Sistem Rekomendasi Film Berbasis Konten Menggunakan Teknik Cosine Similarity dan TF-IDF
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Abstract
The goal of the research is to develop a content-based movie recommendation system that utilizes cosine similarity techniques to get better accuracy and relevance of recommendations to users.The methods used include text analysis of movie synopsis for feature extraction, representation vector generation, and cosine similarity calculation to determine the similarity between movies. Natural language processing is used to understand user preferences and compose recommendations accordingly.The results show that the developed recommendation system is able to enhance the accuracy of movie recommendations based on content, as well as provide a more personalized and relevant experience for users.
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