Analysis of Reading Interests of Visitors to the Library of State Junior High School 01 Salem Using the K-Means Clustering Algorithm

Abstract

Advances in information and communication technology have made information an important element in people's lives, including education and literacy. The high demand for information has encouraged the application of data mining techniques that combine statistics, mathematics, artificial intelligence, and machine learning to extract useful information from big data. In the context of libraries, data mining can be used to analyze borrowing and visit data to understand user needs patterns. In Indonesia, low reading interest remains a serious issue. Data from PISA (OECD) and UNESCO reports indicate that Indonesia's literacy skills and reading interest levels are below global standards. Many students are not accustomed to accessing reading materials outside of textbooks and rarely visit school libraries, which should serve as centers for literacy. The grouping was based on features such as student names, class, book titles along with publishers and authors, and the date and time of visits to the library. This data was categorized into three groups: high, moderate, and low reading interest. The clustering results using the K-Means Clustering algorithm at SMP Negeri 01 Salem show that the majority of students (118) fall into the low reading interest category, 13 students into the moderate category, and only 1 student (Dian) into the high reading interest category. Evaluating the quality of the clusters using the Davies–Bouldin Index (DBI) yielded a value of 0.2966, indicating very good cluster quality—a low DBI value indicates compact and clearly separated clusters. These results prove that the K-Means algorithm is effective in grouping students based on reading behavior. With this segmentation, schools can develop data-driven literacy strategies: tailoring book collections to each cluster's preferences, conducting special programs for students with low reading interest, and involving students with high reading interest as literacy ambassadors. This approach is expected to increase student engagement and strengthen the reading culture at school.