Penerapan K-Means Clustering untuk Menentukan Lokasi Promosi Penerimaan Mahasiswa Baru : (Studi Kasus: STMIK Kaputama Kota Binjai) - Ronauli Silaban; Achmad Fauzi; Lina Arliana Nur Kadim (Asosiasi Riset Teknik Elektro dan Informatika Indonesia, 2024)
The process of accepting new students generates a lot of data in the form of profiles of students who register. From year to year there is an increase in the number of prospective new students who come from several areas in Binjai City, Langkat Regency and surrounding areas, so the location of the socialization of new student admissions promotions every year is increasing and wider. And from several schools that have been visited and are expected to provide new prospective students, in fact, it is not proportional to the final number of prospective students who register. In this study, applying the K-Means Clustering algorithm using 3 variables namely, region, school origin, major. In determining the location of new student admissions promotions, the promotion team first identifies what factors will influence the determination of promotional locations ranging from region, school origin and majors that are considered to be set as promotional locations. Based on the results of grouping new student admission data of STMIK Kaputama Binjai using the K-means Clustering method from 20 data that has been processed, 3 clusters and 3 iterations are produced where cluster 1 has 9 data, cluster 2 has 2 data and cluster 3 has 9 data.