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A rainfall forecasting using fuzzy system based on genetic algorithm

Weather forecasting information is very crucial in decision making process regarding to activities and works, such as in the field of agriculture to determine initial growing season. Recently, climate change causes trouble in weather forecasting. In this paper, rainfall forecasting system using fuzzy system based on genetic algorithm (GA) is made. The data used within this research is taken from Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG) for Kemayoran area, Jakarta. Those data include temperature, air pressure, rainfall, solar radiation, relative humidity, and wind speed. Based on experiment result, it can be concluded that the combination of GA and Fuzzy for Kemayoran weather data can produce prediction model with higher than 90% accuracy with several population size and crossover probability. This condition is highly affected by input data and conducted classification. Obtained model can be used in predicting rainfall class for the next day that divided into 4 class of no-rain or mild rain (<;=20 mm), moderate rain (<;=50 mm), heavy rain (<;=100 mm), and very heavy rain (>100 mm).