Implementation of an IoT-based Threshold Method for a Food Hazardous Substance Detection Tool - Malinda, Threa; Salamah, Irma; Anugraha, Nurhajar (ISB Atma Luhur, 2025)
Food safety is a critical issue that has a direct impact on public health. Illegal addition of hazardous substances such as rhodamine B, melachite green, methanyl yellow, formalin, borax, and sodium hypochlorite are still commonly found in food products sold in the market. This research project aims to develop a tool for detecting hazardous substances in Internet of Things (IoT) based foods using a threshold method that refers to BPOM regulations. The threshold method refers to BPOM regulations. This system integrates two sensors: The TCS3200 sensor is used for RGB color analysis, and the HCHO sensor detects volatile compounds detecting volatile compounds. Test results show that this tool achieves 96.67% accuracy in identifying hazardous substances without producing false positives. The novelty of this research lies in combining both sensors into one system with real-time notification via Telegram. This research is novel because it combines both sensors into one system with real-time notifications via Telegram. It combines both sensors into a single system with real-time notifications via Telegram and ThingSpeak.