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Model ARIMA dengan Variabel Eksogen dan GARCH pada Data Kurs Rupiah

ESTIMASI: Journal of Statistics and Its Application · Vol. 3 No. 1 (2022) · pp. 41–48

DOI
10.20956/ejsa.vi.11603
ISSN
2721-379X, 2721-3803
Published
2022-02-01
Publisher
Hasanuddin University
Language
en

Abstract

Autoregressive integrated moving average with exegenous variable (ARIMAX) model is the development of ARIMA model with addition of other time series data as exogenous variable that affect the dependent variable. ARIMAX model is used to analyze and predict data on the rupiah exchange rate against the US dollar with inflation as an exogenous variabel. The exchange rate has an residual variance that is not constant so that the GARCH model is used to overcome the problem of heteroscedasticity. The results of this research show that forecasting the rupiah exchange rate against the US dollar fot the period January 2010 – December 2019 with the ARIMAX(0,1,1) – GARCH(1,0) model is the best model with a MAPE (1,1655) value which shows a low percentage compared to the ARIMAX model.

Keywords

Collaboration network of the authors

31 authors · 84 co-authorship links

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Co-authorOrganisationJoint articles
Andi Kresna JayaAffiliation unknown4
Erna Tri HerdianiAffiliation unknown2
Raupong RaupongAffiliation unknown2
Muhammad IdmanAffiliation unknown2
Dwicahyo Ramadhan PriyatnaAffiliation unknown1
Rizki AdiputraAffiliation unknown1
Risma RismaAffiliation unknown1
Dewi Santika Upa P.Affiliation unknown1
Fitriatusakiah FitriatusakiahAffiliation unknown1
Fitri AnnisaAffiliation unknown1
Nasrah SirajangAffiliation unknown1
Mukrimin AdamAffiliation unknown1
Ainul FajriAffiliation unknown1
Anisa Haura Salsa Fatih YusufAffiliation unknown1
Georgina Maria TinungkiAffiliation unknown1
Hendriete Tiur Marowi WaibusiAffiliation unknown1
Rael Hofni TandirerungAffiliation unknown1
Nirwan NirwanAffiliation unknown1
Nurhidayatullah NurhidayatullahAffiliation unknown1
Amalia AndrianingrumAffiliation unknown1
Siswanto SiswantoAffiliation unknown1
Andi Isna YunitaAffiliation unknown1
Muhammad FadilAffiliation unknown1
A.Muthiah Nur AngrianyAffiliation unknown1
Rini JamalAffiliation unknown1
Andi M Alfin BasoAffiliation unknown1
Andi FebriyantiAffiliation unknown1
Rahmiati RahimAffiliation 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/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Model ARIMA dengan Variabel Eksogen dan GARCH pada Data Kurs Rupiah</dc:title>
	<dc:creator xml:lang="en">Arianti, Ririn</dc:creator>
	<dc:creator xml:lang="en">Sahriman, Sitti</dc:creator>
	<dc:creator xml:lang="en">Talangko, La Podje</dc:creator>
	<dc:subject xml:lang="en">ARIMAX</dc:subject>
	<dc:subject xml:lang="en">GARCH</dc:subject>
	<dc:subject xml:lang="en">Heteroscedasticity</dc:subject>
	<dc:description xml:lang="en">Autoregressive integrated moving average with exegenous variable (ARIMAX) model is the development of ARIMA model with addition of other time series data as exogenous variable that affect the dependent variable. ARIMAX model is used to analyze and predict data on the rupiah exchange rate against the US dollar with inflation as an exogenous variabel. The exchange rate has an residual variance that is not constant  so that the GARCH model is used to overcome the problem of heteroscedasticity. The results of this research show that forecasting the rupiah exchange rate against the US dollar fot the period January 2010 – December 2019 with the ARIMAX(0,1,1) – GARCH(1,0) model is the best model with a MAPE (1,1655) value which shows a low percentage compared to the ARIMAX model.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2022-02-01</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://journal.unhas.ac.id/index.php/ESTIMASI/article/view/11603</dc:identifier>
	<dc:identifier>10.20956/ejsa.vi.11603</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 3, No. 1, Januari, 2022 : Estimasi; 41-48</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/11603/7855</dc:relation>
</oai_dc:dc>