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All Journal Journal of Computation Physics and Earth Science
Arsy, Muhammad Naufal Afif Al
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Physics

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Model Prediksi Konsentrasi PM2.5 di Wilayah Jakarta Menggunakan Algoritma Random Forest Arsy, Muhammad Naufal Afif Al; Yasir, Ahmad Meijlan
Journal of Computation Physics and Earth Science (JoCPES) Vol 5 No 1 (2025): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63581/JoCPES.v5i1.04

Abstract

This study predicts PM2.5 concentrations in Jakarta using the Random Forest algorithm with historical air quality data from 2015 to 2024. Hyperparameter tuning was performed to optimize model performance, focusing on parameters such as n_estimators, max_depth, and min_samples_split. The model achieved a Mean Absolute Error (MAE) of 14.44, a Root Mean Square Error (RMSE) of 18.75, and an R² Score of 0.61. While the model captured general PM2.5 fluctuation patterns, deviations at certain points indicate room for improvement. Descriptive analysis showed an average PM2.5 concentration of 94.46 µg/m³, with peaks up to 209 µg/m³, exceeding healthy air quality thresholds. The model can be integrated into real-time monitoring systems and support data-driven policies. Future work could incorporate meteorological variables and evaluate longer-term trends to enhance accuracy.
Co-Authors Yasir, Ahmad Meijlan