Weather Forecast for Bandar Lampung City Using Random Forest and C4.5

Abstract

Weather forecasts are important information for various agencies and the wider community. Weather forecasts are usually used to benefit various sectors such as transportation, tourism, plantations and others. This study aims to create a new model regarding weather forecasting using the random forest and C4.5 algorithms using the WEKA application. The dataset uses data from the Panjang Maritime Meteorological Station with 365 days of data and six attributes: rain intensity, average temperature, humidity, rainfall, sunshine duration and average wind speed. The results obtained from this study between the random forest algorithm and C4.5, namely cross-validation trials fold 5, 10 and 15 random forests, have better results than C4.5 by using the MAE and RMSE evaluation values, then in testing with a percentage split 25% on the evaluation of the MAE value is better at C4.5. Still, the random forest has better results for all experiments evaluating the RMSE value and two evaluations of the MAE value.