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Bali Province is one of the provinces with densely populated areas, hence the availability
of electricity is very important for life sustainability. In this research, electricity demand
forecasting was conducted in Bali Province for the period of 2020-2030. The method used to
forecast was neural network which has the advantage of being able to do an adaptive learning
based on the data used for training. In this forecasting process that used neural network, the
neural network toolbox (nntool) on MATLAB 2013a was used. Network architecture used was
feed-forward backpropagation. In this research, layer combination applied was 4 – 12 – 1, with
4 input data such as population, PDRB, PDRB per capita and IHK. Network parameter applied
in this research was training function TRAINGDX, activation function TANSIG and PURELIN
(output), performance function MSE and learning function TRAINGD. The final result of Bali
Province electricity demand forecasting in 2020 the demand for electricity is 5772 GWh, in 2025
it will increase to 6523 GWh and in 2030 become 8551 GWh. This forecasting MAPE againts
the RUKN 2019 result was 3.29%, which is under the PLN regulation that is 10%.
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