Cheng Fuzzy Time Series Model to Forecast the Price of Crude Oil in Malaysia

Jasmani Bidin; Noorzila Sharif; Sharifah Fhahriyah Syed Abas; Ku Azlina Ku Akil; Nurul Aqilah Abdullah

doi:10.24191/jcrinn.v7i2.304

Cheng Fuzzy Time Series Model to Forecast the Price of Crude Oil in Malaysia

Authors

Jasmani Bidin UiTM Perlis
Noorzila Sharif Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis Branch
Sharifah Fhahriyah Syed Abas Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis Branch
Ku Azlina Ku Akil Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis Branch
Nurul Aqilah Abdullah Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis Branch

DOI:

https://doi.org/10.24191/jcrinn.v7i2.304

Keywords:

Crude Oil price forecasting, forecasting, Fuzzy Time Series, Time Series, Cheng Fuzzy Time Series

Abstract

Crude oil is one of the important commodities to Malaysia. As a producer and exporter of oil and gas, Malaysia has gained high Gross Revenue from this sector. Crude oil is the global commodity and highly demanded. Therefore, major price changes on the commodity have a significant influence on world economy. Market sentiment, demand, and supply are some elements directly influencing the oil prices. Since crude oil is the backbone of businesses and is extremely important to the economy, it is essential to study the price of crude oil for future planning purposes. For that reason, this study proposes the use of the Fuzzy Time Series Cheng to predict crude oil price in Malaysia. In this study, Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) are used to evaluate the forecast performance. The result shows that Fuzzy Time Series Cheng is able to produce a good result in forecasting since the analyses shows that the low value of RMSE and MAPE (less than 10 percent). Although this is the fundamental study but the finding may assist many sectors in Malaysia, such as governments, enterprises, investors, and businesses to produce a better economic planning in the future especially after the pandemic covid-19 phase.

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