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					Human Face Image Recognition Posted in Thesis, Computer Science, Artificial intelegent Introduction of the face image is a process to identify and determine the person. Facial image recognition technology in biometrics, including the use of human characteristics. Currently face recognition can be used in various ways, including for security, the introduction of the identity of employees, improve efficiency and effectiveness of various activities, namely by reducing the use of IDs and passwords. Recognition system is implemented using Artificial Neural Network model Adaptive Resonance Theory (ART). JST ART has the ability to accept new information without forgetting the previous information, the same way the human brain works. To be able to identify the facial image, artificial neural networks requires preprocessing and feature extracting first. Feature extraction process with Principal Component Analysis (PCA) aims to obtain information essential features of the face image and its value is taken as input for artificial neural networks. JST Training conducted to obtain the correct classification of the input data train image of the original face. Facial image can be recognized if the facial image into one of the class formed from the training process. Test results obtained from the accuracy level face image recognition system with the best classification is approximately 96% to be able to identify the original face image, and about 80% - 100% to reject a false image of the face.