Tsukamoto Fuzzy In IoT-Based Automatic Control System Of Kitchen Smoke MSME Palembang Crackers - Putri, Nadia; Lindawati; Aryanti (JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING, 2025)
MSMEs, particularly producers of *kerupuk kemplang* from Palembang, often face challenges in managing kitchen smoke generated during production. This smoke not only pollutes the air and poses health risks to workers but also reduces comfort and productivity. Therefore, this study aims to design an Internet of Things (IoT)-based control system using the Fuzzy Tsukamoto algorithm to automatically regulate the exhaust fan speed based on temperature, smoke concentration, and carbon monoxide (CO) levels. This system introduces technological innovation to enhance efficiency and productivity in MSME kitchen management. The method involves using MQ135, MQ7, and DHT11 sensors to detect kitchen environmental conditions in real time. The collected data is processed by the NodeMCU ESP8266 microcontroller using the Fuzzy Tsukamoto algorithm and is then used to adjust the exhaust fan speed via an AC dimmer. The monitoring results are displayed on the Blynk IoT application for easy access. The study results show that the system successfully reduces smoke concentration by up to 30 ppm and CO levels by 40 ppm while maintaining the kitchen temperature within an optimal range of 49°C to 55°C. With a Mean Absolute Percentage Error (MAPE) of 7.66% and an accuracy rate of 92.34%, the system proves to be effective and responsive to changes in kitchen environmental conditions. The implementation of this Fuzzy Tsukamoto and IoT-based system has a positive impact on improving air quality, ensuring worker health, and increasing MSME productivity. Additionally, this system supports a more modern, efficient, and environmentally friendly kitchen management approach, making it an innovative solution for the *kerupuk kemplang* production industry