@thesis{thesis,
		author={Kuswardani  Dwina and Nurindah  Mega Dwi and Siregar  Riki Ruli A},
		title ={SHORT-TERM PREDICTION OF PEAK LOAD USAGE AT PT.PLN (Persero) AREA SORONG USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)},
		year={2018},
		url={http://156.67.221.169/4554/},
		abstract={PT. PLN (Persero) Sorong Area is currently in predicting still using historical load
patterns. This can lead to material losses for both parties, both PT. PLN (Persero)
Sorong Area and consumers. From these problems it is necessary to plan a
prediction system using the method. The method of determining the peak load
prediction value used in this study is the Adaptive Neuro-Fuzzy Inference System
(ANFIS) method which is a combined method of Fuzzy Inference System with
Artificial Neural Network (ANN). From the results of the testing, a comparison was
made between the prediction results by ANFIS with the actual burden of electricity
use in Sorong Kota. The results of calculations using alternative one obtained an
average error reached 1.0183% with an accuracy of 98.9817% while for the
second alternative obtained an average error reached 0.0124% with an accuracy
of 99.9%. These results indicate that the prediction using ANFIS is appropriate
and can be used to assist the generator parts staff at PT. PLN (Persero) Sorong
Area.}
		}