Algoritma Adaptive Neuro Fuzzy Inference System Untuk Perkiraan Intensitas Curah Hujan
Keywords:
Prediction, Precipitation, Adaptive Neuro Fuzzy Inference System.Abstract
Rainfall is the amount of rain that pours or falls within a certain period of time in an area. Rainfall information is useful in many areas. Therefore, fast, accurate and detailed information is indispensable. The method used to predict rainfall is the Adaptive Neuro Fuzzy Inference System (ANFIS) by utilizing daily rainfall data. Adaptive Neuro Fuzzy Inference System (ANFIS) method is a combination of artificial neural network and fuzzy logic. In the learning process, Adaptive Neuro Fuzzy Inference System (ANFIS) method is used LSE Recursive algorithm for advanced learning. The research phase starts from rainfall data collection, learning data, functional and non-functional analysis, ERD, Adaptive Neuro Fuzzy Inference System (ANFIS) method, and Root Means Squared Error (RMSE) calculation and the program is created using PHP and MYSQL as database storage. In this study, two input variables used in the form of rainfall data one day before and rainfall data two days earlier, obtained root means square error (RMSE) results of 17.7 in 1200 training data and 9.4 in 200 test data.
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