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p-Index From 2020 - 2025
0.23
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All Journal International Journal of Science and Mathematics Education
Ardea Dewantari Prasetya
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Education Mathematics Social Sciences

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Machine Learning Approaches for Climate Change Prediction: A Comparative Study Ardea Dewantari Prasetya; Abdul Latif Rahman; Muhammad Indra Novanto
International Journal of Science and Mathematics Education Vol. 1 No. 2 (2024): June:International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v1i2.57

Abstract

This research explores various machine learning approaches, including deep learning and ensemble methods, to predict climate change indicators. We focus on temperature and precipitation trends using large datasets spanning multiple decades. By comparing the performance of algorithms like CNN, RNN, and random forests, we identify the most accurate models for specific climate variables. Our findings demonstrate that ensemble models provide better accuracy and reliability, especially for temperature predictions.
Co-Authors Abdul Latif Rahman Muhammad Indra Novanto