DEVELOPMENT OF THE INFLOW PREDICTION MODEL ON TROPICAL RESERVOIR USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM

Inflow prediction is a key in component planning, design, operation, development, and maintenance of availiable water resources. The inflow prediction model have many benefits in the application of Water Resources such as flood control, preventing drought, and optimizing reservoir operation for hydropower system sustainability. The main purpose of the research is to develop of model to predict the inflow of hydro electric power plant reservoir considering the importance of information on sufficient in this reservoir everyday so that the hydro electric power plant can continue to operate. The method of research approach used is using Adaptive Neuro Fuzzy Inferences System developed a hybrid system between fuzzy logic and artificial neural network as branch of softcomputing. The location of research on the Kotopanjang hydro electric power plant reservoir in Merangin Village, Kampar Residence, Riau Province. The data used in this research is secondary data in the form of inflow data of Kotopanjang hydro electric power plant reservoir which has been done by PT PLN (Persero) KIT Sumbagut Sektor, KIT Pekanbaru from 2007-2012. The main results of the research proved that the implementation of a inflow prediction model on the tropical reservoir in Kampar Residence using the ANFIS method with cross validation approach for the next annual (Qt+1) has a very strong classification tested using statistical parameters coefficient of correlation (R) and mean absolute percentage error (MAPE) respectively value of 0.94 and 12.86 %