Forecasting retail diesel prices in Malaysia using an ARIMA approach

Mohd Said, Rahaini and Hussin, Nor Hafizah and Noor Azhuan, Nur Azura and Mohd Yussoff, Nurul Hajar and Dzulkalnine, Mohamad Faiz (2025) Forecasting retail diesel prices in Malaysia using an ARIMA approach. Journal of Power and Energy Engineering, 13 (10). pp. 61-74. ISSN 2327-5901

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Abstract

Accurate forecasting of diesel prices is essential for Malaysia, where transportation, agriculture, and industry are highly dependent on this fuel. This study investigates the effectiveness of the Autoregressive Integrated Moving Average (ARIMA) model in predicting Malaysian retail diesel prices. Using the Box Jenkins methodology, the research process involves model identification, estimation, and validation. Data stationarity is assessed through visual inspection and the Augmented Dickey-Fuller (ADF) test, with first-order differencing applied to achieve non-stationarity. Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) analysis guide the parameter selection, leading to the estimation of several ARIMA (p, 1, q) models. Model adequacy is determined using the Akaike Information Criterion (AIC) with ARIMA (1, 1, 0) identified as the optimal specification. Performance evaluation based on Mean Squared Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) indicates high predictive accuracy, demonstrating the model’s robustness in capturing diesel price dynamics. The results practically provide value for policymakers and industry stakeholders by supporting evidence-based decision making, facilitating effective economic planning, and optimizing resource management.

Item Type:	Article
Uncontrolled Keywords:	Forecasting, Autoregressive integrated moving average (ARIMA), Diesel price, Autocorrelation function (ACF), Partial autocorrelation Function (PACF)
Divisions:	Faculty Of Electronics And Computer Technology And Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	02 Feb 2026 08:23
Last Modified:	02 Feb 2026 08:23
URI:	http://eprints.utem.edu.my/id/eprint/29393
Statistic Details:	View Download Statistic

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