THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIA

  • Erdanisa Aghnia Ilmani Statistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, Indonesia https://orcid.org/0009-0007-0972-7248
  • Fida Fariha Amatullah Statistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, Indonesia https://orcid.org/0009-0005-6140-7458
  • Khairil Anwar Notodiputro Statistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, Indonesia https://orcid.org/0000-0003-2892-4689
  • Yenni Angraini Statistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, Indonesia https://orcid.org/0000-0003-3186-2378
  • Laily Nissa Atul Mualifah Statistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, Indonesia https://orcid.org/0000-0002-5722-8431
DOI: https://doi.org/10.30598/barekengvol19iss2pp819-828
Keywords: ARIMAX, Cooking Oil Prices, Forecasting

Abstract

Forecasting is crucial for planning, particularly in addressing potential issues. While ARIMA models are commonly used for time series forecasting, they may need more accuracy by overlooking external factors. The ARIMAX model, which incorporates exogenous variables, is employed to enhance accuracy. This study applies the ARIMAX model to forecast cooking oil prices in Indonesia, known for its complex patterns. Using data from the Directorate General of Domestic Trade and Price Stability (2024), the research highlights fluctuating cooking oil prices from 2010 to 2023 every month. Both ARIMA and ARIMAX models are utilized, with domestic fresh fruit bunch (FFB) prices and the COVID-19 pandemic indicator as exogenous variables. Evaluation based on Mean Absolute Percentage Error (MAPE) shows that the ARIMAX model has a MAPE of 17.31%, compared to 17.69% for the ARIMA model. The lower MAPE value for ARIMAX indicates improved forecasting accuracy by incorporating external factors. Thus, the ARIMAX model is recommended for predicting cooking oil prices, offering better accuracy and valuable insights for policymakers and stakeholders.

 

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Published
2025-04-01
How to Cite
[1]
E. A. Ilmani, F. F. Amatullah, K. A. Notodiputro, Y. Angraini, and L. N. A. Mualifah, “THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIA”, BAREKENG: J. Math. & App., vol. 19, no. 2, pp. 819-828, Apr. 2025.
Issue
Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Section
Articles

Copyright (c) 2025 Erdanisa Aghnia Ilmani, Fida Fariha Amatullah, Khairil Anwar Notodiputro, Yenni Angraini, Laily Nissa Atul Mualifah

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