Application of the Tsukamoto Fuzzy Inference System Method for Rainfall Prediction in the Adolina Area

Aditia Sanjaya

doi:10.59934/jaiea.v5i3.2281

Authors

Aditia Sanjaya Universitas Negeri Medan

DOI:

https://doi.org/10.59934/jaiea.v5i3.2281

Keywords:

Rainfall Prediction, Fuzzy Inference System, Tsukamoto, Weather, Adolina

Abstract

Rainfall is one of the key elements in the climate system that significantly affects various sectors, such as agriculture, spatial planning, and disaster mitigation. Adolina, a region with tropical weather characteristics and highly fluctuating rainfall, requires an accurate prediction system to support informed decision-making. This study applies the Fuzzy Inference System (FIS) Tsukamoto method to predict rainfall based on input variables such as air temperature, humidity, and wind speed. The Tsukamoto method is chosen for its capability to handle uncertainty and produce crisp output values through inference and defuzzification processes based on a set of fuzzy rules. The results show that the Tsukamoto FIS provides reasonably accurate and consistent rainfall predictions with a low error rate. Therefore, this approach can serve as an effective alternative in weather decision-support systems for the Adolina area.

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