IMPLEMENTASI NETWORK MONITORING SYSTEM (NMS) MENGGUNAKAN CACTI DENGAN METODE GENETIKA PADA INFRASTRUKTUR JARINGAN
Abstract
This study implements a Network Monitoring System (NMS) based on Cacti with genetic algorithm optimization to improve network monitoring efficiency at SMK PGRI 1 Tangerang. Cacti is used to visualize network performance such as bandwidth, CPU load, and uptime in real-time. The objective of this study is to enhance the efficiency and effectiveness of network monitoring through polling interval optimization so that the system remains efficient without overloading the server. The research methods include literature study, observation, interviews, and system simulation. The results show that the implementation of Cacti with the genetic method can improve network stability, accelerate fault detection, and reduce the Mean Time to Repair (MTTR) by up to 35%, from an average of 90 minutes to 30 minutes per incident, as well as decrease the frequency of failures from 4 times to 2 times per week. The results include graphical visualizations that help technicians and teachers interpret data, such as memory usage and load average. The system has proven effective in improving school network stability with minimal overhead. He implementation of a Network Monitoring System using Cacti with the genetic method has been proven to increase efficiency, stability, and fault detection speed in the network of SMK PGRI 1 Tangerang. This system assists technicians in real-time monitoring and accelerates the troubleshooting process. For future development, the system can be integrated with automatic notifications such as Telegram Bot or Email Alert and expanded to cloud-based monitoring to be more adaptive to modern network needs.Top of Form
References
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