Peramalan Energi Listrik Jangka Panjang di Kabupaten Sampang Pasca Suramadu Mengunakan Metode Jaring Saraf Tiruan Counterpropagation Termodifikasi (Electric Energy Long Term Forecasting in Sampang Regency Post Suramadu Using Modified Counterpropagation Artificial Neural Network Method)

Amirullah, Amirullah and Ananda, Adi (2014) Peramalan Energi Listrik Jangka Panjang di Kabupaten Sampang Pasca Suramadu Mengunakan Metode Jaring Saraf Tiruan Counterpropagation Termodifikasi (Electric Energy Long Term Forecasting in Sampang Regency Post Suramadu Using Modified Counterpropagation Artificial Neural Network Method). SAINTEK, 11 (1). pp. 21-32. ISSN 1693-8917

	Text [22] Jurnal Saintek Vol 11 No 1 Juni 2014.pdf Download (3MB)
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Abstract

The objective of research is forecast the long-term electricity needs in Sampang Regency intelligently and accurately. Forecasting is done to provide early predictions about the long-term electricity needs in Sampang regency adequately. Fuzzy Analytic Hierarchy Process Method is used to determine the variable data to be selected as the input Modified Counterpropagation forecasting using ANN. The results using Fuzzy Analytic Hierarchy Process Method shows that the biggest value of the order or the most influential factor on the load forecasting are: load data, GDP data and weather data, so that the load data used as input load forecasting using ANN Modified Counterpropagation. Training results between the data and the actual energy output ANN training using the Counterpropagation Modified Method in Sampang Swichgear shows as 0 or 0%. The training epoch converging on the 89th and the number of units in the hidden layer neuron is 5. MAPE values between the actual data and the output data on the test results in 2013 forecasting of electric energy in Sampang GI is 0.00 or 0%. Output electrical energy forecasting results in 2013 on the GI Sampang already qualified, as it is still below the value (MAPE) of 0.05 or 5%. Thus Counterpropagation Modified ANN can be used to perform long-term load forecasting in Sampang Regency.

Item Type:	Article
Uncontrolled Keywords:	Electrical Energy Forecasting, Neural Network, Fuzzy Analytic Hierarcy Process Method, Modified Counterpropagation, Mean Avarage Percentage Error
Subjects:	Technology
Divisions:	Faculty of Engineering > Bachelor of Electrical Engineering
Depositing User:	Perpus Ubhara Surabaya
Date Deposited:	19 Oct 2022 07:30
Last Modified:	21 Oct 2022 03:22
URI:	http://eprints.ubhara.ac.id/id/eprint/1459

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