<![CDATA[The water quality of the Ciujung River in Serang has experienced a significant decline due to domestic and industrial waste pollution, directly affecting public health and environmental sustainability. Current monitoring systems remain largely manual and lack responsiveness, resulting in delayed and less data-driven pollution management. This study aims to develop an Internet of Things (IoT)-based water quality monitoring system integrated with an intelligent dashboard to support sustainable environmental programs. The proposed system monitors key water quality parameters, including pH, temperature, turbidity, and total dissolved solids (TDS), in real time. The methodology includes designing a microcontroller-based sensor prototype, integrating data communication modules (LoRa/GSM), processing data via a cloud server, and implementing interactive visualization through a web-based dashboard. Furthermore, the system features an early warning mechanism when water parameters exceed environmental quality thresholds. Field trials are conducted at several strategic points along the Ciujung River to evaluate data acquisition reliability, connectivity stability, and sensor accuracy. The expected outcome is an efficient, responsive, and adaptive monitoring system that supports data-driven decision-making in river water management and reinforces commitments to sustainable development.]]>
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