A Comparison of α-Sutte Indicator and ARIMA Methods in Renewable Energy Forecasting in Indonesia

  • Abstract
  • Keywords
  • References
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  • Abstract

    Humans in this world are very dependent on petroleum and energy. Petroleum and other energies are a major source in supporting human life. Regarding the reduced petroleum availability, a new energy is needed to replace the role of petroleum. Nowadays, there is much renewable energy that have been discovered and used. The purpose of this research is to predict the total primary energy supply in Indonesia by using α-Sutte Indicator and ARIMA method, and comparing those four methods which are effective in predicting data. Data from the research is renewable energy (total primary energy supply) which is obtained from OECD from 1971-2015. From the research, it is found that the α-Sutte Indicator method is more suitable to predict renewable energy (total primary energy supply) data in Indonesia compared to ARIMA (0,1,0).


  • Keywords

    α-Sutte Indicator, ARIMA, Forecasting renewable energy.

  • References

      [1] P. Kuncahyo, A. Z. M. Fathallah, and Semin, “Analisa Prediksi Potensi Bahan Baku Biodiesel sebagai Suplemen Bahan Bakar Motor Diesel di Indoesia,” J. Tek. ITS, vol. 2, no. 1, pp. B62–B66, Mar. 2013.

      [2] OECD, “Renewable energy (indicator),” 2018. [Online]. Available: http://www.oecd-ilibrary.org/energy/renewable-energy/indicator/english_aac7c3f1-en. [Accessed: 08-Jan-2018].

      [3] A. Rahman and A. S. Ahmar, “Forecasting of primary energy consumption data in the United States: A comparison between ARIMA and Holter-Winters models,” in AIP Conference Proceedings, 2017, vol. 1885.

      [4] A. S. Ahmar, A. Rahman, A. N. M. Arifin, and A. A. Ahmar, “Predicting movement of stock of ‘Y’ using sutte indicator,” Cogent Econ. Financ., vol. 5, no. 1, 2017.

      [5] A. S. Ahmar, “Sutte Indicator : A Technical Indicator in Stock Market,” Int. J. Econ. Financ. Issues, vol. 7, no. 2, 2017.

      [6] A. S. Ahmar et al., “Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO),” J. Phys. Conf. Ser., vol. 954, no. 1, 2018.

      [7] A. S. Ahmar, “sutteForecastR: Forecasting Data using Alpha-Sutte Indicator,” 2017. [Online]. Available: https://cran.r-project.org/web/packages/sutteForecastR/index.html.

      [8] A. S. Ahmar, A. Rahman, and U. Mulbar, “A New Method for Time Series Forecasting: α- Sutte Indicator,” J. Phys. Conf. Ser., 2018.

      [9] K. Balasaravanan and M. Prakash, “Detection of dengue disease using artificial neural network based classification technique,” Int. J. Eng. Technol., vol. 7, no. 1.3, pp. 13–15, 2017.

      [10] T. T. Khuat and M. H. Le, “An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction Problem,” JOIV Int. J. Informatics Vis., vol. 1, no. 2, pp. 40–49, 2017.

      [11] A. S. Ahmar, “The Implementation of α-Sutte Indicator to Forecasting Data,” J. Phys. Conf. Ser., 2018.

      [12] A. S. Ahmar, “sutteForecastR: an R Package for Forecasting Data,” J. Phys. Conf. Ser., 2018.

      [13] A. S. Ahmar, “RcmdrPlugin.sutteForecastR: a plugin in Rcmdr for Forecasting Data,” J. Phys. Conf. Ser., 2018.

      [14] A. S. Ahmar, “RcmdrPlugin. sutteForecastR:’Rcmdr’Plugin for Alpha-Sutte Indicator,” 2017. [Online]. Available: https://cran.r-project.org/web/packages/RcmdrPlugin.sutteForecastR/index.html.




Article ID: 12319
DOI: 10.14419/ijet.v7i1.6.12319

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