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IMPLEMENTATION OF FUZZY TIME SERIES CHEN FOR FORECASTING INDONESIAN OIL AND GAS IMPORTS VALUE

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 2 (2023) · pp. 0685–0694

DOI
10.30598/barekengvol17iss2pp0685-0694
ISSN
2615-3017, 1978-7227
Published
2023-06-11
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Indonesia is an importing country that frequently imports goods from abroad continuously every year. Imported goods are oil and gas and non-oil and gas. Oil and gas includes oil and gas. This oil and gas import value data is an example of time series data, where the data is obtained from data recapitulation at the Central Bureau of Statistics (BPS). Time series analysis is a method for predicting an event that will come by looking at data from the previous time. One of the newest methods of time series analysis used in this research is Fuzzy Time Series Chen method. The purpose of this research is to find out how the implementation of Fuzzy Time Series Chen method in predicting the value of Indonesian oil and gas imports and to know the results of forecasting the value of Indonesian oil and gas imports. In predicting the value of Indonesia's oil and gas imports using Fuzzy Time Series Chen method, the results of forecasting the value of Indonesia's oil and gas imports in August 2022 were US$ 3743.213 million with a MAPE value of 19.969%.

Collaboration network of the authors

18 authors · 48 co-authorship links · 9 across different organisations

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  • University of Bengkulu
  • State University of Jakarta
  • IPB University
  • Universitas Gadjah Mada
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
José RizalUniversity of Bengkulu4
Vivin AcnesyaUniversity of Bengkulu3
Zulfia Memi MayasariUniversity of Bengkulu2
Anggel Dwi MirandaUniversity of Bengkulu2
Ratna WidayatiUniversitas Gadjah Mada2
Nurul HidayatiIPB University2
Bunga Aulya WarrahmaUniversity of Bengkulu2
PRIHATIN SIHOTANGUniversity of Bengkulu2
Muhammad Arib AlwansyahState University of Jakarta1
Ramya RachmawatiUniversity of Bengkulu1
Fachri FaisalUniversity of Bengkulu1
Mulia AstutiUniversity of Bengkulu1
Nur AfandiUniversity of Bengkulu1
Refpo RahmanUniversity of Bengkulu1
Ramya RachmawatiAffiliation 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://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">IMPLEMENTATION OF FUZZY TIME SERIES CHEN FOR FORECASTING INDONESIAN OIL AND GAS IMPORTS VALUE</dc:title>
	<dc:creator>Damayanti, Septri</dc:creator>
	<dc:creator>Yosmar, Siska</dc:creator>
	<dc:creator>Afandi, Nur</dc:creator>
	<dc:description xml:lang="en-US">Indonesia is an importing country that frequently imports goods from abroad continuously every year. Imported goods are oil and gas and non-oil and gas. Oil and gas includes oil and gas. This oil and gas import value data is an example of time series data, where the data is obtained from data recapitulation at the Central Bureau of Statistics (BPS). Time series analysis is a method for predicting an event that will come by looking at data from the previous time. One of the newest methods of time series analysis used in this research is Fuzzy Time Series Chen method. The purpose of this research is to find out how the implementation of&amp;nbsp; Fuzzy Time Series Chen method in predicting the value of Indonesian oil and gas imports and to know the results of forecasting the value of Indonesian oil and gas imports. In predicting the value of Indonesia's oil and gas imports using Fuzzy Time Series Chen method, the results of forecasting the value of Indonesia's oil and gas imports in August 2022 were US$ 3743.213 million with a MAPE value of 19.969%.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-06-11</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/7445</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss2pp0685-0694</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications; 0685-0694</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss2year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7445/5930</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Septri Damayanti, Siska Yosmar, Nur Afandi</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>