Library Book Recommendation System Using Content-Based Filtering
DOI:
https://doi.org/10.31763/iota.v4i1.693Keywords:
Recommendation Systems, Books, Content-Based Filtering, TF-IDF, Cosine SimilarityAbstract
In today's digital era, libraries are developed to adapt to student needs. Students can easily search for books on digital library services. However, the large number of books sometimes makes it difficult for students to find the books they want. Overcoming this problem can be done by using a recommendation system. A recommendation system is a system used to provide suggestions to users. This research aims to develop a library book recommendation system at Darul Mustofa Bangkalan Vocational School using content-based filtering. The content-based filtering method offers recommendations based on user preferences according to the item description. The algorithms used are Term Frequency Inverse Document Frequency (TF-IDF) and Cosine similarity. The method used in this research is research and development with a waterfall model. The researcher's testing stage used black box testing. Black box testing results were obtained from validation by system experts, website experts, and user tests with the qualification "Very Eligible."
