Application of Fuzzy Tsukamoto Method to Rainfall Prediction in Sleman Regency

Abstract

The context of this research is that erratic rainfall can disrupt community activities, especially for traders who want to make sales. In addition, information about rainfall is also needed by farmers in determining planting patterns in order to get maximum yields. The purpose of this research is to be able to help farmers predict rainfall to get maximum crop yields. One method to be able to predict rainfall is Fuzzy Logic. This research will use the Tsukamoto Fuzzy method. In the research conducted this time, the author conducted monthly rainfall forecasting in Sleman Regency. Rainfall data in Sleman Regency from 2015 to 2022 will be used in this research. This research succeeded in getting a MAPE value of 49.31%. The result of this research is the highest monthly rainfall prediction in November, with a rainfall of 713.78 mm. At the same time, the lowest occurred in August, which amounted to 36.47 mm. This research only gets a MAPE value of 49.31%. So it can be concluded that the Tsukamoto fuzzy method cannot predict rainfall well.

Keywords

• fuzzy logic
• prediction
• rainfall
• sleman regency
• tsukamoto