Penyebaran Mahasiswa ITB Ahmad Dahlan Jakarta Menggunakan Algoritma Clustering
Abstract
The development of information technology has made it possible to collect and analyze large and complex data. In the context of higher education, information about student distribution patterns can be of added value for institutions to plan and manage their resources effectively. This research aims to design a web mining system that uses a clustering algorithm to grouping the distribution of students at ITB Ahmad Dahlan. In this study, we collected data from open web sources that are relevant to students, such as student profiles, academic preferences, and extracurricular activities. The data is then analyzed using a clustering algorithm to identify patterns and trends in student distribution. By using this approach, we hope to provide useful insights for educational institutions in planning infrastructure, academic programs, and student services.
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