@thesis{thesis,
		author={NURWITANINGSIH  RANI EKA and Siregar  Riki Ruli A},
		title ={METODE LEARNING VECTOR QUANTIZATION UNTUK AUDIT ENERGI SISTEM PENCAHAYAAN PADA SEBUAH GEDUNG (STUDI KASUS : GEDUNG STT-PLN JAKARTA)},
		year={2013},
		url={http://156.67.221.169/564/},
		abstract={Each building would require lighting in every room. Often the use of building occupants do not pay attention to the lights. The research will be conducted in the building STT-PLN, to identify opportunities pengefisienan lighting system in every room per floor. LVQ (Learning Vector Quantization) is a method for classifying (grouping) and has an output pattern that represents a particular class. If two input vectors close together, then the competitive layer will put both the input vectors into the same class. Software engineering waterfall model. The results that determine dispersal patterns building lighting data STTPLN. 
And LVQ method will yield 100% accuracy the results of the training process if successful. Efficiency results will show the percentage per cluster on each floor.}
		}