Rahmah Amanda, Halmar Halide
Airports are vital facilities whose operations are strongly influenced by meteorological conditions, particularly wind parameters that play an important role in aviation safety. This study aims to analyze the characteristics of wind speed and predict extreme wind events up to 12 hours ahead around Sultan Hasanuddin International Airport. The data used in this study were obtained from METAR reports from the Class I Meteorological Station of Sultan Hasanuddin during 2025, including parameters such as wind direction, wind speed, gust, visibility, and air pressure. The data were processed using Visual Studio Code and Microsoft Excel, and the Random Forest method was applied to develop the prediction model. The results show that most wind conditions in the study area fall into the normal category, with relatively fewer extreme wind events. Model evaluation indicates that the model is capable of detecting extreme wind events with relatively small prediction error, as indicated by a Root Mean Square Error (RMSE) value of approximately 0.20. The developed model is also able to provide predictions of potential extreme wind events up to 12 hours ahead based on the observed data patterns.
