<![CDATA[Forest fires are a frequent disaster in Indonesia, especially during the dry season, which has serious impacts on ecosystems, public health, and economic conditions. This research aims to design a prototype Internet of Things (IoT)-based forest fire early detection system supported by LoRa transmission technology and Thingspeak cloud storage platform. The system uses DHT22 sensors to measure temperature and humidity, MQ-2 sensors to detect the presence of gas and smoke, and solar panels as the main power source to support energy efficiency in the field. LoRa was chosen as the communication medium due to its ability to transmit data over long distances with low power consumption. Data read by the sensors is regularly sent to ThingSpeak and displayed graphically with an average transmission delay of 15 seconds. Tests have shown that the system is able to accurately recognize potential fires and send out early warnings quickly. In this way, the system can be an efficient and energy-saving solution for remote forest areas. Overall, this prototype has successfully demonstrated its potential as a reliable and innovative forest fire mitigation tool.]]>
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