Machine Learning Sistem Monitoring Limbah Pembuangan Pabrik Gas Berbasis Iot Menggunakan Algoritma C4.5 Pada Platfrom Blynk (Studi Kasus Pabrik Samator Cidahu) - Hermawan, Rian; Fahruroji, Muhammad Arman; Jadhira, Ardhi Akmaludin (STMIK Subang, 2025)
Air pollution remains a major environmental issue, with NH?, CO, and CO? among the most harmful gases produced by transportation, industry, and agriculture. Increased concentrations of these gases can threaten human health and ecosystems. This research aims to design a monitoring device to detect CO and CO? levels in the atmosphere using Internet of Things (IoT) technology. A prototype system was developed with an ESP8266 microcontroller, Gas sensor for gas detection, DHT22 sensor for temperature and humidity, and Fire sensor for fire detection. The collected data are processed using the C4.5 algorithm to classify air quality into five categories: good, moderate, unhealthy, very unhealthy, and hazardous. Results are displayed through the Blynk platform, allowing real-time monitoring and easy access for the public. The case study was conducted around the Samator plant in Subang, where the system demonstrated the ability to provide timely and accurate information on air conditions. This IoT-based solution is expected to improve community awareness of air pollution risks and serve as an initial step toward environmental monitoring and control