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Rupiah Exchange Rate Forecast Against the United States Dollar Using the Singular Spectrum Analysis Method

Jurnal Matematika, Statistika dan Komputasi · Vol. 22 No. 3 (2026) · pp. 717–729

DOI
10.20956/j.v22i3.50120
ISSN
2614-8811, 1858-1382
Published
2026-05-14
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

Singular Spectrum Analysis (SSA) is a nonparametric time series forecasting method that decomposes a time series into signal and noise components without relying on predetermined model assumptions. This study aims to forecast the rupiah exchange rate against the United States Dollar (USD) using the Singular Spectrum Analysis (SSA) method based on data from the period August 2023 to August 2024. The in-sample data consists of 191 points from August 1, 2023, to May 21, 2024, while the out-of-sample data consists of 48 points from May 22, 2024, to August 1, 2024. The results showed that the SSA method achieved Mean Absolute Percentage Error (MAPE) values of 0.44% on in-sample data and 0.64% on out-of-sample data, indicating that the method is quite effective in predicting the rupiah exchange rate against the USD.

Keywords

Collaboration network of the authors

17 authors · 44 co-authorship links · 12 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Sebelas Maret University
  • Institut Teknologi Sepuluh Nopember
  • Universitas Muhammadiyah Surabaya
  • Padjadjaran University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Winita SulandariSebelas Maret University3
Titis Jati NugrahaSebelas Maret University2
İsnandar SlametSebelas Maret University2
Sri SubantiSebelas Maret University2
Sugianto SugiantoSebelas Maret University2
Nur IriawanInstitut Teknologi Sepuluh Nopember1
Kartika FithriasariInstitut Teknologi Sepuluh Nopember1
Brodjol Sutijo Suprih UlamaInstitut Teknologi Sepuluh Nopember1
Wahyuni SuryaningtyasUniversitas Muhammadiyah Surabaya1
Anindya Apriliyanti PravitasariPadjadjaran University1
Esa Permata Sari Putri IlahiAffiliation unknown1
Hasih PratiwiAffiliation unknown1
Fauzi Nafi'udinAffiliation unknown1
Slamet HaryonoAffiliation 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/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Rupiah Exchange Rate Forecast Against the United States Dollar Using the Singular Spectrum Analysis Method</dc:title>
	<dc:creator xml:lang="en">Qalbu, Mutiara</dc:creator>
	<dc:creator xml:lang="en">Zukhronah, Etik</dc:creator>
	<dc:creator xml:lang="en">Susanto, Irwan</dc:creator>
	<dc:subject xml:lang="en">exchange rate</dc:subject>
	<dc:subject xml:lang="en">forecast</dc:subject>
	<dc:subject xml:lang="en">SSA</dc:subject>
	<dc:description xml:lang="en">Singular Spectrum Analysis (SSA) is a nonparametric time series forecasting method that decomposes a time series into signal and noise components without relying on predetermined model assumptions. This study aims to forecast the rupiah exchange rate against the United States Dollar (USD) using the Singular Spectrum Analysis (SSA) method based on data from the period August 2023 to August 2024. The in-sample data consists of 191 points from August 1, 2023, to May 21, 2024, while the out-of-sample data consists of 48 points from May 22, 2024, to August 1, 2024. The results showed that the SSA method achieved Mean Absolute Percentage Error (MAPE) values of 0.44% on in-sample data and 0.64% on out-of-sample data, indicating that the method is quite effective in predicting the rupiah exchange rate against the USD.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2026-05-14</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/jmsk/article/view/50120</dc:identifier>
	<dc:identifier>10.20956/j.v22i3.50120</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 22 No. 3 (2026): May 2026; 717-729</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/50120/14421</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2026 Jurnal Matematika, Statistika dan Komputasi</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
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