S PE 1000141 Table Of Content
DAFTAR ISI
PERNYATAAN...........................................................................................
ABSTRAK....................................................................................................
KATA PENGANTAR.................................................................................
DAFTAR ISI................................................................................................
DAFTAR TABEL........................................................................................
DAFTAR GAMBAR...................................................................................
DAFTAR LAMPIRAN...............................................................................
BAB I
BAB II
BAB III
BAB IV
PENDAHULUAN....................................................................
1.1 Latar Belakang Masalah......................................................
1.2 Identifikasi Masalah............................................................
1.3 Rumusan Masalah...............................................................
1.4 Tujuan Penulisan Skripsi....................................................
1.5 Manfaat Skripsi...................................................................
1.6 Sistematika Penulisan Skripsi.............................................
TINJAUAN PUSTAKA.........................................................
2.1 Perkembangan Penelitian Short Term Load Forecasting
(STLF).................................................................................
2.2 Analisa Beban Sistem Tenaga Listrik.................................
2.2.1 Faktor-faktor yang mempengaruhi beban listrik........
2.3 Particle Swarm Optimization (PSO)...................................
2.4 Algoritma Backpropagation...............................................
2.4.1 Arsitektur jaringan.....................................................
2.4.2 Fungsi aktivasi...........................................................
2.4.3 Pelatihan standar backpropagation............................
METODE PENELITIAN......................................................
3.1 Pengumpulan Data Beban Listrik dari PLN.......................
3.2 Model Algoritma Hybrid Particle Swarm Optimization
Backpropagation (HPSO-BP).............................................
3.3 Penyusunan Model Matematis............................................
HASIL DAN PEMBAHASAN..............................................
4.1 Hasil Prediksi Hybrid Swarm Particle
Artificial Neural Network....................................................
4.1.1 Pola beban puncak harian Jawa Bali
region Jawa Barat berdasarkan tiga tipe hari.............
4.1.2 Hasil dan pembahasan prediksi
beban puncak pada hari kerja.....................................
4.1.3 Hasil dan pembahasan prediksi
beban puncak pada hari libur akhir pekan.................
Willy Wigia Sofyan , 2014
ESTIMASI BEBAN PUNCAK HARIAN BERDASARKAN
KLUSTER TIPE HARI BERBASIS ALGORITMA
HYBRID SWARM PARTICLE-ARTIFICIAL NEURAL NETWORK
Universitas Pendidikan Indonesia | repository.upi.edu | perpustakaan.upi.edu
i
ii
iii
v
vii
viii
ix
1
1
3
3
4
4
5
7
7
9
13
13
17
18
18
19
23
23
32
37
39
39
39
43
45
BAB V
4.1.4 Hasil dan pembahasan prediksi
beban puncak pada hari libur nasional
cuti bersama...............................................................
4.2 Hasil Eksperimen Optimasi Backpropagation
dan Particle Swarm Optimization......................................
4.3 Model Matematis Hybrid Swarm Particle
Artificial Neural Network..........................................................
KESIMPULAN DAN SARAN..............................................
5.1 Kesimpulan.........................................................................
5.2 Saran....................................................................................
DAFTAR PUSTAKA................................................................................
LAMPIRAN................................................................................................
Willy Wigia Sofyan , 2014
ESTIMASI BEBAN PUNCAK HARIAN BERDASARKAN
KLUSTER TIPE HARI BERBASIS ALGORITMA
HYBRID SWARM PARTICLE-ARTIFICIAL NEURAL NETWORK
Universitas Pendidikan Indonesia | repository.upi.edu | perpustakaan.upi.edu
48
51
54
56
56
57
58
61
PERNYATAAN...........................................................................................
ABSTRAK....................................................................................................
KATA PENGANTAR.................................................................................
DAFTAR ISI................................................................................................
DAFTAR TABEL........................................................................................
DAFTAR GAMBAR...................................................................................
DAFTAR LAMPIRAN...............................................................................
BAB I
BAB II
BAB III
BAB IV
PENDAHULUAN....................................................................
1.1 Latar Belakang Masalah......................................................
1.2 Identifikasi Masalah............................................................
1.3 Rumusan Masalah...............................................................
1.4 Tujuan Penulisan Skripsi....................................................
1.5 Manfaat Skripsi...................................................................
1.6 Sistematika Penulisan Skripsi.............................................
TINJAUAN PUSTAKA.........................................................
2.1 Perkembangan Penelitian Short Term Load Forecasting
(STLF).................................................................................
2.2 Analisa Beban Sistem Tenaga Listrik.................................
2.2.1 Faktor-faktor yang mempengaruhi beban listrik........
2.3 Particle Swarm Optimization (PSO)...................................
2.4 Algoritma Backpropagation...............................................
2.4.1 Arsitektur jaringan.....................................................
2.4.2 Fungsi aktivasi...........................................................
2.4.3 Pelatihan standar backpropagation............................
METODE PENELITIAN......................................................
3.1 Pengumpulan Data Beban Listrik dari PLN.......................
3.2 Model Algoritma Hybrid Particle Swarm Optimization
Backpropagation (HPSO-BP).............................................
3.3 Penyusunan Model Matematis............................................
HASIL DAN PEMBAHASAN..............................................
4.1 Hasil Prediksi Hybrid Swarm Particle
Artificial Neural Network....................................................
4.1.1 Pola beban puncak harian Jawa Bali
region Jawa Barat berdasarkan tiga tipe hari.............
4.1.2 Hasil dan pembahasan prediksi
beban puncak pada hari kerja.....................................
4.1.3 Hasil dan pembahasan prediksi
beban puncak pada hari libur akhir pekan.................
Willy Wigia Sofyan , 2014
ESTIMASI BEBAN PUNCAK HARIAN BERDASARKAN
KLUSTER TIPE HARI BERBASIS ALGORITMA
HYBRID SWARM PARTICLE-ARTIFICIAL NEURAL NETWORK
Universitas Pendidikan Indonesia | repository.upi.edu | perpustakaan.upi.edu
i
ii
iii
v
vii
viii
ix
1
1
3
3
4
4
5
7
7
9
13
13
17
18
18
19
23
23
32
37
39
39
39
43
45
BAB V
4.1.4 Hasil dan pembahasan prediksi
beban puncak pada hari libur nasional
cuti bersama...............................................................
4.2 Hasil Eksperimen Optimasi Backpropagation
dan Particle Swarm Optimization......................................
4.3 Model Matematis Hybrid Swarm Particle
Artificial Neural Network..........................................................
KESIMPULAN DAN SARAN..............................................
5.1 Kesimpulan.........................................................................
5.2 Saran....................................................................................
DAFTAR PUSTAKA................................................................................
LAMPIRAN................................................................................................
Willy Wigia Sofyan , 2014
ESTIMASI BEBAN PUNCAK HARIAN BERDASARKAN
KLUSTER TIPE HARI BERBASIS ALGORITMA
HYBRID SWARM PARTICLE-ARTIFICIAL NEURAL NETWORK
Universitas Pendidikan Indonesia | repository.upi.edu | perpustakaan.upi.edu
48
51
54
56
56
57
58
61