Network Traffic Time Series Performance Analysis Using Statistical Methods

Network Traffic Time Series Performance Analysis Using Statistical Methods

This paper presents an approach for a network traffic characterization by using statistical techniques. These techniques are obtained using the decomposition, winter’s exponential smoothing and autoregressive integrated moving average (ARIMA). In this paper, decomposition and winter’s exponential sm...

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Main Authors: Purnawansyah Purnawansyah, Haviluddin Haviluddin, Rayner Alfred, Achmad Fanany Onnilita Gaffar
Format: Article
Language:English
Published: Universitas Negeri Malang 2017-12-01
Series:Knowledge Engineering and Data Science
Online Access:http://journal2.um.ac.id/index.php/keds/article/view/1236
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spelling doaj-6dc060369eea42d9a88ce426898ec4e92020-11-25T03:52:31ZengUniversitas Negeri MalangKnowledge Engineering and Data Science2597-46022597-46372017-12-01111710.17977/um018v1i12018p1-71391Network Traffic Time Series Performance Analysis Using Statistical MethodsPurnawansyah Purnawansyah0Haviluddin Haviluddin1Rayner Alfred2Achmad Fanany Onnilita Gaffar3Universitas Muslim Indonesia(SCOPUS ID: 56596793000, Universitas Mulawarman)Universiti Malaysia SabahState Polytechnic of SamarindaThis paper presents an approach for a network traffic characterization by using statistical techniques. These techniques are obtained using the decomposition, winter’s exponential smoothing and autoregressive integrated moving average (ARIMA). In this paper, decomposition and winter’s exponential smoothing techniques were used additive and multiplicative model. Then, ARIMA based-on Box-Jenkins methodology. The results of ARIMA (1,0,2) was shown the best model that can be used to the internet network traffic forecasting.http://journal2.um.ac.id/index.php/keds/article/view/1236
collection DOAJ
language English
format Article
sources DOAJ
author Purnawansyah Purnawansyah
Haviluddin Haviluddin
Rayner Alfred
Achmad Fanany Onnilita Gaffar
spellingShingle Purnawansyah Purnawansyah
Haviluddin Haviluddin
Rayner Alfred
Achmad Fanany Onnilita Gaffar
Network Traffic Time Series Performance Analysis Using Statistical Methods
Knowledge Engineering and Data Science
author_facet Purnawansyah Purnawansyah
Haviluddin Haviluddin
Rayner Alfred
Achmad Fanany Onnilita Gaffar
author_sort Purnawansyah Purnawansyah
title Network Traffic Time Series Performance Analysis Using Statistical Methods
title_short Network Traffic Time Series Performance Analysis Using Statistical Methods
title_full Network Traffic Time Series Performance Analysis Using Statistical Methods
title_fullStr Network Traffic Time Series Performance Analysis Using Statistical Methods
title_full_unstemmed Network Traffic Time Series Performance Analysis Using Statistical Methods
title_sort network traffic time series performance analysis using statistical methods
publisher Universitas Negeri Malang
series Knowledge Engineering and Data Science
issn 2597-4602
2597-4637
publishDate 2017-12-01
description This paper presents an approach for a network traffic characterization by using statistical techniques. These techniques are obtained using the decomposition, winter’s exponential smoothing and autoregressive integrated moving average (ARIMA). In this paper, decomposition and winter’s exponential smoothing techniques were used additive and multiplicative model. Then, ARIMA based-on Box-Jenkins methodology. The results of ARIMA (1,0,2) was shown the best model that can be used to the internet network traffic forecasting.
url http://journal2.um.ac.id/index.php/keds/article/view/1236
work_keys_str_mv AT purnawansyahpurnawansyah networktraffictimeseriesperformanceanalysisusingstatisticalmethods
AT haviluddinhaviluddin networktraffictimeseriesperformanceanalysisusingstatisticalmethods
AT rayneralfred networktraffictimeseriesperformanceanalysisusingstatisticalmethods
AT achmadfananyonnilitagaffar networktraffictimeseriesperformanceanalysisusingstatisticalmethods
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