PERAMALAN LALU-LINTAS JARINGAN UGM HOTSPOT MENGGUNAKAN METODE SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE

• Main Authors: , ISNA ALFI BUSTONI, , Adhistya Erna Permanasari, S.T., M.T., Ph.D.
• Format: Theses and Dissertations NonPeerReviewed
• Published: [Yogyakarta] : Universitas Gadjah Mada 2014
• Subjects: ETD
• Online Access: https://repository.ugm.ac.id/130437/; http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=70859
• Institution: Universitas Gadjah Mada

Bandwidth management for UGM - Hotspot Wireless network in the Department of Electrical Engineering and Information Technology UGM is still managed manually by looking at traffic data at one time then share it manually. It make bandwidth sharing becomes less effective. It is necessary to automatically adjust bandwidth allocation based on the everyday use. However, before reaching the automation process, it requires an analysis to find the appropriate forecasting model that can be applied in the development of automation. Different types of methods are used to produce accurate forecasting of network bandwidth, one of them is ARIMA (Autoregressive Integrated Moving Average) method. However, this method is less accurate for modeling the UGM - Hotspot network traffic data because its seasonal trends. Thus, this study using Seasonal ARIMA( SARIMA ) with the addition of outlier detection so that the result becomes more accurate . Based on the result, MAPE(Mean Absolute Percentage Error) for SARIMA model with outlier detection (14 %) is better than SARIMA model without outlier detection (32 %).