Pengelompokkan Data Akademik Menggunakan Algoritma K-Means Pada Data Akademik Unissula

Abstract

A Higher education in the digital era as it is now common to use IT technology (Information Technology) in supporting their daily activities, but the use of IT raises a problem that is serious enough if there is no support and no further management this is only produce a data noise , Sultan Agung Islamic University (Unissula) has implemented an IT-based academic information system, in use of this information systems by time this systems produce a lot of data in the unissula academic database and this data is monotonous data and not clustered or also called data noise data that overlap without any benefit and information further in it, the purpose of this study is to solve the problem of these data into student performance data based on the GPA from semester 1 to semester 4 and make it to be a best data to support an alternative decision by the leader, this study uses the method of datamining and k-means algorithms, k-means algorithm is very good to be used as a solution for problems related to clustering, k-means algorithm is an algorithm that is unsupervised and the data can be adjusted by its self according to its class, the results of this study are a decision support system for grouping academic data for clustering student that have good potential and drop out potential in the form of dashboard information systems.