International Journal of Mathematics Trends and Technology
Volume 68 | Issue 12 | Year 2022 | Article Id. IJMTT-V68I12P502 | DOI : https://doi.org/10.14445/22315373/IJMTT-V68I12P502
| Received | Revised | Accepted | Published |
|---|---|---|---|
| 15 Oct 2022 | 16 Nov 2022 | 29 Nov 2022 | 15 Dec 2022 |
The COVID-19 pandemic caused a decline in oil and gas exports from Indonesia in 2019. After some months, the Covid-19 pandemic started to improve slowly. This had an impact on the economy's recovery, which led to an increase in oil and gas exports once more. This article will use the Linear Regression approach and the Holt-Winters method to forecast the amount of oil and gas exported from Indonesia. In particular, the Holt-Winters method is subdivided into the Holt-Winters multiplicative and Holt-Winters additive. Comparing these three approaches, it is evident that the multiplicative Holt-Winters method is superior to the Linear Regression and Holt-Winters additive methods, which approach out-of-sample data for oil and gas volume forecasting in 2018. This is also directly related to the predictive power of the Holt-Winters multiplicative method, which may approach the actual data for six years longer than other methods. The Mean Absolute Error (MAE) of the three approaches indicates that the multiplicative error of the Holt-Winters method is less than that of the other two ways. Therefore, it may be inferred that the Holt-Winters multiplicative technique is superior for predicting Indonesian oil and gas exports.
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Nuraini Sibuea, Andi Rio Ramadhan, Ratna Tri Aulia, Siska Khairunnisa, Rado Yendra, Arisman Adnan, "Comparison of Linear Regression Method and Holt-Winters Method in Oil and Gas Export Volume Forecasting in Indonesia," International Journal of Mathematics Trends and Technology (IJMTT), vol. 68, no. 12, pp. 7-12, 2022. Crossref, https://doi.org/10.14445/22315373/IJMTT-V68I12P502
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