PERAMALAN KEBUTUHAN ENERGI LISTRIK JANGKA PANJANG DI PROVINSI BALI RENTANG TAHUN 2020 – 2030 MENGGUNAKAN NEURAL NETWORK - Axel Adamma Diwanda; I Nyoman Setiawan; Widyadi Setiawan (Program Studi Teknik Elektro UNUD, 2021)
Bali Province is one of the provinces with densely populated areas, hence the availabilityof electricity is very important for life sustainability. In this research, electricity demandforecasting was conducted in Bali Province for the period of 2020-2030. The method used toforecast was neural network which has the advantage of being able to do an adaptive learningbased on the data used for training. In this forecasting process that used neural network, theneural network toolbox (nntool) on MATLAB 2013a was used. Network architecture used wasfeed-forward backpropagation. In this research, layer combination applied was 4 – 12 – 1, with4 input data such as population, PDRB, PDRB per capita and IHK. Network parameter appliedin this research was training function TRAINGDX, activation function TANSIG and PURELIN(output), performance function MSE and learning function TRAINGD. The final result of BaliProvince electricity demand forecasting in 2020 the demand for electricity is 5772 GWh, in 2025it will increase to 6523 GWh and in 2030 become 8551 GWh. This forecasting MAPE againtsthe RUKN 2019 result was 3.29%, which is under the PLN regulation that is 10%.