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Please use this identifier to cite or link to this item: http://repository.unmul.ac.id/handle/123456789/3601
Title: Comparison Between K-Means and Fuzzy C-Means Clustering in Network Traffic Activities
Authors: Purnawansyah, Purnawansyah
Haviluddin, Haviluddin
Gaffar, Achmad Fanany Onnlita
Tahyudin, Imam
Keywords: Network traffic; K-Means; Fuzzy C-Means; Clustering
Issue Date: 29-Jun-2017
Publisher: International Conference on Management Science and Engineering Management ICMSEM 2017
Abstract: 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.
URI: http://repository.unmul.ac.id/handle/123456789/3601
ISBN: 978-3-319-59279-4
Appears in Collections:P - Computer Sciences and Information Technology

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