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Abstract. Biometrics is a science that is now growing rapidly. Iris recognition is a biometric modality which captures a photo of the eye pattern. The markings of the iris are so distinctive that it has been proposed to use as a means of identification, instead of fingerprints. Iris recognition was chosen for identification in this research because every human has a special feature that each individual is different and the iris is protected by the cornea so that it will have a fixed shape. This iris recognition system is done in three stages namely, pre-processing of data, feature extraction and matching. Hough transformation is used in the process of pre-processing to locate the iris area and Daugman's rubber sheet model to normalize the iris dataset into rectangular blocks.  To find the characteristics of the iris, it was  used box counting method to get the fractal dimension value of the iris . With K-Nearest Neighbor as the data classification and 5-fold cross validation, the result of iris recognition was obtained with the best accuracy was  92,632 %  for K = 3 value on K-Nearest Neighbor (KNN) method

Biometrics, Iris Recognition , Fractal Dimension.