Artificial Intelligence-Based Network Monitoring System Training for Computer and Telecommunication Network Engineering Students at SMK Cipta Insani Mandiri Depok

Johan Bastari
Rino Subekti (Department of Informatics Engineering, Faculty of Computer Science, Institute of Business and Informatics Kosgoro 1957, Jakarta, Indonesia)
Astried Silvanie (Department of Informatics Engineering, Faculty of Computer Science, Institute of Business and Informatics Kosgoro 1957, Jakarta, Indonesia)
Boy Firmansyah (Department of Informatics Engineering, Faculty of Computer Science, Institute of Business and Informatics Kosgoro 1957, Jakarta, Indonesia)
Dwi Sidik Permana (Department of Informatics Engineering, Faculty of Computer Science, Institute of Business and Informatics Kosgoro 1957, Jakarta, Indonesia)
Rahmat Jaya (Department of Informatics Engineering, Faculty of Computer Science, Institute of Business and Informatics Kosgoro 1957, Jakarta, Indonesia)

International Journal of Community Service
Vol. 6 No. 3 (2026): August 2026 ( Indonesia - Thailand)

The increasing adoption of Artificial Intelligence (AI) in network management requires vocational students to possess competencies that align with current industry demands. However, students of the Computer and Telecommunications Network Engineering (TJKT) program at SMK Cipta Insan Mandiri Depok have limited experience in utilizing AI-based network monitoring systems.[1] Therefore, a community service program was conducted to improve students’ knowledge and practical skills in intelligent network monitoring. The program was implemented through three stages: preparation, training, and evaluation. Training activities included theoretical sessions, hands-on practice using network monitoring tools, and the application of AI for network traffic analysis and anomaly detection. Evaluation was carried out through pre-tests, post-tests, and participant feedback. The results showed an improvement in students’ understanding of network monitoring concepts and their ability to utilize AI-assisted monitoring tools. Participants also demonstrated positive engagement and satisfaction throughout the training activities. This program successfully enhanced students’ competencies in AI-based network monitoring and contributed to their readiness for the increasingly automated and technology-driven networking industry.