PERHITUNGAN MATEMATIS KLASTERISASI NILAI MATA KULIAH MAHASISWA MENGGUNAKAN ALGORITMA K-MEANS - Nurhidayati; Imam Marzuki (LPPM STAI Muhammadiyah Probolinggo, 2023)
This research aims to conduct mathematical calculations related to the clustering of statistical course grades among students. The author utilized data from several students enrolled in the Mathematics Education Study Program at STAI Muhammadiyah Probolinggo, who took the statistics course as a case study. The clustering algorithm employed in this study is K-Means. The analysis results provide significant insights into the students' abilities in the statistics course. This research offers potential benefits to the study program in curriculum development and the design of more effective teaching strategies. The findings can be used to identify student groups in need of additional attention and to comprehend academic behavior patterns that may affect learning outcomes. In this study, only grade atributes such as assignments, mid-term, and final exam scores were utilized. Nevertheless, it is worth noting that the K-Means algorithm can be applied to cluster data with multiple grade atributes, including attendance, discipline, participation, and other atributes relevant to student learning.Keywords : mathematical calculations, identification, clustering, attributes