Determine majors in vocational high schools based on fuzzy c-means algorithm - Rahmani AR, Muhammad Bayu; Sudira, Putu (Faculty of Engineering, Universitas Negeri Yogyakarta, 2024)
This study aimed to investigate the use of a decision support system called Fuzzy C-Means to group students based on their interests and aptitude. Fuzzy C-Means was used to group students into several alternative majors such as Catering (CT), Fashion Design (FD), Accounting and Institutional Finance (AIF), Online Business and Marketing (OBM), Multimedia (MM), Office Governance Automation (OGA), and Computer and Network Engineering (CNE). This study employed the quantitative approach with the pre-experimental research design. Data were collected through interest-aptitude tests and documentation. The participants of this study were 58 students of State Vocational High School Barabai 1. Fuzzy C-Means managed to group students into seven clusters. With the criteria of interests and talents, every student had the opportunity to be in all existing majors. The cluster validity value obtained using the Partition Coefficient Index is in the good category (0.6054). The system accuracy value is 89.7%. It means that there is an increase in the accuracy rate of 10.4% when compared to selecting majors manually. Based on cluster validation and the level of system accuracy, a decision support system using the Fuzzy C-Means algorithm is feasible to be an alternative for determining school majors.