@thesis{thesis,
		author={APRIAGUS  HANDI SATRIA and Muhammad  and Osvari },
		title ={IDENTIFIKASI BIOMETRIK CITRA TELINGA MENGGUNAKAN METODE PRINCIPAL COMPONENT ANALYSIS DAN LEARNING VECTOR QUANTIZATION},
		year={2018},
		url={https://repository.unsri.ac.id/9785/},
		abstract={Ear is one of biometric that can be used to identify someone. Ear have unique and stable structure biometric characteristic. The solution to identify someone?s ear image can be done with the computation method through software.. The computation method which is used is Learning Vector Quantization (LVQ) neural network method and Principal Component Analysis (PCA) feature extraction method. The amount of data which is used on this research is 100 ear images, consist of 50 images for left ear and 50 images for right ear. The best accuration of ear image identification are 75% on cropping testing data with learning rate 0.2 (normal grayscale) and 0.3(normal grayscale and green dominant grayscale).}
		}