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Application of Lee’s Fuzzy Time Series on Gold Price Forecasting in Padang City

Mathematical Sciences and Applications Journal · Vol. 5 No. 2 (2025) · hlm. 43–48

DOI
10.22437/msa.v5i2.37660
ISSN
2988-6481
Terbit
2025-07-23
Penerbit
Department of Mathematics, Faculty of Science and Technology Universitas Jambi
Bahasa
en

Abstrak

Gold price forecasting is important due to the asset’s role as a hedge against inflation and economic instability. However, its fluctuating nature makes accurate prediction challenging. Fuzzy Time Series (FTS), particularly the model developed by Lee, offers an effective method by incorporating fuzzy logic and refined interval formation. This study applies Lee’s FTS model to forecast monthly gold prices in Padang City using historical data from January 2017 to December 2023. The analysis includes data fuzzification, construction of fuzzy logical relationships, and defuzzification to obtain predicted values. The results show that the model achieved high forecasting accuracy, with a MAPE of 0.012%, MSE of 172358814,7, and RMSE of 13128,5496 indicating strong performance for short-term prediction.

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Sumber metadata: OAI-PMH (metadata jurnal) https://online-journal.unja.ac.id/index.php/msa/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">Application of Lee’s Fuzzy Time Series on Gold Price Forecasting in Padang City</dc:title>
	<dc:creator xml:lang="en">Dzakiyah, Arifah</dc:creator>
	<dc:creator xml:lang="en">Putri, Darvi Mailisa</dc:creator>
	<dc:subject xml:lang="en">Fuzzy Time Series Lee</dc:subject>
	<dc:subject xml:lang="en">Gold Price</dc:subject>
	<dc:subject xml:lang="en">Forecasting</dc:subject>
	<dc:description xml:lang="en">



Gold price forecasting is important due to the asset’s role as a hedge against inflation and economic instability. However, its fluctuating nature makes accurate prediction challenging. Fuzzy Time Series (FTS), particularly the model developed by Lee, offers an effective method by incorporating fuzzy logic and refined interval formation. This study applies Lee’s FTS model to forecast monthly gold prices in Padang City using historical data from January 2017 to December 2023. The analysis includes data fuzzification, construction of fuzzy logical relationships, and defuzzification to obtain predicted values. The results show that the model achieved high forecasting accuracy, with a MAPE of 0.012%, MSE of 172358814,7, and RMSE of 13128,5496 indicating strong performance for short-term prediction.



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	<dc:publisher xml:lang="en">Department of Mathematics, Faculty of Science and Technology Universitas Jambi</dc:publisher>
	<dc:date>2025-07-23</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">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://online-journal.unja.ac.id/msa/article/view/37660</dc:identifier>
	<dc:identifier>10.22437/msa.v5i2.37660</dc:identifier>
	<dc:source xml:lang="en">Mathematical Sciences and Applications Journal; Vol. 5 No. 2 (2025): Mathematical Sciences and Applications; 43-48</dc:source>
	<dc:source>2988-6481</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://online-journal.unja.ac.id/msa/article/view/37660/21619</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Mathematical Sciences and Applications Journal</dc:rights>
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