<![CDATA[Aquaculture productivity is highly dependent on maintaining optimal water quality, yet traditional manual monitoring methods are labor-intensive and lack real-time capability. This study addresses this gap by designing and implementing an IoT-based real-time water quality monitoring system specifically for aquaculture, integrating pH, temperature, and turbidity sensors with Telegram notifications. The research and development (R&D) approach was employed to build a prototype system consisting of sensor nodes (ESP32 microcontroller with pH, DS18B20 temperature, and TSW-10TM turbidity sensors), a cloud server for data processing, and a Telegram Bot for instant alerts. System testing evaluated sensor accuracy, data transmission reliability, and notification effectiveness. The results demonstrated that the system performed with high accuracy, showing strong correlation (r > 0.99) with standard measurement tools and an average error below 3%. The data communication proved reliable, achieving a Packet Delivery Ratio (PDR) of 98.7% with an average end-to-end latency of 2.3 seconds. Crucially, the Telegram notification mechanism was 100% effective, delivering all threshold breach alerts with an average latency of only 3.8 seconds. These findings confirm the system's potential as a practical, efficient, and affordable solution for precision aquaculture. It enables continuous monitoring and provides early warnings, empowering farmers to take immediate corrective actions to prevent stock stress and economic losses, thereby contributing to the sustainability of small to medium-scale aquaculture operations in Indonesia.]]>
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