Pemanfaatan Jaringan Saraf Tiruan untuk Prediksi Curah Hujan di Sumatera Utara
DOI:
https://doi.org/10.61132/mars.v2i6.457Keywords:
Artificial Neural Network, Weather Prediction, Rainfall, North Sumatra, BMKG, Climate DataAbstract
The use of Artificial Neural Networks (JST) for weather prediction is one of the innovative approaches in climate data analysis. This study aims to apply JST in predicting weather, especially rainfall and the number of rainy days in the North Sumatra region. Historical weather data obtained from BMKG Region I for 2022-2023 is used as input to train the JST model. With a training process that involves processing rainfall data, this model is expected to provide accurate predictions regarding weather patterns. The results of this research can help in agricultural sector planning, disaster risk mitigation, and natural resource management. JST has proven to be effective in identifying dynamic and complex weather patterns, so it has the potential to be used in long-term weather prediction.
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