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Data from the Indonesian Toddler Nutrition Status Survey (SSGBI) in 2021, the prevalence of stunting in Indonesia is still quite high, at 24.4%, which is equivalent to 5.33 million toddlers. This figure is still above the standard tolerated by WHO, which is below 20%. Therefore, efforts are needed to accelerate stunting reduction so that the prevalence of stunting in toddlers decreases to 19.4% by 2024. This research aims to develop a tool for measuring toddlers' height and weight to assess their nutritional status promptly, aiming to preemptively address any nutritional abnormalities and prevent exacerbation. Anthropometry serves as the primary method for assessing toddlers' nutritional status in this study. The tool's design incorporates the ESP32 as the main control unit, the HC-SR04 sensor for height measurements, and the HX711 module and loadcell sensor as weight sensors. Data from the sensor are transmitted from the ESP32 master to the ESP32 slave for processing, culminating in a nutritional status assessment. Notably, the tool boasts a minimal error rate of 0.18% for weight measurement with 99.82% accuracy and a 2.66% error rate for height measurement with 97.34% accuracy. Furthermore, the tool's integration with IoT technology offers additional advantages. It facilitates real-time data transmission and analysis, enabling healthcare professionals to promptly identify any nutritional issues in toddlers. This, in turn, allows for timely intervention and appropriate management strategies to prevent the development or exacerbation of stunting. Overall, the benefits of this research for the Anthropometry Stunting Monitor based on IoT are manifold. It enhances accuracy and efficiency in measuring toddlers' height and weight, enables early detection of stunting, and facilitates timely intervention to address nutritional abnormalities. This holds significant promise for improving pediatric healthcare outcomes and reducing the prevalence of stunting among children.
Rosari et al. (Tue,) studied this question.