PENERAPAN K-MEANS CLUSTERING PADA DATA PENERIMAAN MAHASISWA BARU DI POLITEKNIK NEGERI SAMARINDA --

ABSTRACT
This study aims to apply the K-Means Clustering method to student admission data
(case study: Samarinda State Polytechnic). Cluster formation is one of the techniques
used in extracting the trend pattern of a data. Data mining is usually identical to the
process of extracting data that is neatly arranged. In this case, the writer groups the
new student data with clustering technique. The grouping that the author applies uses
the K-Means Clustering method, the K-Means Clustering method is able to group
data in the same group and different data in different groups This will show the data
groups of new students who choose the Informatics Engineering, Computer
Engineering, Multimedia Informatics Engineering, and Computer Engineering study
programs.