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Penerapan Extreme Learning Machine Dalam Meramalkan Harga Minyak Sawit Mentah

KUBIK: Jurnal Publikasi Ilmiah Matematika · Vol. 7 No. 2 (2023) · hlm. 97–105

DOI
10.15575/kubik.v7i2.20460
ISSN
2686-0341, 2338-0896
Terbit
2023-06-05
Penerbit
Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung
Bahasa
ind

Abstrak

The need for crude palm oil has increased due to the large demand for vegetable oils in various parts of the world. Beginning in March 2022, the price of crude palm oil set a record high which caused international cooking oil prices to soar, especially for Indonesia. This study aims to predict the price of crude palm oil with test parameters, namely hidden neurons and activation functions. The method used is Extreme Learning Machine (ELM). This method is a development of the artificial neural network (ANN) method which can overcome weaknesses in the learning speed process. There are several stages in this study: (1) pre-processing the data by normalizing the data and dividing the data using the time series split method, (2) analyzing the data using the ELM method by testing parameters, namely hidden neurons and activation functions, (3) analyzing the results of the best parameter trials, (4) calculating forecasting data using the best parameters that have been obtained, and (5) analyzing the forecasting results that have been obtained. This study uses daily data on the price of crude palm oil from April 1 2021 to April 14 2022 obtained from the Investing website. The results of the research that has been carried out obtained MAPE and RMSE values of 0.0173 and 0.0308 with the best parameters namely the number of hidden neurons of 5 and the binary sigmoid activation function. Based on the results obtained, it is hoped that it will make it easier for the government to determine the price of crude palm oil in the future.

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  • UIN Sunan Ampel Surabaya
  • Politeknik Elektronika Negeri Surabaya
  • Hasanuddin University
  • University of Indonesia
  • State University of Semarang
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
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Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Moh. HafiyusholehUIN Sunan Ampel Surabaya2
Halimatus Sa’dyahPoliteknik Elektronika Negeri Surabaya1
Nilna AlmumtazahUIN Sunan Ampel Surabaya1
Muhammad Sahrul KiromiUIN Sunan Ampel Surabaya1
Yuniar FaridaUIN Sunan Ampel Surabaya1
Ida PurwantiUIN Sunan Ampel Surabaya1
Wika Dianita UtamiUIN Sunan Ampel Surabaya1
Shafa Fitria Aqilah KhansaUIN Sunan Ampel Surabaya1
Fery FirmansyahAfiliasi tidak diketahui1
Hani KhaulasariUIN Sunan Ampel Surabaya1
Yanuwar ReinaldiUIN Sunan Ampel Surabaya1
Tuti BahfiartiHasanuddin University1
Alem Febri SonniAfiliasi tidak diketahui1
Dinar WahyuningrumAfiliasi tidak diketahui1
Puji HardatiAfiliasi tidak diketahui1
Denny SetiawanUniversity of Indonesia1
Della Raymena JovankaAfiliasi tidak diketahui1
Tarissa Putri HanifahAfiliasi tidak diketahui1
Floribertus Bujana Adi PradanaAfiliasi tidak diketahui1
Muhammad Fathan Zahran DikaAfiliasi tidak diketahui1
Afra YasminAfiliasi tidak diketahui1
Asep KadarohmanAfiliasi tidak diketahui1
Asyti FeblizaAfiliasi tidak diketahui1
Norazilawati AbdullahAfiliasi tidak diketahui1
Afakhrul Masub BakhtiarAfiliasi tidak diketahui1
Sugiyo SugiyoAfiliasi tidak diketahui1
Sinta SaraswatiAfiliasi tidak diketahui1
Saiful RidloState University of Semarang1
DIAN NISA ISTOFAAfiliasi tidak diketahui1
Dion GinantoAfiliasi tidak diketahui1
T. Rykard Yudha PratamaAfiliasi tidak diketahui1
Aqwa Naser DaulayAfiliasi tidak diketahui1
Habib Lauda NararyaAfiliasi tidak diketahui1
Eddy Pahar HarahapAfiliasi tidak diketahui1
Muthmainnah IsmailAfiliasi tidak diketahui1
Lina AmeliaAfiliasi tidak diketahui1
Findya PuspitasariAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://journal.uinsgd.ac.id/index.php/kubik/oai, pertama di-harvest 7 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="id-ID">Penerapan Extreme Learning Machine Dalam Meramalkan Harga Minyak Sawit Mentah</dc:title>
	<dc:creator>Aisyah, Siti</dc:creator>
	<dc:creator>Ulinnuha, Nurissaidah</dc:creator>
	<dc:creator>Hamid, Abdulloh</dc:creator>
	<dc:subject xml:lang="id-ID">Crude Palm Oil</dc:subject>
	<dc:subject xml:lang="id-ID">Extreme Learning Machine</dc:subject>
	<dc:subject xml:lang="id-ID">Time Series Split</dc:subject>
	<dc:description xml:lang="id-ID">The need for crude palm oil has increased due to the large demand for vegetable oils in various parts of the world. Beginning in March 2022, the price of crude palm oil set a record high which caused international cooking oil prices to soar, especially for Indonesia. This study aims to predict the price of crude palm oil with test parameters, namely hidden neurons and activation functions. The method used is Extreme Learning Machine (ELM). This method is a development of the artificial neural network (ANN) method which can overcome weaknesses in the learning speed process. There are several stages in this study: (1) pre-processing the data by normalizing the data and dividing the data using the time series split method, (2) analyzing the data using the ELM method by testing parameters, namely hidden neurons and activation functions, (3) analyzing the results of the best parameter trials, (4) calculating forecasting data using the best parameters that have been obtained, and (5) analyzing the forecasting results that have been obtained. This study uses daily data on the price of crude palm oil from April 1 2021 to April 14 2022 obtained from the Investing website. The results of the research that has been carried out obtained MAPE and RMSE values of 0.0173 and 0.0308 with the best parameters namely the number of hidden neurons of 5 and the binary sigmoid activation function. Based on the results obtained, it is hoped that it will make it easier for the government to determine the price of crude palm oil in the future.</dc:description>
	<dc:publisher xml:lang="en-US">Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung</dc:publisher>
	<dc:date>2023-06-05</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.uinsgd.ac.id/index.php/kubik/article/view/20460</dc:identifier>
	<dc:identifier>10.15575/kubik.v7i2.20460</dc:identifier>
	<dc:source xml:lang="en-US">KUBIK: Jurnal Publikasi Ilmiah Matematika; Vol. 7 No. 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika; 97-105</dc:source>
	<dc:source xml:lang="id-ID">KUBIK; Vol 7 No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika; 97-105</dc:source>
	<dc:source>2686-0341</dc:source>
	<dc:source>2338-0896</dc:source>
	<dc:source>10.15575/kubik.v7i2</dc:source>
	<dc:language>ind</dc:language>
	<dc:relation>https://journal.uinsgd.ac.id/index.php/kubik/article/view/20460/9058</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Siti Aisyah, Nurissaidah Ulinnuha, Abdulloh Hamid</dc:rights>
</oai_dc:dc>