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Please use this identifier to cite or link to this item: http://repository.unmul.ac.id/handle/123456789/3601
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dc.contributor.authorPurnawansyah, Purnawansyah-
dc.contributor.authorHaviluddin, Haviluddin-
dc.contributor.authorGaffar, Achmad Fanany Onnlita-
dc.contributor.authorTahyudin, Imam-
dc.date.accessioned2020-01-17T02:15:24Z-
dc.date.available2020-01-17T02:15:24Z-
dc.date.issued2017-06-29-
dc.identifier.isbn978-3-319-59279-4-
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/3601-
dc.description.abstractA 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.en_US
dc.language.isoenen_US
dc.publisherInternational Conference on Management Science and Engineering Management ICMSEM 2017en_US
dc.subjectNetwork traffic; K-Means; Fuzzy C-Means; Clusteringen_US
dc.titleComparison Between K-Means and Fuzzy C-Means Clustering in Network Traffic Activitiesen_US
dc.typeArticleen_US
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