Open AccessSimulation and Prediction of Rainfall and Crop Yield in West Java Using ANFIS
Author(s) -
Ruminta Roem,
Tati Nurmala
Publication year - 2017
Publication title -
jurnal matematika integratif/jurnal matematika integratif
Language(s) - English
Resource type - Journals
eISSN - 2549-9033
pISSN - 1412-6184
DOI - 10.24198/jmi.v13.n2.11844.83-94
Subject(s) - java , adaptive neuro fuzzy inference system , matlab , yield (engineering) , computer science , agricultural engineering , production (economics) , dssat , crop simulation model , anticipation (artificial intelligence) , software , crop yield , crop , environmental science , meteorology , fuzzy logic , machine learning , engineering , artificial intelligence , ecology , forestry , geography , materials science , fuzzy control system , economics , biology , metallurgy , macroeconomics , programming language , operating system
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