KLASIFIKASI TINGKAT AEROSOL ULTRAVIOLET MENGGUNAKAN ALGORITMA GAUSSIAN MIXTURE MODEL DENGAN MENGGUNAKAN INSTRUMEN TROPOMI PADA SENTINEL-5P NRTI AER

GUSTIANA, ALPA (2024) KLASIFIKASI TINGKAT AEROSOL ULTRAVIOLET MENGGUNAKAN ALGORITMA GAUSSIAN MIXTURE MODEL DENGAN MENGGUNAKAN INSTRUMEN TROPOMI PADA SENTINEL-5P NRTI AER. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

(Abstract--Air pollution in Bandung City, Indonesia, particularly ultraviolet aerosol, has a significant negative impact on health and the environment. This study utilizes the Gaussian Mixture algorithm to cluster ultraviolet aerosol levels based on TROPOMI data from the Sentinel-5P satellite. Data was collected during November 2023, a period chosen due to the occurrence of El Niño and Bandung's geographical conditions. The data was processed through clipping, stacking, and raster mosaicking before modeling. The model was evaluated using metrics such as Confusion Matrix, Cohen’s Kappa, and statistical analyses like RMSE, MSE, MAPE, and R-squared. The research results obtained from the model show an Accuracy of 98%, Precision of 97%, Recall of 98%, F1-Score of 97%, and Cohen's Kappa of 0.96. This study provides deep insights into the variability of ultraviolet aerosols in Bandung, supports air pollution mitigation efforts, and enhances scientific understanding of the impact of air quality on human health and the environment. Keyword: Air Quality, Gaussian Mixture Model, Pollution, Sentinel-5P, Ultraviolet Aerosol (Abstrak--Polusi udara di Kota Bandung, Indonesia, terutama aerosol ultraviolet, memiliki dampak negatif signifikan pada kesehatan dan lingkungan. Penelitian ini menggunakan algoritma Gaussian Mixture untuk mengklasterisasi tingkat aerosol ultraviolet berdasarkan data TROPOMI dari satelit Sentinel-5P. Data dikumpulkan selama November 2023, periode yang dipilih karena adanya kejadian El Nino dan kondisi geografis Bandung. Data diproses melalui clipping, stacking, dan mosaik raster sebelum dimodelkan. Model dievaluasi menggunakan metrik seperti Confusion Matrix, Cohen’s Kappa, dan dan statistikal analisis seperti RMSE, MSE, MAPE, R-squared. Hasil penelitian yang didapatkan dari model yang digunakan dengan Accuracy 85%, Precision 76%, Recall 85%, F1-Score 80%, dan, Cohen's Kappa 0,96. Penelitian ini memberikan wawasan mendalam tentang variabilitas aerosol ultraviolet di Bandung, mendukung upaya mitigasi polusi udara, dan meningkatkan pemahaman ilmiah tentang dampak kualitas udara pada kesehatan manusia dan lingkungan. Kata Kunci: Aerosol Ultraviolet, Gaussian Mixture Model, Polusi, Sentinel-5P, Kualitas Udara

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