MODEL PERAMALAN INTRUSI AIR LAUT PERIODE MUSIM KEMARAU DI ESTUARI MENGGUNAKAN ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS)

Abstract

The main purpose of this research was to develop a model of seawater intrusion forecasting in dry season periods at the estuary, which was caused by the influence of river flow discharge collision with tidal level using neuro fuzzy structure adaptive neuro fuzzy inference system, as the basic pattern that flow the water whenever it free from salt intrusion and also stop taking the water that is already influenced by salt intrusion. The results showed that fuzzy logic as a control process and artificial neural network as a forecast process using primary data of the measurment of salt intrusion’s length, the downstream river flow discharge, and the maximum level of  tidal the river mouth area of  Solo Estuary during the dry season period (from August until October). The model showed high accuration perfomance, which was proved by the mean square error value for the learning process of 0,00000354,  model  validation testing process of 1.799, and set value of plain  waters condition for the next 24 hours range of  32 kms from the Solo Estuary.