PREDIKSI KEBUTUHAN ENERGI LISTRIK SULAWESI UTARA MENGGUNAKAN ARTIFICIAL NEURAL NETWORK DAN METODE EXPONENTIAL SMOOTHING

Authors

  • Febry Aprily Hontong
  • Tritiya Arungpadang
  • Johan S C Neyland

Abstract

To predict the electrical energy need of North Sulawesi for one year ahead requires correct methods. The reliable methods used for the prediction task in this research are Artificial Neural Network and Exponential Smoothing.

The prediction results using Artificial Neural Network are 110.38, 112.62, 111.56, 108.05, 107.95, 110.32, 109.90, 110.58, 113.26, 107.11, 115.60, 105.40 GWh. The prediction results using Exponential Smoothing are 112.32, 112.70, 113.07, 113.45, 113.82, 114.19, 114.57, 114.94, 115.32, 115.69, 116.07, 116.44 GWh.

 

Key words: Artificial Neural Network, Exponential Smoothing, Prediction, Electrical Energy Need.

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Published

2016-10-25

Issue

Vol. 5 No. 2 (2016): Jurnal Poros Teknik Mesin Unsrat

Section

Articles

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How to Cite

PREDIKSI KEBUTUHAN ENERGI LISTRIK SULAWESI UTARA MENGGUNAKAN ARTIFICIAL NEURAL NETWORK DAN METODE EXPONENTIAL SMOOTHING. (2016). Jurnal Poros Teknik Mesin UNSRAT, 5(2). https://ejournal.unsrat.ac.id/v3/index.php/poros/article/view/13789