>