IMPLEMENTASI DATA MINING CLUSTERING MAHASISWA AKTIF ORGANISASI KEMAHASISWAAN UNIVERSITAS SATYA NEGARA INDONESIA MENGGUNAKAN ALGORITMA K-MEANS - Prabandini Kartika; Safrizal (PROSIDING SNITek, 2019)
One important aspect in evaluating the success of the work program at the University of Satya Negara Indonesia is the Student Organization of Universitas Satya Negara Indonesia (OK USNI). OK USNI allows students to have a study load taken each semester, activities that are followed, and academic activities can influence and test the quality of students who have an impact on the final GPA and the accuracy of graduating students. To prove that graduates who actively participate in OK USNI can increase their academic value and pass on time or not, a data grouping technique is used, namely K-Means Clustering. K-Means was chosen because it has a fairly high accuracy on the size of the object, so this algorithm is relatively more measured and efficient for processing large quantities of objects. The system development method uses the PHP programming language and MySQL for the database. The final results of this study in the form of grouping students produced 3 groups of OK USNI active graduates in C1 totaling 46 students or 64%, C2 totaling 22 students or 31%, and C3 totaling 4 students or 6%. For non-active USNI graduates whoare in C1, there are 19 students or 26%, C2 is 45 students or 63%, and C3 is 8 students or 11%. This proves that by participating in the OK USNI, the duration of graduate studies is not affected