Random Forest Algorithm to Measure the Air Pollution Standard Index

Setiawan, Ariyono and Wibowo, Untung Lestari and Mubarok, Ahmad and Larasati, Khoirunnisa and Hammad, Jehad A.H (2024) Random Forest Algorithm to Measure the Air Pollution Standard Index. Knowledge Engineering and Data Science, 7 (1). pp. 86-100. ISSN 2597-4637

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Abstract

This study uses the Random Forest algorithm to measure and predict the Air Pollution Standard Index (APSI) at Blimbing Banyuwangi Airport. Air pollution data, including concentrations of O3, CO, NO2, SO2, PM2.5, and PM10, were collected from air monitoring stations at the airport from April 15-30, 2024. APSI measurement followed established formulas by relevant authorities. Data analysis utilized statistical approaches and computational algorithms. The findings reveal that air quality at the airport is generally "Moderate," with occasional "Good" days. The Random Forest algorithm effectively predicts APSI based on existing pollution data. These results provide insights for improving air pollution management at the airport and surrounding areas, emphasizing the need for continuous air quality monitoring. Days classified as "Moderate" suggest health risks for sensitive groups, indicating the need for targeted mitigation strategies. Recommendations include increasing green spaces, optimizing flight schedules to reduce peak pollution, and raising public awareness about air quality. The effectiveness of the Random Forest algorithm suggests its potential application in other airports for proactive air quality management. Future research could integrate real-time data and advanced machine learning models for more accurate and timelier APSI predictions.

Item Type:	Artikel Umum
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisi / Prodi:	Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Electrical Engineering (S1-Teknik Elektro)
Depositing User:	M.Eng. Alfian Ma'arif
Date Deposited:	21 Apr 2025 01:46
Last Modified:	21 Apr 2025 01:46
URI:	http://eprints.uad.ac.id/id/eprint/83075

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