Time series analysis on sales data of petroleum in Malaysia
In Malaysia, the energy sector is an important driver of economic growth. We all know that oil and natural gas are the two major industries of the energy market. Malaysia is the second-largest oil producer in Southeast Asia and the world’s third largest exporter of liquefied natural gas (LNG). Petro...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universiti Teknologi Malaysia
2023
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| Subjects: | |
| Online Access: | http://eprints.utm.my/108597/1/AdinaNajwa2023_TimeSeriesAnalysisonSalesData.pdf http://eprints.utm.my/108597/ https://science.utm.my/procscimath/2023-2/vol-18/ |
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| Summary: | In Malaysia, the energy sector is an important driver of economic growth. We all know that oil and natural gas are the two major industries of the energy market. Malaysia is the second-largest oil producer in Southeast Asia and the world’s third largest exporter of liquefied natural gas (LNG). Petronas has held exclusive ownership rights over all exploration and production activities related to oil and natural gas in the country since its inception. Throughout the years, there are several issues that affect the sales data of petroleum in Malaysia since the prices are influenced by global supply and demand. This project is based on the time series analysis of monthly sales of petroleum in Petronas Malaysia from the year of 2017 to 2022. The significance of this project is to study the trend and determine the best forecasting model between Exponential Smoothing and Autoregressive Integrated Moving Average (ARIMA) for monthly sales of petroleum in Petronas. The performance of the models are then compared by the values of Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The outcome showed that, in comparison to Exponential Smoothing, the chosen ARIMA model forecasts more accurately. |
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