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dc.contributor.authorSwandari Paramita Yadi Yasir Yuniati Yuniati Ibnu Sina
dc.date.accessioned2019-10-18T15:09:12Z
dc.date.available2019-10-18T15:09:12Z
dc.date.issued2014
dc.identifier.issn1793-8244
dc.identifier.urihttp://repository-ds.unmul.ac.id:8080/handle/123456789/335
dc.description.abstractThis paper presents an approach for a network traffic characterization by using an ARIMA (Autoregressive Integrated Moving Average) technique. The dataset used in this study is obtained from the internet network traffic activities of the Mulawarman University for a period of a week. The results are obtained using the Box-Jenkins Methodology. The Box-Jenkins methodology consists of five ARIMA models which include ARIMA (2, 1, 1) (1, 1, 1)12, ARIMA (1, 1, 1) (1, 1, 1)12, ARIMA (2, 1, 0) (1, 1, 1)12, ARIMA (0, 1, 0) (1, 1, 1)12, and ARIMA (0, 1, 0) (1, 2, 1)12. In this paper, ARIMA (0, 1, 0) (1, 2, 1)12 was selected as the best model that can be used to model the internet network traffic.
dc.publisherJournal of Advances in Computer Networks (JACN)
dc.titleForecasting Network Activities Using ARIMA Method


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