<![CDATA[unstable and easily influenced in decision-making, and one of the most frequent occurrences is the mistakes in determining their faculty. In this case, the application in the form of a faculty recommendation website aims to help students make the right decisions, and the teachers take a role as an admin to view the student data. This application is made using ASP.NET and JavaScript for the front-end and Python and C# for the back-end. Using the C4.5 algorithm, the faculty can recommend the students accordingly based on their hobbies and the grade criteria entered into the system. By calculating the C4.5 algorithm, it will produce a Decision Tree. The decision tree will be more accurate if there is more training data, thus making the system better and more accurate. The results generated on this website are still less accurate because the training data used is still small.]]>
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