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Comparison of Forecasting Using Fuzzy Time Series Chen Model and Lee Model to Foreign Exchange in EUR/USD and GBP/USD

Journal of Advances in Information Systems and Technology · Vol. 3 No. 1 (2021) · hlm. 61–66

DOI
10.15294/jaist.v3i1.49096
ISSN
2715-999X, 2714-9714
Terbit
2021-04-14
Penerbit
Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Each country has a currency value that applies in its territory and can be adjusted to the value of the currency of other countries. In this adjustment, there is a difference in value when the transaction is made, and the difference in profit can be taken, usually referred to as foreign exchange (forex). In forex trading, analytical calculations are needed to plan a decision to get a significant difference so that the profits will increase. One analysis technique that can maximize the search for an enormous profit difference is by using the prediction method using the fuzzy time series. This method is a method that predicts future data based on historical data or past data. The fuzzy time series method has several models, including the Chen model and Lee model. In determining which model is the best, it is necessary to test using the AFER (average forecasting error rate) based on the level of accuracy of the smallest error value. By using historical data of EUR/USD and GBP/USD from 19 February 2019 to 19 February 2020, it is known that Lee’s fuzzy time series method predicts better accuracy because Chen’s model in foreign currency EUR/USD has a more significant error rate of 0.0018 (0.18%) or greater than Lee’s model which only has a value of 0.0016 (0.16%). Then the Chen model in foreign currency GBP/USD has an error rate of 0.00445 (0.445%) or greater than the Lee model, which only has an error rate of 0.00297 (0.297%).

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  • State University of Semarang
  • National University of Malaysia
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Rekan penulisOrganisasiArtikel bersama
Deonisius Germandy Cahaya PutraState University of Semarang2
Vivi WulandariState University of Semarang2
Resta AdityatamaState University of Semarang2
Muh. SholehState University of Semarang1
Martanto Setyo HusodoState University of Semarang1
Taripar Matius AlexanderState University of Semarang1
Florentina Yuni AriniState University of Semarang1
Riza ArifudinState University of Semarang1
Athoillah AthoillahState University of Semarang1
Cahya WulandariState University of Semarang1
Muhamad Sayuti HassanNational University of Malaysia1
Zidney Ilma Fazaada EmhaState University of Semarang1
Sugianto SugiantoState University of Semarang1
Angel Novita SinuratState University of Semarang1
Tazkiyatun Aeni AmaliyahState University of Semarang1
Ahmad WarsunState University of Semarang1
Pradistia Edo KristiantoState University of Semarang1
Annisya Dira PrastiwiState University of Semarang1
Adham Satria FirmansyahState University of Semarang1
Luthfi Ilham Agus PratamaState University of Semarang1
Muhammad Zaenal MuttaqinState University of Semarang1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/jaist/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Comparison of Forecasting Using Fuzzy Time Series Chen Model and Lee Model to Foreign Exchange in EUR/USD and GBP/USD</dc:title>
	<dc:creator>Syehudin, Syehudin</dc:creator>
	<dc:creator>Putra, Anggyi Trisnawan</dc:creator>
	<dc:description xml:lang="en-US">Each country has a currency value that applies in its territory and can be adjusted to the value of the currency of other countries. In this adjustment, there is a difference in value when the transaction is made, and the difference in profit can be taken, usually referred to as foreign exchange (forex). In forex trading, analytical calculations are needed to plan a decision to get a significant difference so that the profits will increase. One analysis technique that can maximize the search for an enormous profit difference is by using the prediction method using the fuzzy time series. This method is a method that predicts future data based on historical data or past data. The fuzzy time series method has several models, including the Chen model and Lee model. In determining which model is the best, it is necessary to test using the AFER (average forecasting error rate) based on the level of accuracy of the smallest error value. By using historical data of EUR/USD and GBP/USD from 19 February 2019 to 19 February 2020, it is known that Lee’s fuzzy time series method predicts better accuracy because Chen’s model in foreign currency EUR/USD has a more significant error rate of 0.0018 (0.18%) or greater than Lee’s model which only has a value of 0.0016 (0.16%). Then the Chen model in foreign currency GBP/USD has an error rate of 0.00445 (0.445%) or greater than the Lee model, which only has an error rate of 0.00297 (0.297%).</dc:description>
	<dc:publisher xml:lang="en-US">Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang</dc:publisher>
	<dc:date>2021-04-14</dc:date>
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	<dc:identifier>10.15294/jaist.v3i1.49096</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Advances in Information Systems and Technology; Vol 3 No 1 (2021): April; 61-66</dc:source>
	<dc:source>2715-999X</dc:source>
	<dc:source>2714-9714</dc:source>
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	<dc:rights xml:lang="en-US">Copyright (c) 2021 Journal of Advances in Information Systems and Technology</dc:rights>
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