S PE 1000141 Bibliography
DAFTAR PUSTAKA
Abdullah, A.G., Suranegara, G.M., Hakim, D.L. (2013). “Metode Hibrid PSOJST untuk Peningkatan Akurasi Prediksi Beban Listrik Jangka Pendek”. Forum
Pendidikan Tinggi Teknik Elektro Indonesia (FORTEI).
Behera, R., Panigrahi B., P., Pati, B., B., 2011, A Hybrid Short Term Load
Forecasting Model of an Indian Grid, Energy and Power Engineering, p190-193,
doi:10.4236/epe.2011.32024.
Annamareddi, S., Gopinathan, S., and Dora, Bharathi. (2013). “A Simple Hybrid
for Short-Term Load Forecasting”. Hindawi Publishing Corporation Journal of
Engineering. Vol 2013.
Arora Siddharth., Taylor, J.W. (2013). “Short-Term Forecasting of Anomalous
Load using Rule-Based Triple Seasonal Methods”. IEEE Transactions on Power
Systems, Forthcoming.
Chaturvedi, D.K., Premdayal, S.A., and Chandiok A. (2013). “Short Term Load
Forecasting using Neuro-Fuzzy-Wavelet Approach”. International Journal of
Computing Academic Research (IJCAR). Vol 2, (1), 36-48.
Hermaen, Undang. (2013). Peramalan Beban Jangka Pendek Khusus Hari Libur
Berbasis Jaringan Syaraf Tiruan dengan Algoritma Backpropagation. Skripsi
Sarjana Teknik Elektro pada FPTK UPI Bandung: tidak diterbitkan.
Jain, A., Jain M., B, 2013, Fuzzy Modeling and Similarity based Short Term
Load Forecasting using Swarm Intelligence-A step towards Smart Grid,
Proceedings of Seventh International Conference on Bio-Inspired Computing:
Theories and Applications (BIC-TA 2012), Advances in Intelligent Systems and
Computing 202, p15-27, DOI: 10.1007/978-81-322-1041-2_2,Springer India.
Kashani, Z., S., A Multi Adaptive Neuro Fuzzy Inference System for Short Term
Load Forecasting by Using Previous Day Features, Fuzzy Inference System Theory and Applications, InTech Publisher, Croatia.
Kuswadi, Son. (2007). Kendali Cerdas Teori dan Aplikasi Praktisnya.
Yogyakarta: Andi.
Marsudi, Djiteng. (2006). Operasi Sistem Tenaga Listrik. Jakarta: Graha Ilmu.
58
Paaso, E.A., Liao, Yuan. (2013). “Development of New Algorithms for Power
System Short-Term Load Forecasting”. International Journal of Computer and
Information Technology. Vol 02, Issue 02, 201-209.
Pandjaitan, L.W. (2007). Dasar-Dasar Komputasi Cerdas. Yogyakarta: Andi.
Peranginangin, Anwar. (2012). Optimasi Influence Range Algoritma Fuzzy
Subtractive Clustering untuk Peramalan Beban Dasar dan Beban Puncak Harian.
Skripsi Sarjana Teknik Elektro pada FPTK UPI Bandung: tidak diterbitkan.
Quaiyum, S., Khan, Y.I., Rahman, S., Barman, P. (2011). “Artificial Neural
Network Based Short-Term Load Forecasting of Power System”. International
Journal of Computer Applications. Vol 30, (4), 1-5.
Retana, Andri Mardian. (2010). Studi Model Prakiraan Beban Listrik Harian
Menggunakan Metode Moving Average dan Metode Backpropagation. Seminar
Tugas Akhir pada FPTK UPI Bandung: tidak diterbitkan.
Sari, Artika Dinar. (2006). “Peramalan Kebutuhan Beban Jangka Pendek
Menggunakan Jaringan Syaraf Tiruan Backpropagation”. Makalah Seminar Tugas
Akhir. Semarang: Universitas Diponegoro.
Siang, Jong Jek. (2005). Jaringan Syaraf Tiruan & Pemrogramannya
Menggunakan MATLAB. Yogyakarta: Andi.
Shayegi, H., Shayanfar, H.A., Azimi, G. (2010). “A Hybrid Particle Swarm
Optimization Backpropagation Algorithm for Short Term Load Forecasting”.
International Journal on Technicial and Physical Problems of Engineering
(IJTPE). Vol 2, Issue 4, 12-22.
Stroud, K.A. (1987). Matematika Untuk Teknik Edisi Ketiga. Jakarta: Erlangga.
Sudjana. (2005). Metoda Statistika. Bandung: Tarsito.
Syafii., Noveri, Edyan. (2013). “Studi Peralaman (Forecasting) Kurva Beban
Harian Listrik Jangka Pendek Menggunakan Metode Autoregressive Integrated
Moving Average (ARIMA)”. Jurnal Nasional Teknik Elektro. Vol 2, (1), 65-73.
Widiarsono, Teguh. (2005). Tutorial Praktis Belajar MATLAB. Ebook: tidak
diterbitkan.
59
Widyapratiwi, L.K., Mertasa, I.P.A., Arjana, I.G.D. (2012). “Peramalan Beban
Listrik Jangka Pendek di Bali Menggunakan Pendekatan Adaptive Neuro-Fuzzy
Inference System (ANFIS)”. Jurnal Teknik Elektro. Vol 11, (1), 50-55.
Zeng M., Xue S., Wang Z., Zhu X., Zhang G. (2013). “Short-Term Load
Forecasting of Smart Grid Systems by Combination of General Regression Neural
Network and Least Squares-Support Vector Machine Algorithm Optimized by
Harmony Search Algorithm Method”. Applied Mathematics & Information
Sciences An International Journal. Vol 7, (11), 291-298.
60
Abdullah, A.G., Suranegara, G.M., Hakim, D.L. (2013). “Metode Hibrid PSOJST untuk Peningkatan Akurasi Prediksi Beban Listrik Jangka Pendek”. Forum
Pendidikan Tinggi Teknik Elektro Indonesia (FORTEI).
Behera, R., Panigrahi B., P., Pati, B., B., 2011, A Hybrid Short Term Load
Forecasting Model of an Indian Grid, Energy and Power Engineering, p190-193,
doi:10.4236/epe.2011.32024.
Annamareddi, S., Gopinathan, S., and Dora, Bharathi. (2013). “A Simple Hybrid
for Short-Term Load Forecasting”. Hindawi Publishing Corporation Journal of
Engineering. Vol 2013.
Arora Siddharth., Taylor, J.W. (2013). “Short-Term Forecasting of Anomalous
Load using Rule-Based Triple Seasonal Methods”. IEEE Transactions on Power
Systems, Forthcoming.
Chaturvedi, D.K., Premdayal, S.A., and Chandiok A. (2013). “Short Term Load
Forecasting using Neuro-Fuzzy-Wavelet Approach”. International Journal of
Computing Academic Research (IJCAR). Vol 2, (1), 36-48.
Hermaen, Undang. (2013). Peramalan Beban Jangka Pendek Khusus Hari Libur
Berbasis Jaringan Syaraf Tiruan dengan Algoritma Backpropagation. Skripsi
Sarjana Teknik Elektro pada FPTK UPI Bandung: tidak diterbitkan.
Jain, A., Jain M., B, 2013, Fuzzy Modeling and Similarity based Short Term
Load Forecasting using Swarm Intelligence-A step towards Smart Grid,
Proceedings of Seventh International Conference on Bio-Inspired Computing:
Theories and Applications (BIC-TA 2012), Advances in Intelligent Systems and
Computing 202, p15-27, DOI: 10.1007/978-81-322-1041-2_2,Springer India.
Kashani, Z., S., A Multi Adaptive Neuro Fuzzy Inference System for Short Term
Load Forecasting by Using Previous Day Features, Fuzzy Inference System Theory and Applications, InTech Publisher, Croatia.
Kuswadi, Son. (2007). Kendali Cerdas Teori dan Aplikasi Praktisnya.
Yogyakarta: Andi.
Marsudi, Djiteng. (2006). Operasi Sistem Tenaga Listrik. Jakarta: Graha Ilmu.
58
Paaso, E.A., Liao, Yuan. (2013). “Development of New Algorithms for Power
System Short-Term Load Forecasting”. International Journal of Computer and
Information Technology. Vol 02, Issue 02, 201-209.
Pandjaitan, L.W. (2007). Dasar-Dasar Komputasi Cerdas. Yogyakarta: Andi.
Peranginangin, Anwar. (2012). Optimasi Influence Range Algoritma Fuzzy
Subtractive Clustering untuk Peramalan Beban Dasar dan Beban Puncak Harian.
Skripsi Sarjana Teknik Elektro pada FPTK UPI Bandung: tidak diterbitkan.
Quaiyum, S., Khan, Y.I., Rahman, S., Barman, P. (2011). “Artificial Neural
Network Based Short-Term Load Forecasting of Power System”. International
Journal of Computer Applications. Vol 30, (4), 1-5.
Retana, Andri Mardian. (2010). Studi Model Prakiraan Beban Listrik Harian
Menggunakan Metode Moving Average dan Metode Backpropagation. Seminar
Tugas Akhir pada FPTK UPI Bandung: tidak diterbitkan.
Sari, Artika Dinar. (2006). “Peramalan Kebutuhan Beban Jangka Pendek
Menggunakan Jaringan Syaraf Tiruan Backpropagation”. Makalah Seminar Tugas
Akhir. Semarang: Universitas Diponegoro.
Siang, Jong Jek. (2005). Jaringan Syaraf Tiruan & Pemrogramannya
Menggunakan MATLAB. Yogyakarta: Andi.
Shayegi, H., Shayanfar, H.A., Azimi, G. (2010). “A Hybrid Particle Swarm
Optimization Backpropagation Algorithm for Short Term Load Forecasting”.
International Journal on Technicial and Physical Problems of Engineering
(IJTPE). Vol 2, Issue 4, 12-22.
Stroud, K.A. (1987). Matematika Untuk Teknik Edisi Ketiga. Jakarta: Erlangga.
Sudjana. (2005). Metoda Statistika. Bandung: Tarsito.
Syafii., Noveri, Edyan. (2013). “Studi Peralaman (Forecasting) Kurva Beban
Harian Listrik Jangka Pendek Menggunakan Metode Autoregressive Integrated
Moving Average (ARIMA)”. Jurnal Nasional Teknik Elektro. Vol 2, (1), 65-73.
Widiarsono, Teguh. (2005). Tutorial Praktis Belajar MATLAB. Ebook: tidak
diterbitkan.
59
Widyapratiwi, L.K., Mertasa, I.P.A., Arjana, I.G.D. (2012). “Peramalan Beban
Listrik Jangka Pendek di Bali Menggunakan Pendekatan Adaptive Neuro-Fuzzy
Inference System (ANFIS)”. Jurnal Teknik Elektro. Vol 11, (1), 50-55.
Zeng M., Xue S., Wang Z., Zhu X., Zhang G. (2013). “Short-Term Load
Forecasting of Smart Grid Systems by Combination of General Regression Neural
Network and Least Squares-Support Vector Machine Algorithm Optimized by
Harmony Search Algorithm Method”. Applied Mathematics & Information
Sciences An International Journal. Vol 7, (11), 291-298.
60