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All Journal Journal of Robotics, Automation, and Electronics Engineering
Tanzila Bagus Ramadhan
Universitas Negeri Yogyakarta
Electrical & Electronics Engineering Engineering

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Air Quality Classification Using the K-Nearest Neighbors Algorithm: A Case Study in Juwana District Tanzila Bagus Ramadhan; Dessy Irmawati
Journal of Robotics, Automation, and Electronics Engineering Vol. 4 No. 1 (2026): March 2026
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v4i1.2553

Abstract

Air quality is an important factor in maintaining human health and environmental sustainability. Increasing transportation activity in Pati Regency contributes to higher air-pollutant emissions. This study develops a real-time air-quality monitoring and classification system using the K-Nearest Neighbors (KNN) algorithm. The system uses MQ-7, MQ-135, and SDS011 sensors to measure CO, CO₂, PM2.5, and PM10 concentrations. Measurement data are transmitted to Firebase Realtime Database and classified through a graphical user interface using Euclidean distance. Experimental results show that the system achieves 83% accuracy, 85% precision, 83% recall, and an F1-score of 82%. These results indicate that the proposed system can provide reliable real-time air-quality information for environmental monitoring applications.
Co-Authors Dessy Irmawati