Memanfaatkan Teknik Machine Learning dan Deep Learning untuk Meramalkan Curah Hujan dan Cuaca: Sebuah Tinjauan

Ndaumanu, Daniela Adolfina
Irviandi, Risnu

Journal of Computation Physics and Earth Science
Vol 2 No 2 (2022): Journal of Computation Physics and Earth Science

Machine learning and deep learning are vital for achieving precise rainfall and weather forecasting, which is crucial for agricultural planning, managing water resources, and reducing disaster risks. This study reviews a range of literature on weather and rainfall forecasting, emphasizing deep learning techniques. Additionally, it examines the performance of various machine learning models, including Long Short-Term Memory (LSTM) networks and Support Vector Regression (SVR), in improving forecast accuracy. These methods show notable improvements in accuracy over traditional models. The study’s findings suggest that enhanced machine learning and deep learning models can significantly benefit weather forecasting, aiding in climate change adaptation efforts.