Comparison Between K-Means and Fuzzy C-Means Clustering in Network Traffic Activities

被引：4
|
作者：
Purnawansyah [1 ]
Haviluddin [2 ]
Gafar, Achmad Fanany Onnilita [3 ]
Tahyudin, Imam [4 ]
机构：
[1] Univ Muslim Indonesia, Fac Comp Sci, Makassar, Indonesia
[2] Mulawarman Univ, Fac Comp Sci & Informat Technol, Samarinda, Indonesia
[3] State Polytech Samarinda, Samarinda, Indonesia
[4] STMIK AMIKOM, Dept Informat Syst, Purwokerto, Indonesia
来源：
PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT | 2018年
关键词：
Network traffic; K-Means; Fuzzy C-Means; Clustering;
D O I：
10.1007/978-3-319-59280-0_24
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A network traffic utilization in order to support teaching and learning activities are an essential part. Therefore, the network traffic management usage is requirements. In this study, analysis and clustering network traffic usage by using K-Means and Fuzzy C-Means (FCM) methods have been implemented. Then, both of method were used Euclidean Distance (ED) in order to get better results clusters. The results showed that the FCM method has been able to perform clustering in network traffic.
引用
收藏
页码：300 / 310
页数：11
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