Forecasting Electricity Sales Using the Artificial Neural Network Backpropagation Method

Yosi Febria Utami; Gumgum  Darmawan; Resa Septiani  Pontoh

doi:10.55927/ajae.v2i4.6589

Authors

Yosi Febria Utami Universitas Padjadjaran
Gumgum Darmawan Universitas Padjadjaran
Resa Septiani Pontoh Universitas Padjadjaran

DOI:

https://doi.org/10.55927/ajae.v2i4.6589

Keywords:

Forecasting, Electricity Sales, Artificial Neural Network Backpropagation

Abstract

PT PLN operates in the field of providing electrical energy and one of its goals is to meet consumer needs for electrical energy now and in the future, as well as PLN UID West Java. The initial step is to estimate how much electricity will be sold in the future. For this reason, electricity sales forecasting is carried out which can be taken into consideration by PLN UID West Java in making decisions. This research uses monthly electricity sales data in West Java for the last ten years. This data is not linear and not stationary, so an alternative method is used, namely Artificial Neural Network Backpropagation. Forecasting produces the best network architecture 12-7-1 with a MAPE of 2.965%. This architectural model is used to forecast electricity sales in West Java until August 2024.

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