Simulation and Prediction of Rainfall and Crop Yield in West Java Using ANFIS

Ruminta Roem, Tati Nurmala


Simulation of numerical data for prediction purposes is very important for the planning and anticipation of the future, for example, prediction data of rainfall and agricultural production. There are various models to simulate and forecast the numerical data, one of which is a artificial intelligence model using ANFIS. In this connection it has studied a simulation and prediction of rainfall and agricultural production in West Java using ANFIS. The study uses data of rainfall and crop production. The method of this study is descriptive explanatory which is a type of quantitative analysis. Numerical data were analyzed using ANFIS of the Software Matlab 8.0. The study results showed that ANFIS can simulate rainfall and crop yield with highly accurate and has the potential to be used as one of the alternative model to predict rainfall and crop yield in West Java


artificial intelligence, ANFIS, crop yield, numeric data, rainfall pattern

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