PREDIKSI BEBAN LISTRIK JANGKA PENDEK BERBASIS BACKWARD ELIMINATION
Short-term electrical load prediction is one way that can be used to generate and distribute electrical energy economically so that the provider can determine the load and power demand for some time to come. Many researchers who examined the short-term electric load by the method of Neural Network. However, the use of the data set that a lot of the neural network can result in an excessive number of neurons so that can cause over generalizes phenomenon so that the necessary process of feature selection to reduce attributes in the data set that much. This research begins with the ability to process data loads daily system time series per-30 minutes. The method used is a Neural Network based on Backward Elimination with the input data used is the data in January 2012. Several experiments were conducted to obtain the optimal architecture and generate accurate predictions. The results showed an experiment with Neural Network-based methods Backward Elimination produces a lower RMSE is 0,018 compared to RMSE produced by the method of Neural Network is 0,035.
Alfarez, K, Hesham&Nazeeruddin, Mohammad. (2002). Electric Load Forecasting: Literature Survey and Classification Of Methods. International Journal of System Science. 1. 23-34.
Hayati, Mohsen &Shirvany, Yazdan. (2007). Artificial Neural Network Approach for Short Term Load Forecasting for Illam Region. World Academy of Science, Engineering and Technology. 28.
Liao, Warren. T. &Triantaphyllou.Evangelos. (2007). Recent Advances in Data Mining of Enterprise Data: Algorithms and Applications. Series: Computer and Operation Research. 6. 190.
Maimon, Oded&Rokach, Lior. (2010). Data Mining and Knowledge Discovery Handbook. (2nd ed). New York: Springer.
Marsudi, Djiteng. (2006). Operasi Sistem TenagaListrik. Yogyakarta: GrahaIlmu.
Myatt, Glenn J. (2007). Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining. New Jersey: John Wiley & Sons, Inc.Mitchell, T.R.,
Abstract viewed = 21 times
PDF downloaded = 16 times
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to the PILAR Nusa Mandiri journal as the publisher of the journal, and the author also holds the copyright without restriction.
Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases, and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , are allowed with written permission from the PILAR Nusa Mandiri journal.
PILAR Nusa Mandiri journal, the Editors and the Advisory International Editorial Board make every effort to ensure that no wrong or misleading data, opinions, or statements be published in the journal. In any way, the contents of the articles and advertisements published in the PILAR Nusa Mandiri journal are the sole and exclusive responsibility of their respective authors and advertisers.