<![CDATA[The Recommendation System can produce system requirements data that is more descriptive and easy to implement into software. Recommendation methods are combined to form more comprehensive recommendations based on fermat points. The education sector has never been indifferent to new technologies, and eventually switched to using the Internet. Prior to conducting this research, a review was carried out on various previous research results related to the lack of the role of knowledge space and user preferences in the data visualization recommendation system [3]. Broadly speaking, this study uses the method of recommending the Analysis and Discussion system. One of the main elements that must be considered in the system analysis stage is software problems, because the software used must be in accordance with the problem to be solved. In this stage, the search and collection of data and knowledge obtained by the expert system are carried out. A machine learning-based recommendation system for undergraduate study programs can help prospective new students choose the right study program according to their interests and talents. The classification model used can produce fairly high accuracy in recommending undergraduate study programs to prospective new students.]]>
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