<![CDATA[Scientific articles were wrote as result of the research process that follow agreed rules, methods, and systematics so that the fact can be accounted for. Those scientific articles or publications were commonly available in the internet as indexed list. One of the biggest source of publication indexed in SINTA (Science and Technology Index) of Ministry of Education, Culture, Research and Technology of Indonesia. According to SINTA, the number of Indonesian publications continues to increase over years since 2017. Because of this increasing number of publications, the need of managing those documents is emerging. The management of published document data would be very difficult to do manually, including grouping or classifying documents based on the research topic. This become the background of this research on how to classify the articles topic automatically. This research utilizing support vector machine classifier to achieve the solution. After conducting research using 600 documents, we successfully classify the topic of Indonesian scientific article documents using the support vector machine method with a 94% accuracy, 95% precision, and 94% recall.]]>
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