Meramalkan Curah Hujan di Kabupaten Maros dengan Menggunakan Metode Adaptive Neuro Fuzzy Inference System
DOI:
https://doi.org/10.20956/ejsa.v7i1.26433Keywords:
Rainfall, Fuzzy Time Series, Generalized Bell, Fuzzy Inference System, Neural Network, Adaptive Neuro Fuzzy Inference SystemAbstract
The adaptive neuro-fuzzy inference system or ANFIS method is a hybrid of the fuzzy time series method and artificial neural networks. This algorithm maps the input data in the input layer to the target in the output layer via neurons in the hidden layer using time series data. The working principle of ANFIS has layers that function as input and output. This study aims to obtain the results of rainfall forecasting using the ANFIS method in Maros Regency, South Sulawesi. This research is divided into training data and testing data with details of 292 training data and 73 test data. Then the forecasting results were obtained using 73 test data, namely the period October 20 - October 31, which obtained a value of 0.384% from the calculation of MAPE (Mean Absolute Percentage Error) in the very good forecasting category. The correlation coefficient was obtained by 0.99 with a strong correlation category. So, it can be concluded that the ANFIS method can predict rainfall in Maros Regency with a good degree of accuracy.
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