PREDICTION OF CRUDE OIL PRICES IN INDONESIA USING FOURIER SERIES ESTIMATOR AND ARIMA METHOD

  • Alma Khalisa Rahma Mathematics Department, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Qumadha Zaenal Abidin Mathematics Department, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Juan Krisfigo Prasetyo Mathematics Department, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Berliani Larasati Mathematics Department, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Dita Amelia Mathematics Department, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0000-0002-2387-9981
  • Nur Chamidah Mathematics Department, Faculty of Science and Technology, Universitas Airlangga, Indonesia
DOI: https://doi.org/10.30598/barekengvol18iss3pp1673-1682
Keywords: Crude Oil, ARIMA, Forecasting, Fourier Series Estimator

Abstract

Crude oil is one of the non-renewable natural resources that is crucial for countries around the world in driving economic development. However, the availability of crude oil is decreasing over time. The high demand for crude oil results in scarcity which causes price fluctuations. Low oil prices can reduce state revenues, disrupt development programs, and even trigger budget deficits. On the other hand, an increase in crude oil prices can make a positive contribution to state revenues. Crude oil exports become more profitable, which can increase state revenue through royalties and taxes levied on the oil and gas sector. This additional revenue can be used to support infrastructure development, social programs, and investment in key sectors of the economy. High oil prices can also harm the economy. With the many impacts that can be caused by crude oil prices, the government must be able to anticipate and prepare for it.  The data used in this study are data on crude oil prices in Indonesia for monthly periods from January 2018 to October 2023 sourced from the official website of the Ministry of Energy and Mineral Resources (ESDM) of the Republic of Indonesia. The researcher tried to compare two analysis methods, namely the Fourier series and the ARIMA estimator. The results of this study show that the best method in predicting crude oil prices in Indonesia is the Fourier series estimator with Cos-Sin function which produces RMSE and MAPE values of 7.93 and 8.4%. The prediction results can be used as a reference for the government to anticipate and make programs or policies that are more focused and targeted toward the impacts that can be caused by changes in crude oil prices.

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Published
2024-07-31
How to Cite
[1]
A. Rahma, Q. Abidin, J. Prasetyo, B. Larasati, D. Amelia, and N. Chamidah, “PREDICTION OF CRUDE OIL PRICES IN INDONESIA USING FOURIER SERIES ESTIMATOR AND ARIMA METHOD”, BAREKENG: J. Math. & App., vol. 18, no. 3, pp. 1673-1682, Jul. 2024.
Issue
Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Section
Articles

Copyright (c) 2024 Alma Khalisa Rahma, Qumadha Zaenal Abidin, Juan Krisfigo Prasetyo, Berliani Larasati, Dita Amelia, Nur Chamidah

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