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Forecasting Model for Hotspot Bandwidth Management at Department of Electrical Engineering and Information Technology UGM

A.E. Permanasari, I. Hidayah, I.A. Bustoni

Abstract


Bandwidth management for UGM-Hotspot Wireless network in the Department of Electrical Engineering and Information Technology UGM have been managed manually by looking at data traffic at one time then sharing it to user. This make bandwidth sharing becomes less effective. Therefore, automation management becomes necessary to adjust bandwidth allocation based on daily use. In order to meet this purpose, it requires an analysis to find the appropriate forecasting model that can be applied in the development of automation. Different types of statistical methods are used to produce accurate forecasting of network bandwidth, one of them is Autoregressive Integrated Moving Average (ARIMA) method. Unfortunately, this method is less accurate for modeling the UGM-Hotspot network traffic because its seasonal trends. Thus, this study implemented Seasonal ARIMA (SARIMA) with the addition of outlier detection to obtain more accurate prediction. Based on the result, SARIMA(0,1,1)(0,1,1)7, that included constant, was the most appropriate model. This model achieved forecasting accuracy 14.49% with outlier detection. It could reduce error compare to model with outlier (32%).

Keywords


Forecasting; bandwidth; hotspot; SARIMA; outlier.

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