Prediksi Curah Hujan Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS) - Muhammad Isradi Azhar; Wayan Firdaus Mahmudy (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Rainfall is the amount of rain that occurs in an area within a certain period of time. Information of rainfall is useful in various fields such as agriculture. In the field of agriculture, the information of rainfall can affect the annual planting period and also can determine what kind of crops that are suitable to be planted. Malang Regency is one areas in Indonesia which has 36.359 Ha farming area and produce rice equal to 470.285 Ton. Rice crops have a common criteria for determining the beginning of the rice growing season, with the amount of rainfall more than 50 mm in three consecutive dasarians. But the current wet season is uncertain which resulted in the process of rice cultivation is disrupted. Therefore, rainfall prediction is needed to help farmers to reduce the possibility of loss. Adaptive Neuro Fuzzy Inference System (ANFIS) method can be used to predict rainfall by utilizing dasarian data of rainfall, temperature, humidity, and wind speed. Adaptive Neuro Fuzzy Inference System (ANFIS) is a combination of neural network and fuzzy logic. In the learning process of Adaptive Neuro Fuzzy Inference System (ANFIS), there is backpropagation steepest descent and least square Iestimator (LSE) algorithm. Based on the test results using the best parameters, it obtain best RMSE value of 1.88.