Air Quality Classification Using Support Vector Machine - Ade Silvia Handayani; Sopian Soim; Theresia Enim Agusdi; Nyayu Latifah Husni (Computer Engineering and Applications Journal, 2021)
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.