PERAMALAN BEBAN PUNCAK LISTRIK JANGKA PENDEK MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN BACKPROPAGATION

ADITYA, DIMAS and Zaini, Syamsuri and Thayib, Rudyanto (2023) PERAMALAN BEBAN PUNCAK LISTRIK JANGKA PENDEK MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN BACKPROPAGATION. Undergraduate thesis, Sriwijaya University.

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Abstract

Indonesia is a developing country with all the developments in every sector and is also supported by technological advances. Without an exact formula that can determine the magnitude of the electrical load at any time, what can be done is to predict the electrical load. The load forecasting method discussed in this thesis is the Backpropagation Artificial Neural Network (ANN) method. After the simulation, a comparison is made between the forecast results by the Backpropagation Neural Network and the load coefficient results showing that the average error with the Backpropagation ANN method for the first until fourth weeks reaches 1.89% with an accuracy of 98.11% and the average error of the load coefficient method for the first and second weeks reached 4.51% with an accuracy of 95.49%. These results indicate that the Backpropagation ANN forecasting is better than the load coefficient method

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Peramalan, Beban Puncak, JST, Backpropagation, Akurasi
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering > TK1 Electrical engineering--Periodicals. Automatic control--Periodicals. Computer science--Periodicals. Information technology--Periodicals. Automatic control. Computer science. Electrical engineering. Information technology.
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Dimas Aditya
Date Deposited:	13 Apr 2023 01:16
Last Modified:	13 Apr 2023 01:17
URI:	http://repository.unsri.ac.id/id/eprint/95928

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