?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=PREDIKSI+BEBAN+LISTRIK+JANGKA+PENDEK+DENGAN%0D%0APENDEKATAN+BACKPROPAGATION+PADA+GARDU+INDUK+METRO&rft.creator=Salwa+Nursalsabila%2C+1715031007&rft.subject=620+Ilmu+teknik+dan+ilmu+yang+berkaitan&rft.description=Intisari+%E2%80%93+Prediksi+beban+listrik+jangka+pendek+dilakukan+untuk+mengetahui%0D%0Apenjadwalan+pembangkit+pada+suatu+sistem+pembangkit+tenaga+listrik.+Pada%0D%0Apenelitian+ini+prediksi+beban+listrik+jangka+pendek+dilakukan+di+Gardu+Induk+Metro%0D%0ALampung+dengan+2+kategori+yaitu+dengan+historis+data+6+bulan+dan+historis+data+2%0D%0Atahun+selama+satu+minggu.+Untuk+mengasilkan+prediksi+beban+listrik+dengan+nilai%0D%0Ayang+akurat+dilakukan+dengan+melakukan+simulasi+menggunakan+software+Matlab.%0D%0AMetode+yang+digunakan+dalam+prediksi+ini+adalah+Artificial+Neural+Network%0D%0Apendekatan+Backpropagation+dengan+tipe+jaringan+Feed+Forward%0D%0ABackpropagation.+Variabel+yang+digunakan+dalam+proses+simulasi+adalah+data%0D%0Ahistoris+beban+listrik+pada+trafo+1+dan+2+Gardu+Induk+Metro%2C+serta+data+historis%0D%0Atemperatur+udara+BMKG.+Hasil+prediksi+beban+listrik+dalam+penelitian+ini%0D%0Amenunjukkan+bahwa+tipe+jaringan+Feed+Forward+Backpropagation+dapat%0D%0Adigunkakan+untuk+memprediksi+beban+listrik+jangka+pendek+pada+Gardu+Induk%0D%0AMetro+Lampung.+Hasil+prediksi+beban+listrik+jangka+pendek+menggunakan+data%0D%0Ahistoris+sebanyak+6+bulan+menghasilkan+nilai+MAPE+sebesar+8.75%25+dan+prediksi%0D%0Abeban+listrik+jangka+pendek+menggunakan+data+historis+sebanyak+2+tahun%0D%0Amenghasilkan+nilai+MAPE+sebesar+1.99%25.%0D%0A%0D%0AKata+kunci+%E2%80%93+Prediksi+beban+listrik+jangka+pendek%2C+Artificial+Neural+Network%2C+Feed%0D%0AForward+Backpropagation.%0D%0AAbstract+%E2%80%94+The+generator+scheduling+in+a+power+system+is+determined+by%0D%0Aestimating+short-term+electrical+load.+Short-term+electrical+load+forecasts+elaborated%0D%0Aat+the+Metro+Substation+using+two+categories+of+previous+data%3A+6+months+of+historical%0D%0Adata+and+2+years+of+historical+data+in+one+week+horizon.+A+simulation+utilizing%0D%0AMatlab+software+was+used+to+obtain+an+accurate+prediction.+The+Artificial+Neural%0D%0ANetwork+Backpropagation+method+with+Feed+Forward+Backpropagation+network%0D%0Atype+was+utilized+in+this+calculation.+Historical+data+on+electrical+loads+at%0D%0Atransformers+1+and+2+at+Metro+Substations%2C+as+well+as+historical+data+of+daily%0D%0Atemperature+from+BMKG%2C+were+included+in+the+simulation+process.+The+Feed%0D%0AForward+Backpropagation+network+type+can+be+utilized+to+estimate+the+short-term%0D%0Aelectrical+load+at+the+Lampung+Metro+Substation%2C+based+on+the+results+of+this+study's%0D%0Aelectrical+load+prediction.+The+MAPE+value+for+short-term+power+load+predictions%0D%0Ausing+6+months+of+historical+data+was+8.75%25%2C+and+the+MAPE+value+for+short-term%0D%0Aelectricity+load+predictions+using+2+years+of+historical+data+was+1.99%25.%0D%0A%0D%0AKeywords+%E2%80%94+Short-term+load+forecast%2C+Artificial+Neural+Network%2C+Feed+Forward%0D%0ABackpropagation.&rft.publisher=FAKULTAS+TEKNIK&rft.date=2021&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F61185%2F1%2FAbstrak%2520-%2520salwa%2520nursalsabila.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F61185%2F2%2FSkripsi%2520Full%2520Tanpa%2520Lampiran%2520-%2520salwa%2520nursalsabila.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F61185%2F3%2FSkripsi%2520Full%2520Tanpa%2520Bab%2520Pembahasan%2520-%2520salwa%2520nursalsabila.pdf&rft.identifier=++Salwa+Nursalsabila%2C+1715031007++(2021)+PREDIKSI+BEBAN+LISTRIK+JANGKA+PENDEK+DENGAN+PENDEKATAN+BACKPROPAGATION+PADA+GARDU+INDUK+METRO.++FAKULTAS+TEKNIK%2C+UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F61185%2F