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Forecasting Nickel Prices in Indonesia Using ARIMA, SVR, and Hybrid ARIMA-SVR Approach

Jurnal Matematika, Statistika dan Komputasi · Vol. 21 No. 3 (2025) · hlm. 627–645

DOI
10.20956/j.v21i3.42558
ISSN
2614-8811, 1858-1382
Terbit
2025-05-14
Penerbit
Department of Mathematics, Hasanuddin University
Bahasa
en
Lisensi
creativecommons.org/licenses/by/4.0

Abstrak

Nickel production plays a key role in reducing reliance on fossil fuels, supporting the 7th Sustainable Development Goals (SDGs) on clean and affordable energy. As the world's largest nickel ore producer, Indonesia significantly influences global market dynamics. This study evaluates the accuracy of ARIMA, SVR, and hybrid ARIMA-SVR models in forecasting Indonesia’s daily nickel futures prices for 2023 using historical data from official website investing.com. The results indicate that SVR outperforms the other models, achieving the lowest MAPE of 0.2532% with the Radial Basis Function (RBF) kernel and optimized parameters, and selected through grid search method which gives the minimum RMSE and MAE values as well. Accurate nickel price forecasting is essential for investors, mining companies, and policymakers to optimize production planning, manage risks, and enhance market stability. However, this study relies solely on historical price data, without considering external factors such as geopolitical events and market shocks, highlighting the need for future research incorporating broader economic indicators and alternative modeling approaches

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  • Universitas Airlangga
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Rekan penulisOrganisasiArtikel bersama
Muhammad Fariz Fadillah MardiantoUniversitas Airlangga4
Muhammad Fikry Al FariziUniversitas Airlangga1
Made Riyo Ary PermanaUniversitas Airlangga1
Alfian Iqbal ZahUniversitas Airlangga1
Bagas Shata PratamaUniversitas Airlangga1
Grace Lucyana KoesnadiUniversitas Airlangga1
Dzuria Hilma Qurotu AinUniversitas Airlangga1
Sa’idah Zahrotul JannahUniversitas Airlangga1
Sugha Faiz Al MaulaUniversitas Airlangga1
Nicoletta Almira Dyah SetiawanUniversitas Airlangga1
Fatiha Nadia SalsabilaUniversitas Airlangga1
Alfi Nur NitasariUniversitas Airlangga1
Irma Ayu IndrastaUniversitas Airlangga1
Hanny ValidaUniversitas Airlangga1
Farah Fauziah PutriUniversitas Airlangga1
Doni Muhammad FauziUniversitas Airlangga1
Dita AmeliaUniversitas Airlangga1
Suliyanto SuliyantoUniversitas Airlangga1
Nur AzizahUniversitas Airlangga1
Jovansha AriyawanUniversitas Airlangga1
R. Arya Januarta AdiputraUniversitas Airlangga1
Irsyad Yoga AdyatmaUniversitas Airlangga1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/jmsk/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">Forecasting Nickel Prices in Indonesia Using ARIMA, SVR, and Hybrid ARIMA-SVR Approach</dc:title>
	<dc:creator xml:lang="en">Carista, Nashwa</dc:creator>
	<dc:creator xml:lang="en">Mahadesyawardani, Arinda</dc:creator>
	<dc:creator xml:lang="en">Dwiyanto, Adelia Sukma</dc:creator>
	<dc:creator xml:lang="en">Pusporani, Elly</dc:creator>
	<dc:subject xml:lang="en">Autoregressive Integrated Moving Average (ARIMA)</dc:subject>
	<dc:subject xml:lang="en">Support Vector Regression (SVR)</dc:subject>
	<dc:subject xml:lang="en">Hybrid ARIMA-SVR</dc:subject>
	<dc:subject xml:lang="en">Forecasting</dc:subject>
	<dc:subject xml:lang="en">Nickel</dc:subject>
	<dc:description xml:lang="en">Nickel production plays a key role in reducing reliance on fossil fuels, supporting the 7th Sustainable Development Goals (SDGs) on clean and affordable energy. As the world's largest nickel ore producer, Indonesia significantly influences global market dynamics. This study evaluates the accuracy of ARIMA, SVR, and hybrid ARIMA-SVR models in forecasting Indonesia’s daily nickel futures prices for 2023 using historical data from official website investing.com. The results indicate that SVR outperforms the other models, achieving the lowest MAPE of 0.2532% with the Radial Basis Function (RBF) kernel and optimized parameters , and  selected through grid search method which gives the minimum RMSE and MAE values as well. Accurate nickel price forecasting is essential for investors, mining companies, and policymakers to optimize production planning, manage risks, and enhance market stability. However, this study relies solely on historical price data, without considering external factors such as geopolitical events and market shocks, highlighting the need for future research incorporating broader economic indicators and alternative modeling approaches</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2025-05-14</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/42558</dc:identifier>
	<dc:identifier>10.20956/j.v21i3.42558</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 21 No. 3 (2025): MAY 2025; 627-645</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/42558/12795</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 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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