<![CDATA[Forest and land fires are a serious problem that often occurs in Indonesia, especially duringthe dry season. The impact is very wide, ranging from ecosystem damage, health problems, to economiclosses. This research aims to design and build an Internet of Things (IoT)-based forest fire predictionsystem using the Fuzzy Logic method. The system is equipped with a temperature sensor (DHT22),smoke sensor (MQ-4), and flame sensor (Flame Sensor) connected to a ESP8266 NodeMCUmicrocontroller. The data collected by the sensors will be processed and analyzed using the Fuzzy Logicmethod to determine the level of fire risk with the categories of "Safe", "Alert", and "Dangerous". Thetest results showed that the system was able to detect changes in temperature, humidity, smoke, and thepresence of fire in real-time and provide alerts through the website. The temperature sensor has anaverage error of 4.8%–5%, humidity of 4.1%–4.5%, and the fire sensor is able to detect fire up to adistance of 300 cm. With a good level of accuracy, the system can improve preparedness in dealing withpotential wildfires and help authorities take preventive actions quickly and effectively.]]>
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