Network Traffic Time Series Performance Analysis Using Statistical Methods

Purnawansyah Purnawansyah (Universitas Muslim Indonesia)
Haviluddin Haviluddin ((SCOPUS ID: 56596793000, Universitas Mulawarman))
Rayner Alfred (Universiti Malaysia Sabah)
Achmad Fanany Onnilita Gaffar (State Polytechnic of Samarinda)

Knowledge Engineering and Data Science
Vol 1, No 1 (2018)

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.