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TIME SERIES MODELING OF NATURAL GAS FUTURE PRICE WITH FUZZY TIME SERIES CHEN, LEE AND TSAUR

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 16 No. 4 (2022) · pp. 1185–1196

DOI
10.30598/barekengvol16iss4pp1185-1196
ISSN
2615-3017, 1978-7227
Published
2022-12-15
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Investment is the process of investing money or capital for profit or material results. The investor carefully calculates the investment object to minimize losses and maximize profits. One of the essential investment objects is the futures price of natural gas considered a commodity that plays a vital role in the Indonesian economy. The movement of natural gas futures prices can be modeled using a time series model. The data in the time series model is believed to have particular pattern to model the data in the future. The natural gas futures price is modeled into a time series method by using fuzzy time series (FTS) approach of the FTS Chen, Lee and Tsaur. Model accuracy is calculated using the criteria of Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The three FTS methods have good performance of accuracy for this time series data, where FTS Tsaur as fuzzy times series approach with average based method shows the best results with the smallest error rate to the data of natural gas future price.

Collaboration network of the authors

18 authors · 38 co-authorship links

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  • Universitas Muhammadiyah Madiun
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Ferra YanuarAffiliation unknown5
Rudiyanto RudiyantoAffiliation unknown2
Lilis Harianti HasibuanAffiliation unknown2
SRI WAHYUNIAffiliation unknown1
Fery MurtiningrumAffiliation unknown1
Melinda NoerAffiliation unknown1
Frilianda WulandariAffiliation unknown1
Izzati RahmiAffiliation unknown1
Latifah ZahraAffiliation unknown1
Ridho SaputraAffiliation unknown1
Alvi Khairin NisaAffiliation unknown1
Nia RamadhaniAffiliation unknown1
Mawanda AlmuhayarAffiliation unknown1
Cici SaputriAffiliation unknown1
Muhammad Qolbi ShobriUniversitas Muhammadiyah Madiun1

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://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">TIME SERIES MODELING OF NATURAL GAS FUTURE PRICE WITH FUZZY TIME SERIES CHEN, LEE AND TSAUR</dc:title>
	<dc:creator>Devianto, Dodi</dc:creator>
	<dc:creator>Zuardin, Aulia</dc:creator>
	<dc:creator>Maiyastri, Maiyastri</dc:creator>
	<dc:description xml:lang="en-US">Investment is the process of investing money or capital for profit or material results. The investor carefully calculates the investment object to minimize losses and maximize profits. One of the essential investment objects is the futures price of natural gas considered a commodity that plays a vital role in the Indonesian economy. The movement of natural gas futures prices can be modeled using a time series model. The data in the time series model is believed to have particular pattern to model the data in the future. The natural gas futures price is modeled into a time series method by using fuzzy time series (FTS) approach of the FTS Chen, Lee and Tsaur. Model accuracy is calculated using the criteria of Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The three FTS methods have good performance of accuracy for this time series data, where FTS Tsaur as fuzzy times series approach with average based method shows the best results with the smallest error rate to the data of natural gas future price.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2022-12-15</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://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5888</dc:identifier>
	<dc:identifier>10.30598/barekengvol16iss4pp1185-1196</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications; 1185-1196</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol16iss4year2022</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5888/5135</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Dodi Devianto, Aulia Zuardin, Maiyastri Maiyastri</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>