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Salsabila, Destiana
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Computer Science & IT Education

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Klasifikasi dan Pemetaan Spasial Kualitas Udara Berbasis ISPU Menggunakan Support Vector Machine dengan Data Multisumber: Indonesia Salsabila, Destiana; Utami, Nurul Fadila
Jurnal Sains & Teknologi Lingkungan Vol. 17 No. 2 (2025): SAINS & TEKNOLOGI LINGKUNGAN
Publisher : Teknik Lingkungan Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/jstl.vol17.iss2.art6

Abstract

Indonesia, particularly DKI Jakarta, faces severe challenges regarding air pollution, with PM2.5 concentrations far exceeding the thresholds set by the WHO, placing Jakarta among the top cities with the highest levels of air pollution. This study aims to provide a comprehensive overview of air quality conditions in DKI Jakarta, classify air quality using SVM algorithm, and generate high-resolution air quality maps by integrating data from air quality monitoring stations (SPKU) and satellite imagery. The methodology involves imputation and SMOTE-Tomek Link resampling techniques to address missing data and class imbalance problems. The results indicate that air pollution levels in DKI Jakarta fluctuate throughout the 2022–2024 period. Satellite imagery data contains more missing values, however, classification models based on these data still demonstrate optimal performance. In contrast, data from SPKU shows significant improvement in model performance after resampling. Spatial maps derived from satellite data offer finer resolution and can estimate air quality in areas beyond SPKU coverage.
Co-Authors Utami, Nurul Fadila