YUNIAR, HELTI and Stiawan, Deris and Heryanto, Ahmad (2022) KLASIFIKASI POLA TRAFIK JARINGAN PADA APLIKASI SKYPE DAN CISCO WEBEX MENGGUNAKAN METODE SUPPORT VECTOR MACHINE. Undergraduate thesis, Sriwijaya University.
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Abstract
Video conferencing is a multimedia communication service that provides simultaneous video, audio and data communication services. Video conferencing is used for long-distance communication that brings together two or more people by utilizing broadband services. Recently, due to the impact of Covid-19, video conferencing services have been widely used by the national and international community. The classification of network traffic is an important basis for managing network quality and network security. Machine Learning classification with the Support Vector Machine method provides learning to distinguish different application network traffic based on their characteristics. This research uses the Support Vector Machine algorithm by utilizing three kernels, namely linear kernel, polynomial kernel and radial basis function (RBF) kernel in the classification process. The results of this study indicate that there are differences in characteristics between the cisco webex skype application traffic data. In addition, this study shows the effect of gamma values in the classification process and the accuracy results obtained. Of the three kernels used, the highest accuracy result is the RBF kernel with 99.11% accuracy, 99.45% precision, 99.09% recall and 99.27% f1 score.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | JARINGAN, APLIKASI SKYPE |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA168 Systems engineering |
Divisions: | 09-Faculty of Computer Science > 56201-Computer Systems (S1) |
Depositing User: | Helti Yuniar |
Date Deposited: | 23 Sep 2022 04:52 |
Last Modified: | 23 Sep 2022 04:52 |
URI: | http://repository.unsri.ac.id/id/eprint/79351 |
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