Prediction of Monthly Rainfall using Fuzzy Logic Tsukamoto in Medan Belawan - Dian Aulia Zulfa; Hendra Cipta (EduMatSains : Jurnal Pendidikan, Matematika dan Sains, 2025)
Rainfall prediction plays an important role in understanding the pattern of rainfall movement for daily life. This research aims to predict monthly rainfall in Medan Belawan using the Tsukamoto fuzzy logic method. Tsukamoto fuzzy logic is used to predict monthly rainfall in Medan Belawan. This method uses several steps, starting from data input, fuzzification, inference, to defuzzification to help predict rainfall. This research aims to apply Tsukamoto fuzzy logic to monthly rainfall prediction. Fuzzy logic has tolerance for imprecise data. This rainfall prediction uses 4 (four) input variables, namely air temperature, air humidity, air pressure and wind speed, and 1 (one) output variable, namely rainfall as a crips value which is the output generated for rainfall prediction. The data used is 12 monthly data from January 2023 to December 2023. The results show the accuracy of the fuzzy method of 57.75% using the MAPE calculation and show that the calculation of the Tsukamoto fuzzy method is sufficient or feasible to do.