Implementasi Algoritma K-Means untuk Klasterisasi Penentuan Tempat Prakerin - Hasanah Arif, Surya; Jasmir, Jasmir (LPPM Universitas Dinamika Bangsa, 2024)
Over time, the system of placement of internships in the Department of computer engineering and network (TKJ) vocational secondary school who runs the current gave rise to some of the problems faced by the Department as well as students. For the first system, the Department often difficulty in determining the location of internship students who place the grouping in accordance with knowledge and skills that students have. On the system of the two problems often found on the place of location of the internship the students find themselves because it does not fit with the majors TKJ. Therefore it is necessary a technique in determining the location of internship place groupings in accordance with scientific concentration and the ability of students to the party heading for easy placement of students in doing internships. Research undertaken aims to spot clusters academic competency-based apprenticeship that students have. The data used to make the Division of apprenticeship places cluster using data from 57 people grade 2 TKJ. To do this cluster will use the method of the K-Means algorithm. The cluster is formed into three clusters, namely: C0: Government Agencies; C1: Computer Store; and C2: provider network. Then the data will be in the analysis with the help of RapidMiner software to determine the result of the Division of apprenticeship places cluster. Obtained on the test results the overall data amounted to 57 the data on the cluster of Government Agencies: C0 found the data included as many as 29 students, in cluster C1: computer shop found the data included as many as 18 students, and in cluster C2: Member data Network Provider found a total of 10 students