FUNGSI GLCM PADA BACKPROPAGATION UNTUK IDENTIFIKASI SIDIK JARI
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Abstract
The use of fingerprints for identification has been done a lot, both in the police for investigations, in government for absences, in population and much more. To identify fingerprints, various methods are widely used which purpose is to produce a better level of accuracy. This is as reference to find out how important the function of the method will be used before the identification process is applied. The renewal of this research prioritizes how far the function of GLCM (GRAY LEVEL CO-OCCURRENCE MATRIX) is useful to improve the accuracy of fingerprint identification using the backpropagation method. The test results showed that GLCM can affect the increase in accuracy to 83%.
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