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Forecasting Rice Prices in Gorontalo Province Using Hybrid Singular Spectrum Analysis (SSA) and Triple Exponential Smoothing Methods (TES)

Jurnal Matematika, Statistika dan Komputasi · Vol. 22 No. 1 (2025) · hlm. 1–15

DOI
10.20956/j.v22i1.43322
ISSN
2614-8811, 1858-1382
Terbit
2025-09-08
Penerbit
Department of Mathematics, Hasanuddin University
Bahasa
en
Lisensi
creativecommons.org/licenses/by/4.0

Abstrak

Currently, Gorontalo Province is experiencing the problem of unstable rice prices from the government which makes it difficult for people to meet their food needs, especially rice. There are several factors that can influence rice price instability, namely high demand from other regions, large areas of harvested land, and weather conditions such as drought, floods and the spread of pests that can destroy rice plants. This can cause the price of rice to increase and decrease each month. Therefore, forecasting rice prices for the future is carried out. The method used to forecast is hybrid Singular Spectrum Analysis and Triple Exponential Smoothing. The criteria for determining forecasting accuracy are based on the Mean Absolute Percentage Error value. After the forecasting was carried out, the hybrid Singular Spectrum Analysis and Triple Exponential Smoothing forecasting obtained a Mean Absolute Percentage Error (MAPE) value of 0.04352537 or 4.35%. The hybrid method of Singular Spectrum Analysis and Triple Exponential Smoothing is said to be better if it has an accuracy value of less than 10%.

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  • State University of Gorontalo
  • Afiliasi tidak diketahui
  • Organisasi berbeda
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Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Nisky Imansyah YahyaState University of Gorontalo2
Zulkifli AlamtahaAfiliasi tidak diketahui1
Mohamad Rivaldi KoniAfiliasi tidak diketahui1
Irsan K. HasanState University of Gorontalo1
Sri Endang SalehState University of Gorontalo1
Debyyansa PakayaState University of Gorontalo1
Muhammad Rezky Friesta PayuState University of Gorontalo1
Lailany YahyaState University of Gorontalo1
La Ode NasharState University of Gorontalo1
Amanda AdityaningrumState University of Gorontalo1
Sri Indriani LadjaliState University of Gorontalo1
Herlina JusufState University of Gorontalo1

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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 Rice Prices in Gorontalo Province Using Hybrid Singular Spectrum Analysis (SSA) and Triple Exponential Smoothing Methods (TES)</dc:title>
	<dc:creator xml:lang="en">Hunowu, Lisnawati R.</dc:creator>
	<dc:creator xml:lang="en">Djakaria, Ismail</dc:creator>
	<dc:creator xml:lang="en">Arsal, Armayani</dc:creator>
	<dc:subject xml:lang="en">Forecasting</dc:subject>
	<dc:subject xml:lang="en">Singular Spectrum Analysis</dc:subject>
	<dc:subject xml:lang="en">Triple Eksponential Smoothing</dc:subject>
	<dc:description xml:lang="en">Currently, Gorontalo Province is experiencing the problem of unstable rice prices from the government which makes it difficult for people to meet their food needs, especially rice. There are several factors that can influence rice price instability, namely high demand from other regions, large areas of harvested land, and weather conditions such as drought, floods and the spread of pests that can destroy rice plants. This can cause the price of rice to increase and decrease each month. Therefore, forecasting rice prices for the future is carried out.  The method used to forecast is hybrid Singular Spectrum Analysis and Triple Exponential Smoothing. The criteria for determining forecasting accuracy are based on the Mean Absolute Percentage Error value. After the forecasting was carried out, the hybrid Singular Spectrum Analysis and Triple Exponential Smoothing forecasting obtained a Mean Absolute Percentage Error (MAPE) value of 0.04352537 or 4.35%. The hybrid method of Singular Spectrum Analysis and Triple Exponential Smoothing is said to be better if it has an accuracy value of less than 10%.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2025-09-08</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/43322</dc:identifier>
	<dc:identifier>10.20956/j.v22i1.43322</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 22 No. 1 (2025): SEPTEMBER 2025; 1-15</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/43322/13323</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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