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Pemodelan Nilai Tukar Rupiah terhadap Dolar AS Menggunakan Ridge Regression dengan Koreksi Autokorelasi Prais Winsten

ESTIMASI: Journal of Statistics and Its Application · Vol. 7 No. 1 (2026) · pp. 116–130

DOI
10.20956/ejsa.v7i1.45517
ISSN
2721-379X, 2721-3803
Published
2026-05-05
Publisher
Hasanuddin University
Language
en

Abstract

Linear regression is a statistical method used to analyze the relationship between dependent and independent variables. Parameter estimation is generally obtained through the Ordinary Least Square (OLS) method, which produces unbiased and efficient estimates. However, the presence of multicollinearity and autocorrelation can render OLS estimates suboptimal. The Ridge Regression method combined with Prais Winsten correction can to produce more accurate parameter estimates than OLS. Unlike the subjective approach in determining the bias constant () through Ridge Trace, this study determines the optimal value by minimizing the Mean Square Error (MSE). The results show that the Ridge Regression model with Prais Winsten autocorrelation correction has an Adjusted R² of 78% and a Root Mean Square Error (RMSE) of Rp364,389. Four independent variables are found to have a significant effect on the exchange rate of the Indonesian Rupiah against the United States Dollar (USD), namely money supply, interest rate, exports, and imports.

Keywords

Collaboration network of the authors

28 authors · 89 co-authorship links

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  • Institut Agama Islam Negeri Kendari
  • Affiliation unknown
  • Different organisations
  • Same organisation
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  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Anna IslamiyatiAffiliation unknown3
Nirwan IlyasAffiliation unknown3
Sitti SahrimanAffiliation unknown2
Muhammad FadilAffiliation unknown2
Fauziah NurhidayahAffiliation unknown2
Zhazha Alifkhamulki RamdhaniAffiliation unknown1
Samsul ArifinAffiliation unknown1
Andi Sitti Fahmi Riyanti HufainiAffiliation unknown1
Dwicahyo Ramadhan PriyatnaAffiliation unknown1
La Podje TalangkoAffiliation unknown1
Vieri KoerniawanAffiliation unknown1
Nurtiti SunusiAffiliation unknown1
Dewi Rahma EnteAffiliation unknown1
Andi Kresna JayaAffiliation unknown1
Andi Tenri Riski AmaliaAffiliation unknown1
Fitri AnnisaAffiliation unknown1
Asnidar AsnidarAffiliation unknown1
Nurul HikmahInstitut Agama Islam Negeri Kendari1
Nasrah SirajangAffiliation unknown1
Siswanto SiswantoAffiliation unknown1
Andi Isna YunitaAffiliation 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">Pemodelan Nilai Tukar Rupiah terhadap Dolar AS Menggunakan Ridge Regression dengan  Koreksi Autokorelasi Prais Winsten</dc:title>
	<dc:creator xml:lang="en">Parapa, Anni Ivoni</dc:creator>
	<dc:creator xml:lang="en">Raupong, Raupong</dc:creator>
	<dc:creator xml:lang="en">Angriany, A.Muthiah Nur</dc:creator>
	<dc:subject xml:lang="en">Autocorrelation</dc:subject>
	<dc:subject xml:lang="en">Multicollinearity</dc:subject>
	<dc:subject xml:lang="en">Prais Winsten</dc:subject>
	<dc:subject xml:lang="en">Ridge Regression</dc:subject>
	<dc:subject xml:lang="en">Rupiah Exchange Rate Against the US Dollar</dc:subject>
	<dc:description xml:lang="en">Linear regression is a statistical method used to analyze the relationship between dependent and independent variables. Parameter estimation is generally obtained through the Ordinary Least Square (OLS) method, which produces unbiased and efficient estimates. However, the presence of multicollinearity and autocorrelation can render OLS estimates suboptimal. The Ridge Regression method combined with Prais Winsten correction can to produce more accurate parameter estimates than OLS. Unlike the subjective approach in determining the bias constant () through Ridge Trace, this study determines the optimal  value by minimizing the Mean Square Error (MSE). The results show that the Ridge Regression model with Prais Winsten autocorrelation correction has an Adjusted R² of 78% and a Root Mean Square Error (RMSE) of Rp364,389. Four independent variables are found to have a significant effect on the exchange rate of the Indonesian Rupiah against the United States Dollar (USD), namely money supply, interest rate, exports, and imports.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2026-05-05</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/45517</dc:identifier>
	<dc:identifier>10.20956/ejsa.v7i1.45517</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 7, No. 1, Januari, 2026 : Estimasi; 116-130</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/45517/14385</dc:relation>
</oai_dc:dc>