<![CDATA[Eye iris pattern recognition is widely used for the purpose of identifying a person's identity. This is can be done because the iris is unique and has a high consistency and stability for years without changing. In this research we will perform iris image pattern recognition by the Haar level 3 wavelet transforms and the LVQ neural networks. This research is expected to know the iris images pattern recognition systems which are more effective; efficient also requires a short time in matching process on this method. The object in this research is the PNG color images with size of 128 x 128 pixels. Parameters used in this research are to varying value of learning rate 0.01 and 0.05, the number of neurons 30 and 40; and epoch value 100 and 200. The values of these parameters will be varied so that the obtained parameter values are the most effective, efficient and a relatively requires short time in the process of the iris image pattern recognition.Based on testing performed, the Haar level 3 wavelet transform combined with LVQ neural network in the process of finding the iris images. The method also gives fast matching process and high accuracy level. Changes in the values of learning rate, number of neurons and epoch value affect network performance. The iris matching process has the fastest time of 2.15 seconds and the higher of accuracy of 87% when the value of learning rate 0.01; the number of neurons 40 as well as the epoch value 100.]]>
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