<![CDATA[Indonesia has the biggest forest area which is almost 2/3 of the total area. Around 4000 types of wood are spread in the all areas of Indonesia?s forests. Wood identification has important benefits in determining quality of wood, that is developing in the wood industry. Manually, identifying wood species can only be done by a number of wood experts so the process take so much time and also has complex methods that cannot be done in shortly. Therefore, we need a system that can solve identification of wood types which is the process to be short and accurate. In this study, we used the method of support vector machine (SVM) to do classification of wood types which the resulting level of accuracy is 95%. This result also obtained by looking at the value of k-fold cross validation and confusion matrix.]]>
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