PENERAPAN KLASIFIKASI ALGORITMA C4.5 PADA FITUR GRAY LEVEL CO-OCCURRANCE MATRIX UNTUK ANALISA TEKSTUR CITRA WAJAH - Ilham Kurniawan; Dwiza Riana (INTI Nusa Mandiri, 2019)
Research on facial images is useful to distinguish the characteristics of each human being. The introduction of healthy and unhealthy facial skin images aims to identify human skin types automatically. For this purpose features such as contrast, correlation, energy, homogeneity, which are features of the Gray Level Co-occurrance Matrices (GLCM) are used. This study proposes a method for analyzing and classifying the GLCM texture on facial skin. The image used in this study was taken in the face image section which consists of the skin of the cheek and the whole face. The methods used are image acquisition, facial skin image, ROI selection, RGB image conversion to gray image, GLCM feature extraction, C4.5 algorithm classification and evaluation. The results showed that the C4.5 algorithm classification on texture analysis of facial images produced an accuracy value of 66.67%, the accuracy value was still low and the need for further research could not be used to increase the accuracy of texture analysis of facial images.