<![CDATA[This research aims to design and develop an Internet of Things (IoT)-based monitoring system as an early warning tool for tsunami disasters, capable of monitoring sea wave height, wind speed, and wind direction in real time. The system integrates an MPU6050 sensor to detect wave height, an optocoupler sensor for wind speed, and a Hall Effect sensor for wind direction. The collected data is processed by an Arduino Mega 2560 microcontroller and transmitted via an ESP32 module to a Telegram application as a notification medium. A simulation was conducted on a 1:200 scale using an aquarium, where artificial waves represented hazardous sea waves. The test results showed that the system achieved an accuracy rate of 99.77% for wave height measurements and 99.9427% for wind speed, with an average notification delay of 2.67 seconds. The system also successfully detected wind direction and coordinates accurately as designed. These findings suggest that the proposed system has the potential to serve as an efficient and affordable small-scale solution for marine disaster monitoring, with the possibility of further development for real-world applications in coastal areas.]]>
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