Abstrak 
The Application of Seasonal Autoregressive Fractionally Integrated Moving Average (SARFIMA) in Forecasting of River Streamflow
Dadang Ruhiat, Toni Toharudin, Gumgum Darmawan
Universitas Padjadjaran, Proceeding of The 2nd International Conference on Applied Statistics 2016 ISSN : 2579-4361
Bahasa Inggris
Universitas Padjadjaran, Proceeding of The 2nd International Conference on Applied Statistics 2016 ISSN : 2579-4361
MAPE., Sarfima, seasonal factors
Time series modeling can be used in various fields including hydrology. River streamflow is one of the hydrological parameters which is not only affected by seasonal factors but also often identified to possess long memory pattern. In this paper, a modeling using Seasonal Autoregressive Fractionally Integrated Moving Average (SARFIMA) will be applied. The data used is historical data of Cimanuk river streamflow which is the result of 20-year documentation in monthly interval. SARFIMA model is then compared with ARFIMA. The analysis is done to comprehend how SARFIMA model is able to model seasonal factors and long memory pattern which is shown by the data of Cimanuk river streamflow. The result of the analysis shows that SARFIMA model is not suitable for this data based on MSE and MAPE value.