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All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Informatika dan Rekayasa Elektronik
Theresia Enim Agusdi
Politeknik Negeri Sriwijaya
Computer Science & IT Engineering

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Journal : ComEngApp : Computer Engineering and Applications Journal

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Air Quality Classification Using Support Vector Machine Ade Silvia Handayani; Sopian Soim; Theresia Enim Agusdi; Nyayu Latifah Husni
Computer Engineering and Applications Journal Vol 10 No 1 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.677 KB) | DOI: 10.18495/comengapp.v10i1.350

Abstract

Air pollution in Indonesia, especially in urban areas, becomes a serious problem that needs attention. The air pollution will impact on the environment and health. In this research, the air quality will be classified using Support Vector Machine method that obtained from the sensor readings. The sensors used in the detection of CO, CO2, HC, dust/PM10 and temperature, namely TGS-2442, TGS-2611, MG-811, GP2Y1010AU0F and DHT-11. After testing, the results obtained with classification accuracy of 95.02%. The conclusion of this research indicates that the classification using the Support Vector Machine has the ability to classify air quality data.
Co-Authors Ade Silvia Handayani Ali Nurdin Husni, Nyayu Latifah Rumiasih Rumiasih Sopian Soim, Sopian