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Forecasting Dry Rubber Production in Indonesia for the Year 2022 Using Pegel's Exponential Smoothing Method with Modified Golden Section Optimization

Jurnal Matematika, Statistika dan Komputasi · Vol. 21 No. 2 (2025) · pp. 368–381

DOI
10.20956/j.v21i2.37158
ISSN
2614-8811, 1858-1382
Published
2025-01-12
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

English

Pegel’s Exponential Smoothing is a forecasting method that considers separating trend and seasonal aspects, with additive and multiplicative models. Pegel’s Exponential Smoothing has three parameters, α, β, and γ. Many possible parameter combinations may yield an optimal solution, so a modified Golden Section method is used. The principle of this method is to iteratively reduce the boundary area of x that may produce an optimal objective function value, systematically decreasing the number of search steps to minimize the number of trials. Data obtained from the Central Bureau of Statistics regarding the amount of dry rubber production in Indonesian plantations from January 2017 to December 2022 is assumed to contain a multiplicative seasonal effect due to the relatively unstable seasonal pattern heights. This study compares three trend models: no trend, additive trend, and multiplicative trend in the multiplicative seasonal Pegel’s Exponential Smoothing method. This study aims to predict the amount of dry rubber production in Indonesian plantations from January 2022 to December 2022. Forecast validation results show that the multiplicative trend in the multiplicative seasonal Pegel’s Exponential Smoothing method, with a MAPE of 3.389001% and an RMSE of 8,839.965080, has the best forecasting accuracy for this data compared to the other three trend models.

Indonesian

Pegel’s Eksponential Smoothing merupakan metode peramalan yang mempertimbangkan pemisah aspek tren dan musiman dimana modelnya bersifat aditif dan multiplikatif. Pegel’s Eksponential Smoothing memiliki tiga parameter, yaitu dan. Terdapat banyak kombinasi parameter yang mungkin menghasilkan solusi optimal sehingga digunakan modifikasi metode Golden Section, dimana prinsip dari metode ini yaitu mengurangi secara bertahap dan berulang wilayah batas yang mungkin menghasilkan nilai fungsi objektif optimum sehingga mampu meminimalkan jumlah percobaan. Data yang diperoleh dari Badan Pusat Statistik mengenai jumlah produksi karet kering perkebunan Indonesia periode Januari 2017-Desember 2022 diasumsikan mengandung efek musiman multiplikatif dikarenakan ketinggian pola musimannya relatif tidak stabil. Penelitian ini membandingkan 3 model tren yaitu tanpa tren, tren aditif, dan tren multiplikatif pada metode Pegel’s Eksponential Smoothing musiman multiplikatif. Tujuan dari penelitian ini yaitu untuk meramalkan jumlah produksi karet kering perkebunan Indonesia periode Januari 2022-Desember 2022. Validasi hasil peramalan menunjukkan bahwa metode Pegel’s Eksponential Smoothing musiman multiplikatif tren multiplikatif dengan nilai MAPE sebesar 3,389001% dan nilai RMSE sebesar 8.839,965080 adalah metode yang memiliki akurasi peramalan terbaik dalam meramalkan data tersebut dibanding dengan 3 model tren lainnya.

Keywords

Collaboration network of the authors

40 authors · 128 co-authorship links

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  • Sultan Ageng Tirtayasa University
  • Affiliation unknown
  • Different organisations
  • Same organisation
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Show as table
Co-authorOrganisationJoint articles
Erna Tri HerdianiAffiliation unknown2
La Podje TalangkoAffiliation unknown2
Andi Kresna JayaAffiliation unknown2
Siswanto SiswantoAffiliation unknown2
Muh. Ikbal TaufikAffiliation unknown2
Anisa KalondengAffiliation unknown2
M. Zaky Hisyam GozhiAffiliation unknown2
Rizki AdiputraAffiliation unknown1
Risma RismaAffiliation unknown1
Dewi Santika Upa P.Affiliation unknown1
Ririn AriantiAffiliation unknown1
Muhammad IdmanAffiliation unknown1
Raupong RaupongAffiliation unknown1
Fitri AnnisaAffiliation unknown1
Nasrah SirajangAffiliation unknown1
Mukrimin AdamAffiliation 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
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
Andi Sri YuliantiAffiliation unknown1
Eunike Laurine RandaAffiliation unknown1
Sitti Aisyah SuriandaAffiliation unknown1
M. Zaky Gozhi HisyamAffiliation unknown1
Guntur Dwi PutraAffiliation unknown1
Anisa AnisaSultan Ageng Tirtayasa University1
Syamsuddin ToahaAffiliation unknown1
Aidul Fitri MustaminAffiliation 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">Forecasting Dry Rubber Production in Indonesia for the Year 2022 Using Pegel's Exponential Smoothing Method with Modified Golden Section Optimization</dc:title>
	<dc:creator xml:lang="en">Fitrah, Rahmi Nurul Ainun</dc:creator>
	<dc:creator xml:lang="en">Sahriman, Sitti</dc:creator>
	<dc:subject xml:lang="en">Pegel’s Eksponential Smoothing</dc:subject>
	<dc:subject xml:lang="en">Modified Golden Section</dc:subject>
	<dc:subject xml:lang="en">Dry Rubber</dc:subject>
	<dc:description xml:lang="en">Pegel’s Exponential Smoothing is a forecasting method that considers separating trend and seasonal aspects, with additive and multiplicative models. Pegel’s Exponential Smoothing has three parameters, α, β, and γ. Many possible parameter combinations may yield an optimal solution, so a modified Golden Section method is used. The principle of this method is to iteratively reduce the boundary area of x that may produce an optimal objective function value, systematically decreasing the number of search steps to minimize the number of trials. Data obtained from the Central Bureau of Statistics regarding the amount of dry rubber production in Indonesian plantations from January 2017 to December 2022 is assumed to contain a multiplicative seasonal effect due to the relatively unstable seasonal pattern heights. This study compares three trend models: no trend, additive trend, and multiplicative trend in the multiplicative seasonal Pegel’s Exponential Smoothing method. This study aims to predict the amount of dry rubber production in Indonesian plantations from January 2022 to December 2022. Forecast validation results show that the multiplicative trend in the multiplicative seasonal Pegel’s Exponential Smoothing method, with a MAPE of 3.389001% and an RMSE of 8,839.965080, has the best forecasting accuracy for this data compared to the other three trend models.</dc:description>
	<dc:description xml:lang="id">Pegel’s Eksponential Smoothing merupakan metode peramalan yang mempertimbangkan pemisah aspek tren dan musiman dimana modelnya bersifat aditif dan multiplikatif. Pegel’s Eksponential Smoothing memiliki tiga parameter, yaitu dan . Terdapat banyak kombinasi parameter yang mungkin menghasilkan solusi optimal sehingga digunakan modifikasi metode Golden Section, dimana prinsip dari metode ini yaitu mengurangi secara bertahap dan berulang wilayah batas yang mungkin menghasilkan nilai fungsi objektif optimum sehingga mampu meminimalkan jumlah percobaan. Data yang diperoleh dari Badan Pusat Statistik mengenai jumlah produksi karet kering perkebunan Indonesia periode Januari 2017-Desember 2022 diasumsikan mengandung efek musiman multiplikatif dikarenakan ketinggian pola musimannya relatif tidak stabil. Penelitian ini membandingkan 3 model tren yaitu tanpa tren, tren aditif, dan tren multiplikatif pada metode Pegel’s Eksponential Smoothing musiman multiplikatif. Tujuan dari penelitian ini yaitu untuk meramalkan jumlah produksi karet kering perkebunan Indonesia periode Januari 2022-Desember 2022. Validasi hasil peramalan menunjukkan bahwa metode Pegel’s Eksponential Smoothing musiman multiplikatif tren multiplikatif dengan nilai MAPE sebesar 3,389001% dan nilai RMSE sebesar 8.839,965080 adalah metode yang memiliki akurasi peramalan terbaik dalam meramalkan data tersebut dibanding dengan 3 model tren lainnya.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2025-01-12</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/37158</dc:identifier>
	<dc:identifier>10.20956/j.v21i2.37158</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 21 No. 2 (2025): JANUARY 2025; 368-381</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/37158/12434</dc:relation>
	<dc:coverage xml:lang="id">Peramalan</dc:coverage>
	<dc:rights xml:lang="en">Copyright (c) 2025 Jurnal Matematika, Statistika dan Komputasi</dc:rights>
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