Skripsi
HUBUNGAN KARAKTERISTIK DENGAN TINGKAT KESEJAHTERAAN HIDUP PETANI PADI LAHAN GAMBUT DI DESA BANGSAL KECAMATAN PAMPANGAN KABUPATEN OGAN KOMERING ILIR
Bandwidth optimization is a crucial aspect in supporting network performance, especially when dealing with dynamic traffic. This research develops a Network Automation system based on Python, utilizing the Paramiko library, which is capable of performing automatic and adaptive configurations by implementing Load Balancing methods using Per Connection Classifier (PCC) techniques. Four testing scenarios were conducted to compare the effectiveness of manual and automated configurations under normal conditions as well as under high load. The results of the study indicate an increase in throughput from 2.92 Mbps to 11.98 Mbps, alongside a reduction in packet loss from 22.8% to 2.1%. In extreme scenarios, the system successfully maintained packet loss at 2.9%, despite an increase in delay reaching up to 7,199.7 ms. Furthermore, the system is equipped with real-time notifications via Telegram, informing the administrator when there is a spike in CPU usage, thereby facilitating a prompt response. With this approach, network administrators no longer need to perform manual configurations, but can rely on a responsive and efficient system. Keywords: Network Automation, Bandwidth, Load Balancing, PCC, Python, Paramiko, Computer Network.
Inventory Code | Barcode | Call Number | Location | Status |
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2407001161 | T139935 | T1399352024 | Central Library (References) | Available but not for loan - Not for Loan |
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