Prediksi Perubahan Iklim Ekstrem di Kota Palembang dan Kaitannya dengan Fenomena El Niño-Southern Oscillation (ENSO) Berbasis Machine Learning


  • Melly Ariska Universitas Sriwijaya
  • Hamdi Akhsan
  • Muhammad Muslim Universitas Sriwijaya
  • Muhammad Romadoni Universitas Sriwijaya
  • Fena Siska Putriyani Universitas Sriwijaya



Climate Change, ENSO, Rainfall, Niño 3.4, Machine Learning, Palembang City


The purpose of this study is to provide predictions of climate conditions and trend of temperature rise in the city of Palembang in the 21st century. The BMKG station data used, namely SK Palembang and SM SMB II from the 2000-2020 period were analyzed based on the agreement of the Expert Team for Climate Change Detection and Indices (ETCCDI). ). Analysis using google colab shows that rainfall in the city of Palembang has a fairly high variability and a decrease in the number of rainy days that occur in the city of Palembang with the trend of air temperature, namely TMAXmean and TMINmean, has increased significantly by 2.40C for 50 years. Based on the correlation analysis between rainfall and El Niño-Southern Oscillation (ENSO) with Google Colab, a negative relationship was found. The El Niño-Southern Oscillation (ENSO) index used is the Niño 3.4 index. The study concluded that although the geographical location of Palembang city is located in the Asian Monsoon area, the ENSO phenomenon does not significantly affect rainfall variability in Palembang city.


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How to Cite

Ariska, M., Akhsan, H., Muslim, M., Romadoni, M., & Putriyani, F. S. (2022). Prediksi Perubahan Iklim Ekstrem di Kota Palembang dan Kaitannya dengan Fenomena El Niño-Southern Oscillation (ENSO) Berbasis Machine Learning. JIPFRI (Jurnal Inovasi Pendidikan Fisika Dan Riset Ilmiah), 6(2), 79–86.
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