Implementation of ARIMA Model to Asses Seasonal Variability Macrobenthic Assemblages

Abstract

Human activities, including industrial and aquaculture, may have impact on water environment, especially organic enrichment. One of bioindicator of pollution that affect the quality of the water ecosystem is macrobenthic community. In general, the more diverse macrobenthic assemblages indicate the better of the waters quality. Understanding spatial and temporal distribution of macrobenthic abundance has become an important part of research in the field of ecology in understanding the level of environmental disturbance over time. This study discussed the application of the method of Autoregressive Integrated Moving Average (ARIMA) to asses seasonal variability ofmacrobentic assemblages. We found that forecasting using autoregressive integrated moving average method with the model of ARIMA (0,1,1) is obtained the smallest value of the Mean Square Deviation (MSD).