Design of Anthropometry Parameter Sensor with High Stunting Prevalence

Stunting, characterized by suboptimal growth and development in children, is a pressing health concern in Indonesia, with prevalence rates ranging between 30% to 39% across various regions. Addressing this issue is crucial for safeguarding the well-being and future of Indonesian children. In response, this study introduces an innovative system to measure body mass and height, critical anthropometric parameters for monitoring child health. The system utilizes an Arduino Uno microcontroller, an ultrasonic sensor for height measurement, and a load cell sensor for assessing body mass. The effectiveness of these instruments is evaluated based on their accuracy in measuring and storing data. This research highlights the importance of precise height and weight data as vital indicators of socio-economic influences, healthcare access, and nutritional quality, playing a significant role in public health interventions and strategies aimed at combating stunting. Additionally, the study explores the potential of Artificial Intelligence (AI) in predicting stunting by analyzing growth charts and leveraging Internet of Things (IoT) technology for data collection. The proposed system's architecture integrates four layers—Instrumentation, Information System, Business Intelligence, and Gamification—to create a comprehensive physical-cyber System. Preliminary tests reveal that the ultrasonic sensor accurately measures infant height with a marginal error of 0.8%, and the load cell sensor records baby weight with an error of 0.7% to 1.4%, both within the acceptable error range. These findings underscore the system's capacity to facilitate immediate and long-term health interventions, with the potential to transform public health outcomes and foster a healthier generation