Downscaling Spasial Data Curah Hujan TRMM di Wilayah Sumatera Selatan dengan Algoritma Artificial Neural Network dan Random Forest Regression

Harisdianto Harisdianto, Azhar Kholiq Affandi, Menik Ariani, Suhadi Suhadi

Abstract


Pemahaman tentang karakter distribusi curah hujan temporal dan spasial sangat penting dalam menunjang studi tentang ekologi, meteorologi, dan hidrologi. Penelitian ini memetakan kembali distribusi spasial curah hujan tahunan TRMM di wilayah Sumatera Selatan pada resolusi tinggi menggunakan teknik downscaling berbasis machine learning, Artificial Neural Network (ANN) dan Random Forest Regression (RFR). Prediktor yang digunakan yaitu NDVI, DEM, Longitude dan Latitude. Proses downscaling spasial curah hujan TRMM dengan model ANN memiliki akurasi R^2 0, 6494, RMSE 728 mm/tahun dan MAE 715 mm/tahun. Model RFR memiliki kinerja lebih baik dengan nilai R^2 0,6818, RMSE 695 mm/tahun dan MAE 683 mm/tahun.

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References


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DOI: https://doi.org/10.56064/jps.v25i3.906

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