<![CDATA[It is undeniable that nowadays, the internet is essential for various needs. STMIK Widya Cipta Dharma is no exception. The internet is widely used in the campus environment by students, lecturers and education staff. Teaching and learning activities and work in the campus environment are inseparable from the need to use the internet. However, internet usage time sometimes accumulates in certain hours and causes slow internet speeds. This is influenced by the large number of header packets sent in the internet traffic flow, so the connection becomes heavy and feels sluggish. Therefore, a classification method is needed to provide information about the activities of students, lecturers and academic staff using the internet. The classification algorithm used is the Support Vector Machine (SVM). The development method used is SKKNI Number 299 of 2020. The parameters used are the flow of packets sent by the user and packets received by the user. The results of this study are in the form of an SVM algorithm model that can classify current internet traffic usage into four categories, namely Download, Game, SocialNetwork, and Web, which has an accuracy of 64% using the Radial Basis Function (RBF) kernel. The resulting accuracy results are pretty low and make the SVM algorithm unsuitable for classifying internet traffic and the need for other methods to classify internet traffic.]]>
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