Algoritme Genetika untuk Peningkatan Prediksi Kebutuhan Permintaan Energi Listrik
Predicting the demand of electrical energy with a high degree of accuracy is expected. Application of an appropriate model using exact method will greatly affect the level of accuracy result. Neural Network (NN) and Support Vector Machine (SVM) models are used to predict the needs of electricity dem...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Universitas Gadjah Mada
2016-05-01
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| Series: | Jurnal Nasional Teknik Elektro dan Teknologi Informasi |
| Subjects: | |
| Online Access: | http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/233 |
| _version_ | 1828914591338332160 |
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| author | Oman Somantri Catur Supriyanto |
| author_facet | Oman Somantri Catur Supriyanto |
| author_sort | Oman Somantri |
| collection | DOAJ |
| description | Predicting the demand of electrical energy with a high degree of accuracy is expected. Application of an appropriate model using exact method will greatly affect the level of accuracy result. Neural Network (NN) and Support Vector Machine (SVM) models are used to predict the needs of electricity demand. Those models have weaknesses. Both are still difficult in determining the value of parameters used, thus, affecting the level of accuracy. Genetic Algorithm (GA) is proposed as a method to optimize the value of NN and SVM parameters in predicting the demand of electrical energy. The result shows that the NN and GA models have a better accuracy than the SVM and GA. |
| first_indexed | 2024-12-13T19:57:43Z |
| format | Article |
| id | doaj.art-6827ed697acb4f2db898abcdc03e45e0 |
| institution | Directory Open Access Journal |
| issn | 2301-4156 2460-5719 |
| language | English |
| last_indexed | 2024-12-13T19:57:43Z |
| publishDate | 2016-05-01 |
| publisher | Universitas Gadjah Mada |
| record_format | Article |
| series | Jurnal Nasional Teknik Elektro dan Teknologi Informasi |
| spelling | doaj.art-6827ed697acb4f2db898abcdc03e45e02022-12-21T23:33:16ZengUniversitas Gadjah MadaJurnal Nasional Teknik Elektro dan Teknologi Informasi2301-41562460-57192016-05-015210811410.22146/jnteti.v5i2.233Algoritme Genetika untuk Peningkatan Prediksi Kebutuhan Permintaan Energi ListrikOman Somantri0Catur Supriyanto1Politeknik Harapan Bersama TegalUniversitas Dian NuswantoroPredicting the demand of electrical energy with a high degree of accuracy is expected. Application of an appropriate model using exact method will greatly affect the level of accuracy result. Neural Network (NN) and Support Vector Machine (SVM) models are used to predict the needs of electricity demand. Those models have weaknesses. Both are still difficult in determining the value of parameters used, thus, affecting the level of accuracy. Genetic Algorithm (GA) is proposed as a method to optimize the value of NN and SVM parameters in predicting the demand of electrical energy. The result shows that the NN and GA models have a better accuracy than the SVM and GA.http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/233listrikneural networksupport vector machinealgoritma genetik |
| spellingShingle | Oman Somantri Catur Supriyanto Algoritme Genetika untuk Peningkatan Prediksi Kebutuhan Permintaan Energi Listrik Jurnal Nasional Teknik Elektro dan Teknologi Informasi listrik neural network support vector machine algoritma genetik |
| title | Algoritme Genetika untuk Peningkatan Prediksi Kebutuhan Permintaan Energi Listrik |
| title_full | Algoritme Genetika untuk Peningkatan Prediksi Kebutuhan Permintaan Energi Listrik |
| title_fullStr | Algoritme Genetika untuk Peningkatan Prediksi Kebutuhan Permintaan Energi Listrik |
| title_full_unstemmed | Algoritme Genetika untuk Peningkatan Prediksi Kebutuhan Permintaan Energi Listrik |
| title_short | Algoritme Genetika untuk Peningkatan Prediksi Kebutuhan Permintaan Energi Listrik |
| title_sort | algoritme genetika untuk peningkatan prediksi kebutuhan permintaan energi listrik |
| topic | listrik neural network support vector machine algoritma genetik |
| url | http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/233 |
| work_keys_str_mv | AT omansomantri algoritmegenetikauntukpeningkatanprediksikebutuhanpermintaanenergilistrik AT catursupriyanto algoritmegenetikauntukpeningkatanprediksikebutuhanpermintaanenergilistrik |