Analisis dan Klasifikasi Polusi Udara Menggunakan Data Citra Satelit (Modis, Sentinel-5p, Himawari) dan Data PWV Dari CORS GNSS dengan Metode Machine Learning

Haq, Failaqul (2024) Analisis dan Klasifikasi Polusi Udara Menggunakan Data Citra Satelit (Modis, Sentinel-5p, Himawari) dan Data PWV Dari CORS GNSS dengan Metode Machine Learning. Masters thesis, Institut Teknologi Sepuluh Nopember.

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6016212006-Master_Thesis.pdf - Accepted Version
Restricted to Repository staff only until 1 April 2026.

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Abstract

Polusi udara adalah masalah lingkungan global yang berkembang pesat dan memiliki dampak serius terhadap kesehatan manusia serta ekosistem. Penelitian ini bertujuan untuk mengembangkan metode analisis dan klasifikasi polusi udara yang canggih dengan memanfaatkan data citra satelit (MODIS, Sentinel-5p, Himawari) dan data Precipitable Water Vapor (PWV) dari Continuous Operating Reference Station Global Navigation Satellite System (CORS GNSS) dalam kombinasi dengan teknik machine learning. Penelitian ini mencakup eskalasi masalah polusi udara dan potensi manfaat dari penggunaan teknologi satelit dan CORS GNSS dalam pemantauan polusi udara. Penelitian ini mengembangkan model analisis polusi udara yang dapat memprediksi tingkat polusi udara pada wilayah urban. Metodologi penelitian mencakup pengumpulan data dari citra satelit dan CORS GNSS, preprocessing data, serta pelatihan dan evaluasi model machine learning. Kami menggunakan berbagai metrik evaluasi untuk mengevaluasi kinerja model, seperti akurasi, presisi, recall, dan F1-Score. Model random forest yang dibuat mempunyai akurasi 84% pada proses pelatihan dengan data wilayah provinsi DKI Jakarta. Pada pengujian di wilayah kota Surabaya menunjukkan akurasi yang cukup bagus yaitu 86%. penelitian ini akan menggabungkan teknologi citra satelit dan CORS GNSS dengan metode machine learning untuk menghasilkan pemahaman yang lebih baik tentang polusi udara.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Polusi udara, Citra satelit, MODIS, Sentinel-5p, Himawari, Data PWV, CORS GNSS, Pembelajaran mesin, Klasifikasi.
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences > GE195.5 Green movement
T Technology > TD Environmental technology. Sanitary engineering > TD887.B58 Air pollutants. Bituminous materials
Divisions: Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29101-(S2) Master Thesis
Depositing User: Failaqul haq
Date Deposited: 16 Feb 2024 07:51
Last Modified: 16 Feb 2024 07:51
URI: http://repository.its.ac.id/id/eprint/107553

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