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Emerensye S.Y. Pandie
Universitas Nusa Cendana
Computer Science & IT

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Implementasi Metode Backpropagation Untuk Memprediksi Beban Listrik Di Kabupaten Sikka Maria Olinda Harun; Sebastianus A.S Mola; Emerensye S.Y. Pandie
J-Icon : Jurnal Komputer dan Informatika Vol 4 No 1 (2016): Maret 2016
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v4i1.1397

Abstract

Electric energy is one of the tools to support the welfare of society. Their population grow and their activities increase, therefore, their need of electricity is increasing too. The electricity almost cover up the area of Sikka Region. Based on the real data, the electrical load is increased every month. In order to reach the balance between the productivity of electric energy and the consumption of electric energy, then, the electrical provider should know the electrical load for the future.Backpropagation method is one of the methods at artificial neural network which can be used in this research to predict the electrical load for the next one month. The backpropagation method consists of some steps such as training, data testing and prediction.The data which used as a paramater in this research is the data of electrical load (KWH carry), numbers of consumers and the data of connected electrical power. The researcher used the data January 2007 until December 2012 as learning process, and for the testing, the researcher used data from January 2013 until December 2013.The result of this application is the load power consumption for the next one montj in Sikka Regency. The presentation of final result of this testing for the data that has been trained is 85% and the data which never been trained is 80%. Because of the presentation is above 50% the backpropagation can be used to predict the electrical load for the next one month.
Co-Authors Maria Olinda Harun Sebastianus A.S Mola