Abstract
The development of biometric technolgy is growing so that many recognition systems use biometrics in the form of physical characteristics and behavioral characteristics. Physical characteristics such as fingerprints, retina of the eye, face, and iris. While the behavioral characteristics include signatures, gait, and voice. One of the biometric parts used as an identifier is iris recognition using mathematical techniques. The iris of the eye has a unique and distinct pattern for each individual with stable identification and tends to remain unchanged. This study aims to design a tool that is able to detect a person's iris with a feature extraction method, namely Gabor wavelet with a classification method, namely K-Nearest Neighbor (K-NN). The results of the experiments carried out, the system succeeded in recognizing the iris image according to the selected image. However, if the selected image is not in the database, the results will show the name of the image that has the closest predictive value.
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