Clustering Data Mining Algoritma K-Means Dalam Pengolahan Nilai Pat Pada Mata Pelajaran Bahasa Inggris, Bahasa Indonesia Dan Matematika Dengan Pembelajaran Virtual Learning (Studi Kasus Siswa Kelas XI SMA AL Maghfirah Telajung Bekasi)

Sudirman Sudirman (Universitas Pelita Bangsa)

Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB
Vol 11 No 1 (2020): Desember 2020

This research was motivated by problems regarding the PAT (year-end assessment) scores in the subjects of English, Indonesian and Mathematics for class XI students of SMA Al Maghfirah Telajung Cikarang Barat Bekasi which have not been grouped. This study aims to determine the results of using k-means algorithm data mining clustering in processing PAT (Year-End Assessment) data on English, Indonesian and Mathematics subjects with virtual learning in class XI SMA AL Maghfirah Telajung Bekasi. The subjects of this study were 37 students of PAT (year-end assessment) grade XI SMA Al Maghfirah data. The data clustering technique uses the k-means algorithm clustering method through the Rapidminer Studio software. The results showed that this method can classify the PAT value data (year-end assessment) based on the distance between the data. The results of data grouping are as follows: cluster 0 (low) of 18 students and cluster 1 (high) of 19 students. From this research it can be concluded that the data clustering technique using the k-means algorithm clustering method through the Rapidminer Studio application can be said to be successful in clustering PAT value data (year-end assessment) at SMA Al Maghfirah Telajung Cikarang Jawa Barat Keywords: PAT Value, Clustering, K-Means and Rapidminer Studio