PENGENALAN WAJAH MENGGUNAKAN JST BERDASARKAN EKSTRAKSI CIRI PCA DAN LDA

MUHAMMAD FAZLUR RAHMAN , NIM. 07650009 (2012) PENGENALAN WAJAH MENGGUNAKAN JST BERDASARKAN EKSTRAKSI CIRI PCA DAN LDA. Skripsi thesis, PERPUSTAKAAN UIN SUNAN KALIJAGA.

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Abstract

Humans have the intelligence of a very complex multi-intelligence. Just as human is able ti quickly recognize, memorize and distinguish each person‟s face with an expression of previously known and different circumstances. Unlike human, computer system needs to be trained to pick the skills that are similar to humans. Biometric is the ability of the verification and identification based on physical characteristic and human behavior. Face recognition system is an example of biometric based on physical characteristic that can help computer system to have the similar capability to humans intelligence. This research uses 14 facial images as the trained data that‟s extracted to be covarian matrics then the eigen values taken from each datum of images using method of principal component analysis (PCA) and linear discriminant analysis (LDA). Each datum produce 4 eigen values which become the inputs to the training algorithm of artificial neural network of back propagation and the application algorithm of back propagation. The training algorithm earns outputs in form of optimal weight values which become reference to the application algorithm. The system is capable of extracting facial images into eigen values using PCA and LDA. Face recognition system is also capable of doing training data using an artificial neural network of back propagation. The system can also recognize facial images with successfull procentage 77,77% by structure of artificial neural network of back propagation: 4 nodes at input layer, 8 nodes at hidden layer and 3 nodes at output layer using epoch value of training 60x10 4

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