Perbandingan Peramalan Beban Listrik Jangka Pendek Menggunakan Support Vector Machine Dan Jaringan Syaraf Tiruan Perambatan Balik
Abstract
Penelitian ini membahas pemakaian Jaringan Syaraf Tiruan (JST) Perambatan Balik dan Support Vector Machine (SVM) untuk peramalan kebutuhan beban listrik. Variabel yang dipakai dalam JST dan SVM adalah data beban listrik wilayah Bali. Hasil peramalan memiliki persentase kesalahan rata-rata absolut 5,71% untuk metode JST dan 3,53% untuk metode SVM. Metode JST mempunyai rata-rata eror minimal 0,35% dan maksimal 17,34%. Metode SVM mempunyai rata-rata eror minimal 0,16% dan maksimal 10,53%. Metode SVM memiliki keakuratan lebih baik dibandingkan dengan metode JST.Downloads
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References
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[3] EI-Sharkawi, M., Niebur, D., 1996. “Short-Term Load Forecasting with Artificial Neural Networks: The International Activities”, IEEE power engineering society: tutorial course on artificial neural networks with applications to power systems, pp. 90–103
[4] Ran Qiwen，Shan Yongzheng，Wang Qi and et al. 2003. “Wavelet-neural networks-PARIMA method for power system short term load forecasting”,Proceedings of the CSEE, 23(3):38-42
[5] Kang Chongqing, Xia Qing, Zhang Boming. 2004. Review of Power System Load Forecasting and Development. Automation of Electric Power Systems, 28(7): 1-11.
[6] Kyung-Bin Song, Young-Sik Baek, Dug Hun Hong, and Gilsoo Jang.2005. “Short-Term Load Forecasting for the Holidays Using Fuzzy Linear Regression Method”, IEEE Transactions on Power System, Vol.20, No.1, February.
[7] X.M. Li, D. Gong, L. Li, and C.Y. 2005. “Next day load forecasting using SVM”, Proc. ISNN '05, Lecture Notes in Computer Science, Springer, Berlin, pp. 634-639.
[8] Gunn, S., 1998, Support Vector Machines for Classification and Regression, Tech.Rep., Dep.of Electronics and Computer Science, University of Southampton.
[9] Janes A. Freeman and David M Skapura,1992, Neural Network Algorithms, Application and Programming Techniques, Addison-Wesley Publishing Company, California.
[10] I Nyoman Setiawan dan Widyadi Setiawan, 2012, Perbandingan Peramalan Beban Listrik Jangka Pendek Menggunakan Support Vector Machine dan Jaringan Syaraf Tiruan Perambatan Balik (Studi Kasus di Pulau Bali), Laporan Akhir Penelitian Bidang Ilmu Teknik Elektro, Jurusan Teknik Elektro Universitas Udayana.
How to Cite
SETIAWAN, I Nyoman; SETIAWAN, Widyadi.
Perbandingan Peramalan Beban Listrik Jangka Pendek Menggunakan Support Vector Machine Dan Jaringan Syaraf Tiruan Perambatan Balik.
Majalah Ilmiah Teknologi Elektro, [S.l.], v. 12, n. 2, dec. 2013.
ISSN 2503-2372.
Available at: <https://ojs.unud.ac.id/index.php/mite/article/view/15549>. Date accessed: 19 nov. 2024.
Section
Articles
Keywords
jaringan syaraf tiruan, perambatan balik, support vector machine, peramalan beban
This work is licensed under a Creative Commons Attribution 4.0 International License
