%A NIM. 12651098 AKHMAD CHOERUDIN WAKHID
%O M. Didik R Wahyudi, S.T., MT.
%T IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA K-MEANS CLUSTERINNG UNTUK MENGETAHUI POLA PEMILIHAN PROGRAM STUDI MAHASISWA BARU IAIN SALATIGA
%X Data mining can be used in agencies, schools, college and so on. In college can be used to process the existing data such as student data, employees, lecturers and others. Every year, colleges will open new admissions. Therefore, the college will produce new student data that must be stored like name, address, origin of school, and so forth. Not all colleges use all of the student data other than just for administration. This study uses the application of data mining with k-means clustering method in order to know the pattern of study program selection for new students at IAIN Salatiga by grouping the student data. The student data are grouped based on similarity of data so that the data with the same characteristics will be in one cluster. The attributes used are program study, school, the major of origin of school. Clusters formed after the K-Means Clustering process are three clusters with the first cluster amounting to 1492 student data, second cluster 638 student data, and third cluster 336 student data. From the results of this study can be concluded that the first cluster is the highest demand. So it can be seen the interest of new students in choosing courses that are in IAIN Salatiga by looking at the results of the three clusters that have been processed through various processes.
%K Program of study, school, major of origin of school, Data mining, K-Means clustering, Student, IAIN Salatiga.
%D 2017
%I UIN SUNAN KALIJAGA YOGYAKARTA
%L digilib29733