Estimation of Energy Demand in Indonesia using Artificial Neural Network

Satrio Mukti Wibowo, Dedi Hakim, Baba Barus and Akhmad Fauzi
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Satrio Mukti Wibowo: Ministry of Energy and Mineral Resources, Jakarta, 10110, Indonesia,
Baba Barus: Department of Soil and Land Resources, Faculty of Agriculture, Bogor Agricultural University, Bogor 16680, Indonesia.
Akhmad Fauzi: Faculty of Economy and Management, Bogor Agricultural University, Bogor 16680, Indonesia,

International Journal of Energy Economics and Policy, 2022, vol. 12, issue 6, 261-271

Abstract: Although Indonesia has many variations in energy types, Indonesia is currently a Net Oil Importer Country. Therefore, accurate energy demand estimation is very important for energy policy making in Indonesia. This study proposes a neural network model to efficiently, precisely and validly estimate energy demand for Indonesia. This model has four independent variables, such as gross domestic product (GDP), population, imports, and exports. Data obtained from Central Bureau of Statistics of Indonesia and The Ministry of Energy and Mineral Resources. Energy estimation is using a pessimistic, realistic and optimistic scenario that estimates of energy demand in the next 10 years using artificial neural networks shows that energy demand in Indonesia continues to increase every year, both in pessimistic, realistic and optimistic scenarios.

Keywords: energy demand; energy policy; artificial neural networks (search for similar items in EconPapers)
JEL-codes: Q41 Q47 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eco:journ2:2022-06-33

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