Air Pollution Assessment of Samarinda Using the C4.5 Algorithm
DOI:
https://doi.org/10.51967/tanesa.v24i2.2946Keywords:
ESP32, Air quality, C4.5 Algorithm, Internet of Things, Classifying air qualityAbstract
The degradation of air quality in numerous Indonesian cities is attributed to the swift proliferation of motorised vehicles, rapid population growth, and inadequate green spaces. Samarinda, the capital of East Kalimantan province, is plagued by high levels of pollution resulting from heavy vehicle exhaust emissions. The provision of accurate air quality information can mitigate respiratory issues. However, the public does not have access to air quality information due to the high cost of air quality measuring devices. Therefore, an Internet of Things (IoT)-based air pollution monitoring system using ESP32 is needed to provide interactive and real-time information. This study tested the C4.5 algorithm to classify air quality data based on six measurement parameters: PM10, PM2.5, CO, O3, and NO2. PM10 and PM2.5 particles are the primary pollutants that significantly impact human health. The World Health Organization (WHO) has set an annual quality standard value of 20μg/m3 for PM10 and 10μg/m3 for PM2.5. Carbon Monoxide (CO) can reduce the blood's ability to carry oxygen, which can affect the function of vital organs such as the heart and brain. Ozone (O3) on the Earth's surface is a harmful pollutant that can damage the lungs and other respiratory systems. Nitrogen dioxide (NO2) can cause lung inflammation and lower immunity to infections, such as influenza and pneumonia. This study uses the C4.5 algorithm to classify air quality data based on these parameters, which are important for determining air quality. The results show that air quality is divided into two types: good and moderate, with different proportions each day. The C4.5 algorithm achieved a success rate of 99.5074% and a failure rate of 0.4926% when processing air quality data. It was effective in classifying air quality and processing data. An Internet of Things (IoT)-based air pollution monitoring system using ESP32 is needed to provide interactive and real-time information to the public.
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