Analisis Klasterisasi Mahasiswa Baru dalam Memilih Program Studi dengan Menggunakan Algoritma K-Means
- Helpi Nopriandi Universitas Islam Kuantan Singingi, Teluk Kuantan, Indonesia
-
Febri Haswan
*
Universitas Islam Kuantan Singingi, Teluk Kuantan,
Indonesia
(*) Corresponding Author
Abstract
Kuantan Singingi Islamic University is a private university located in Riau Province with a population of 345,850 people. Kuantan Singingi Islamic University has 12 Study Programs with 1700 active students, from 2013-2021 the number of new students at Kuantan Singingi Islamic University there was an increase and decrease in new students, a significant decrease in the number of new students occurred in 2019 and 2020, The decrease in the number of new students makes several study programs have a ratio of lecturers to students that is not comparable and can harm the institution, by clustering new students in choosing the desired study program. the goal is as a material consideration for leaders to determine strategies in increasing the number of students in the future. The K-Means algorithm is one of the algorithms in data mining that can be used to cluster data, by grouping the data, it can be seen that the number of students in each study program increases or decreases, from these results can be used as evaluation material by the leadership for an increase in new students in each study program so that study programs that have a disproportionate ratio of lecturers to students are in line with what is expected, the ideal ratio of lecturers and students according to the 2012 higher education law is 1:20 for exact sciences and 1 :30 for Social Science.
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