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General Information
    • ISSN: 1793-8244
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Dr. Ka Wai Gary Wong
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET),  Electronic Journals Library, Ulrich's Periodicals Directory, EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
Dr. Ka Wai Gary Wong
Division of Information and Technology Studies, Faculty of Education, The University of Hong Kong.
It's a honor to serve as the editor-in-chief of JACN. I'll work together with the editors and reviewers to help the journal progress
JACN 2014 Vol.2(3): 173-177 ISSN: 1793-8244
DOI: 10.7763/JACN.2014.V2.106

Forecasting Network Activities Using ARIMA Method

Haviluddin and Rayner Alfred
Abstract—This 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.

Index Terms—Network traffic, ARIMA, time series, forecasting.

Haviluddin is with the School of Natural Science, Department of Computer Science, Universitas Mulawarman, 75119 Samarinda, Indonesia (e-mail: haviluddin@gmail.com).
Rayner Alfred is with the COESA, Universiti Malaysia Sabah, 88400 Kota Kinabalu, Sabah, Malaysia (e-mail: ralfred@ums.edu.my).


Cite:Haviluddin and Rayner Alfred, "Forecasting Network Activities Using ARIMA Method," Journal of Advances in Computer Networks vol. 2, no. 3, pp. 173-177, 2014.

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