<![CDATA[Ornamental fish farming at the partner-seller scale often faces operational efficiency challenges, particularly related to water quality management. Observations with partners revealed issues such as inefficient electricity costs and manual water drainage methods, which pose risks to fish health and increase workloads. This research aims to design an Internet of Things (IoT)-based water quality monitoring system to automate aquarium monitoring. The system uses an ESP32WROOM 32 microcontroller as the main processing unit, a turbidity sensor to detect water turbidity levels, and a water-resistant JSN-SR04T ultrasonic sensor to measure water levels. Test results showed that the turbidity sensor was able to operate with an average error rate of 11.56%. Meanwhile, the JSN-SR04T sensor demonstrated a very high level of accuracy, with a precision of ± 0.2 cm. In terms of connectivity, analysis of data transmission to the IoT platform demonstrated stable performance with an average latency of at least 0.1 ms. By implementing this system, sales partners can monitor aquarium conditions in real-time, optimize the use of electrical devices, and replace manual draining methods with a more scalable and efficient system. the JSN SR04T sensor achieves a precision of ±0.5 cm. Data transmission delay analysis yields an average latency of at least 0.1 ms, supporting responsive real-time monitoring. In conclusion, this monitoring system is proven to be valid and reliable, offering a robust and time-efficient solution for IoT-based aquarium water quality management.]]>
