Utilization of Context Aware System: Enhancing Book Selection Recommendations in Smart Libraries

This study aims to utilize a context-aware system to improve book recommendations in a smart digital library. The system is expected to help library visitors in choosing books. This study provides book recommendations based on visitor preferences. This study has four main stages. The first stage is data collection, done by recording all the books in the library. The second stage is to classify books and group them into certain categories. The third stage is to determine book recommendations. The last stage is testing and drawing conclusions. This study uses content-based filtering and makes recommendations using the term frequency-inverse document frequency (TF-IDF) algorithm. With a context-aware system, Smart Libraries can recommend readings according to user preferences. This study conducted testing with two methods. The first method is system testing on the developer side. The second test is the user acceptance test. Based on the test results, The system can help users get book recommendations according to user preferences. This algorithm is quite effective in providing book recommendations in the library; The system can help optimize access to the book in library; and This system can make managing books that suit users in the library easier and more effective.