<![CDATA[The recommendation system is an important component in enhancing the user experience by providing relevant and personalized course recommendations that align with individual preferences and needs. The Hybrid Collaborative Filtering approach combines the Collaborative Filtering (CF) method, which analyzes user interaction patterns, with the Content-Based Filtering (CBF) method, which evaluates the similarity of course content features. Implementing this hybrid system is expected to overcome the limitations of each method, such as the cold start problem in CF and the limitation of recommendation variety in CBF. This research aims to design a recommendation system in the academic environment known as “Genusian Course Academy”. This hybrid approach is expected to overcome the weaknesses of each approach and result in a more accurate and personalized recommendation system. The implementation of this system is expected to improve the online learning experience and help users find training that matches their needs users.]]>
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