Analisis Data Untuk Pengelompokan Mahasiswa Dengan Metode K-MEAN (Studi Kasus : Institut Shanti Bhuana)

Santi Thomas, Noviyanti P Noviyanti P


Student achievement index (GPA) has always been used as a benchmark to assess the quality of a college. Likewise with ISB (Institut Shanti Bhuana) which  has  been working for 5 years, also hopes to create qualified graduates. ISB is different from the other universities because in addition to intellectual achievement in ISB, it also has an ICP (Integrity-Credit-Point). These two values are used as benchmarks to see whether students have succeeded in becoming qualified graduates as written in the ISB's vision and mission. The purpose of this study was to classify students who have good grades in both GPA and ICP. The K-mean algorithm is chosen because it is easy to adapt and the most widely used in data clustering. The data set was taken as many as 97 students from 4 study programs with 3 clusters. The results showed that cluster 1 was 18 people, cluster 2 was 48 people and cluster 3 was 31 people. It is hoped that this research can help the leadership get useful information in making decisions both in academic development and morality as well as decisions in granting scholarships based on considerations of the value of the GPA and ICP.

Keyword: K-mean, clustering, outstanding students, data analysis

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