CD Skripsi
Implementasi Metode Long Short Term Memory Dalam Prediksi Parameter Cuaca Kabupaten Karimun
Weather is an important factor in human life. Fluctuating weather changes can have an impact on extreme weather conditions or climate change over a relatively long period of time. The importance of weather predictions for decision making and preventive actions to reduce risks related to weather changes in various aspects of life. This research aims to obtain the best predictions for weather parameter data in Karimun Regency using the Long Short Term Memory (LSTM) method based on a combination of hyperparameters determined by the researcher. The combination that has the best performance is used to predict weather parameters for the next day. This research uses 8 parameters from Karimun Regency weather data. Based on the analysis results, it is known that each weather parameter has the best performance in different hyperparameter combinations. The RMSE value for the minimum temperature parameters is 0.8602, maximum temperature is 1.1755, average temperature is 0.8572, average humidity is 3.8877, rainfall is 15.0889, duration of sunlight is 2.7102, maximum wind speed is 1.0090 and average wind speed of 0.6740
Keywords:Weater, hyperparmeter, LSTM, prediction
Tidak tersedia versi lain