Stunting remains a significant public health concern in Indonesia, leading to lifelong developmental and economic disadvantages. This study aims to address limitations in conventional child growth monitoring by developing and validating an IoT-based system that integrates ultrasonic and load cell sensors, an ESP32 microcontroller, RFID identification, and cloud-based data management. The system enables automated, real-time measurement and digital record-keeping, accessible via a user-friendly dashboard. Empirical validation was conducted on 35 children at local Integrated Health Service Post (Posyandu), showing high measurement accuracy (±0.53 cm for height, ±0.08 kg for weight), rapid average data transmission (2.05 seconds), and strong agreement with manual gold standards (p > 0.05). Usability evaluations indicated high satisfaction among health cadres, with streamlined workflows reducing time and staff requirements. The findings demonstrate that the proposed IoT-based system offers an effective, scalable, and economically viable solution for improving child growth monitoring and supporting stunting prevention programs in community health settings.