Purwarupa Sistem Rekomendasi Buku Perpustakaan Menggunakan Metode Content Based Filtering
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Institusion
Institut Teknologi Telkom Purwokerto
Author
Victory, Herawidatama Esa Putra
Subject
T Technology (General)
Datestamp
2022-04-14 05:56:43
Abstract :
The development of information technology has made the library into a process of digitizing information and communication technology (ICT). However, with the library entering the realm of ICT, it creates new problems, such as the difficulty of students finding books related to their interests or study programs. In addition, due to the large number of books owned by the Purwokerto Telkom Institute of Technology library, currently +7590 in 2022, so to solve existing problems, a book recommendation system is needed that can provide several alternative book recommendations based on the title of the previous book. read or based on keywords to find the book they want. In this study, researchers applied the Content-Based Filtering method, which is a machine learning algorithm that can provide recommendations based on an item. This method works to measure the improvement of each place entered by the reader with the library data set. The results of the evaluation of the system based on testing data were based on an assessment based on a precision value of 70.6%, using a book title of 60.6% precision value and a recall value of 87.54% for a recall value without a recommendation limit. With five recommendation limits, the average precision value is 84% for the use of keywords and 92% for the use of book titles. Keywords: Information , Library, ICT, Recommendation System, Content-Based Filtering, Dataset
The development of information technology has made the library into a process of digitizing information and communication technology (ICT). However, with the library entering the realm of ICT, it creates new problems, such as the difficulty of students finding books related to their interests or study programs. In addition, due to the large number of books owned by the Purwokerto Telkom Institute of Technology library, currently +7590 in 2022, so to solve existing problems, a book recommendation system is needed that can provide several alternative book recommendations based on the title of the previous book. read or based on keywords to find the book they want. In this study, researchers applied the Content-Based Filtering method, which is a machine learning algorithm that can provide recommendations based on an item. This method works to measure the improvement of each place entered by the reader with the library data set. The results of the evaluation of the system based on testing data were based on an assessment based on a precision value of 70.6%, using a book title of 60.6% precision value and a recall value of 87.54% for a recall value without a recommendation limit. With five recommendation limits, the average precision value is 84% for the use of keywords and 92% for the use of book titles. Keywords: Information , Library, ICT, Recommendation System, Content-Based Filtering, Dataset
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