Analisis Jam Belajar dan Hasil Ujian Siswa dengan Menggunakan Metode K-Means Clustering, Principal Component Analysis (PCA) - Andreas Sijabat; Satna Siagian; Sepania Yolanda Br Sinaga; Muhammad Yasin Naufal (Lembaga Pengembangan Kinerja Dosen, 2025)
Education is a fundamental pillar in shaping students' abilities and potential, with one of the critical factors often under attention being the time spent on studying. Understanding the extent to which study time impacts academic achievement is essential for improving education quality. This study aims to explore whether there is a significant relationship between the number of study hours per week and students' final exam scores. The methods used in this research include K-Means Clustering, Principal Component Analysis (PCA), and the Apriori Algorithm. The expected result of this study is to discover a significant correlation between the two variables. If a significant positive correlation is found, it would indicate that increased study time is associated with better exam performance. Conversely, if the correlation is weak or negative, it would suggest that other factors may play a more dominant role in influencing students' academic performance. Furthermore, significance testing is conducted to ensure that the results of the analysis did not occur by chance. This research is expected to provide valuable insights for parents and students in developing more effective and efficient learning strategies. For educators, these findings can serve as a foundation for designing more structured learning programs, including recommendations for optimal study time allocation. On the other hand, for students, the results of this study can serve as a guide to managing their study time more optimally.