Wood is the part of the stem or twig of a plant that hardens as a result of the natural lignification process. Wood has properties that cannot be imitated by other materials. The properties of wood are durable, strong and non-corrosive. Weaknesses of wood, namely natural deficiencies contained in it such as knot defects, heart brittle defects, and borer hole defects. This study uses the SVM (Support Vector Machine) method to obtain accuracy against defects in wood by using GLCM (Gray Level Co-occurence Matrix) extraction. The dataset used contains 160 images and then separated into 112 train data and 48 test data. The identification carried out on the Gaussian kernel got the highest accuracy of 27.08% compared to using the Linear kernel with a smaller accuracy of 16.67%.
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