PERAMALAN BEBAN LISTRIK JARAK PENDEK DENGAN MENGGUNAKAN JARINGAN SYARAF TIRUAN DI P3B PT. PLN REGION III JAWA TENGAH DAN DIY - Purnomo, Harry (MAGISTRA, 2007)
Short-term load forcasting need to planning activity of electrical generating and demand of power system, to schedull and controlling power system or running generatingresources. Short-term load forecasting in P3B PT. PLN Region III Central Java and DIY have load coofesien mothode. This method is not practically and need a long time to forecasting. Artificial neural-network hort-term load forecasting (ANNSTLF) with backpropagation algorithm used a new methode for short-term load forecasting. The load were divided into 10 design : 6 load work day, 1 load for Sunday or Holiday, 3 load for special day (new year, Christmas and Idul Fitri). A load not linear. Input for Artificial neural-network is historical load for 2 day ago and yesterday (48 hour), and the output is load forecasting, load of hour by hour for 24 hour tomorrow. Artificial neural-network short-term load forecasting (ANNSTLF) with backpropagantion of algorithm have been worked successful by simulation and forecast a load with a relative less error.   Keyword : Artificial neural-network, backpropagation, electric load forecasting.