Perancangan dan Implementasi Sistem Monitoring Jaringan Berbasis Zabbix untuk Deteksi Dini Gangguan Jaringan di Fakultas Biologi Universitas Gadjah Mada

Bramunsya Derawan, Ir. Alif Subardono, S.T., M.Eng.

2026 | Tugas Akhir | D4 TEKNOLOGI JARINGAN

Jaringan komputer di Fakultas Biologi UGM menghadapi tantangan pemantauan yang kompleks akibat tingginya jumlah perangkat aktif dan keterbatasan sistem monitoring manual. Penelitian ini merancang dan mengimplementasikan sistem monitoring jaringan berbasis Zabbix 7.0.22 secara non-invasif menggunakan virtual machine yang terhubung ke jaringan fakultas melalui kabel LAN, tanpa mengubah konfigurasi infrastruktur yang ada. Sistem memantau 100 perangkat jaringan aktif berupa Switch dan Access Point menggunakan protokol ICMP Ping dengan trigger Warning dan notifikasi otomatis melalui Telegram Bot API. Pengujian dilakukan selama 4 minggu (4–29 Mei 2026) dengan validasi silang terhadap data Eventlogs resmi DTI UGM. Hasil menunjukkan sistem berhasil mendeteksi 598 insiden gangguan jaringan dengan tingkat keandalan notifikasi Telegram 96,85?ri 1.142 notifikasi. Akurasi deteksi tervalidasi dengan toleransi timestamp hanya 0–1 detik dibandingkan sistem monitoring enterprise universitas. Perangkat AP-GDA-LT3-FALITMA-60 teridentifikasi sebagai titik kerentanan tertinggi dengan 39 kejadian gangguan dan uptime 98,45%, di bawah standar SLA 99,5%.

The computer network at the Faculty of Biology UGM faces complex monitoring challenges due to the high number of active devices and limitations of manual monitoring systems. This study designs and implements a Zabbix 7.0.22-based network monitoring system in a non-invasive manner using a virtual machine connected to the faculty network via LAN cable, without modifying any existing infrastructure configuration. The system monitors 100 active network devices consisting of Switches and Access Points using the ICMP Ping protocol with severity triggers Warning and automatic notifications via Telegram Bot API. Testing was conducted over 4 weeks (May 4–29, 2026) with cross-validation against official DTI UGM Eventlogs data. Results show the system successfully detected 598 network disruption incidents with a Telegram notification reliability rate of 96.85% from 1,142 notifications. Detection accuracy was validated with a timestamp tolerance of only 0–1 second compared to the university enterprise monitoring system. The device AP-GDA-LT3-FALITMA-60 was identified as the highest vulnerability point with 39 disruption incidents and 98.45% uptime, below the 99.5% SLA standard.

Kata Kunci : Zabbix, ICMP, Monitoring Jaringan, Deteksi dini, Notifikasi Telegram, Packet loss, Latency, Availability