Pemodelan Geospasial Beban Polusi Udara Jakarta: Integrasi Data AOD dan PM₂.₅ Untuk Menentukan Wilayah Dengan Tingkat Kerawanan Tertinggi
DOI:
https://doi.org/10.54082/jupin.2327Kata Kunci:
AOD, Geospasial, Jakarta, PM₂.₅, Polusi UdaraAbstrak
Polusi udara partikulat halus (PM₂.₅) merupakan ancaman kesehatan lingkungan utama di Jakarta. Meskipun pemantauan berbasis stasiun darat memberikan akurasi tinggi, keterbatasan jumlah sensor menyebabkan adanya celah informasi geospasial. Di sisi lain, data satelit Aerosol Optical Depth (AOD) menawarkan cakupan luas namun sering kali memiliki bias dalam merepresentasikan konsentrasi polutan di permukaan tanah. Penelitian ini bertujuan untuk memodelkan beban polusi udara di Jakarta secara geospasial dengan mengintegrasikan data satelit AOD (MODIS MCD19A2) dan data ground-station PM₂.₅ periode Desember 2022 hingga Maret 2025 untuk menentukan wilayah dengan tingkat kerawanan tertinggi. Metodologi penelitian melibatkan sinkronisasi data temporal, normalisasi Max-Scaling, dan penerapan model integrasi terbobot. Untuk meminimalkan bias atmosfer atas dan memprioritaskan risiko kesehatan nyata, diterapkan pembobotan variabel sebesar 80% untuk PM₂.₅ dan 20% untuk AOD. Lima titik pemantauan dianalisis, yaitu Bundaran HI, Kelapa Gading, Jagakarsa, Lubang Buaya, dan Kebon Jeruk. Hasil penelitian menunjukkan bahwa wilayah Lubang Buaya (Jakarta Timur) memiliki tingkat kerawanan tertinggi dengan skor indeks gabungan sebesar 0,966 dan rata-rata konsentrasi PM₂.₅ sebesar 76,91 µg/m³. Wilayah Kebon Jeruk menempati peringkat kedua (0,951), sementara Jagakarsa tercatat sebagai wilayah dengan kerawanan terendah (0,864). Penelitian ini menyimpulkan bahwa model integrasi terbobot efektif dalam mengidentifikasi titik panas (hotspot) polusi yang sering kali tidak tertangkap sepenuhnya oleh sensor satelit tunggal. Hasil ini merekomendasikan perlunya intervensi kebijakan mitigasi yang lebih intensif di wilayah Jakarta Timur dan Barat sebagai zona kerawanan pencemaran polusi udara prioritas.
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