Optimalisasi Literasi Digital dalam Rekomendasi Buku Referensi dengan Metode Clustering - Ahdiani, Ulaya; Winiarti, Sri; Ismail, Taufiq (STIKOM Tunas Bangsa Pematangsiantar, 2024)
In the learning process, library sources or teaching references are one of the main components needed for a lecturer. The large number of textbook references available for a course can make it difficult for a lecturer to determine which option is appropriate or widely used by lecturers for the same course. The importance of selecting textbook references allows a lecturer to search for information to determine whether the reference is the main reference or an additional reference. Digital literacy is one way that a lecturer can use to search for information related to textbook references by using computers or smartphones. The problem is that the available digital literacy is not yet able to provide recommendations for textbooks that teachers widely use for a course based on certain criteria. Several criteria can be used as determining indicators for a recommended book, for example, popularity due to the highest rating used, author's name, publisher's name, content or material, and year of publication are usually the determining indicators for using a book as a reference. In fact, in cyberspace, a lot of textbook reference information is provided, but it has not been grouped based on use. By utilizing a database of books published or sold online, you can find out what textbooks are the most popular and can be used as teaching materials. Still, a lecturer needs to find out one by one in each available online shop. The method in this research is data mining for textbooks that can be used as a reference for a lecturer using text mining techniques by clustering book titles in several online stores and based on semester learning plans from several campuses to map textbooks that are widely used. as reference material for 500 book titles from several publishers. Using 6 variables consisting of a book title, use for courses or fields of science, publisher, author, year of publication, and material, analysis will be carried out to obtain a data pattern. This research aims to apply a text mining concept to provide textbook recommendations for lecturers in the Informatics field of artificial intelligence courses using clustering techniques so that they can recommend reading books using 6 variables. The aim of this research is achieved in the form of software as a form of application of theory that has been tested in the laboratory for accuracy. The benefit of this research is providing lecturers with a list of textbooks that have been ranked automatically and are widely used in the same field of science.