Timbangan Pintar sebagai Alternatif Pencegahan Stunting Berbasis Internet Of Things dan Artificial Intelligence

Abstract

Elementary school children are individuals in the 6-12 age group who experience significant physiological growth, requiring optimal nutrition to support their development, and are among the demographics highly vulnerable to malnutrition. Data from the Indonesian Ministry of Health shows that in 2018, the prevalence of stunting reached 37.2%, with approximately 8 million children experiencing suboptimal growth. Challenges in monitoring children's nutritional status, particularly in areas with limited access, often hinder early prevention efforts. This study develops a Smart Weighing system integrated with Internet of Things (IoT) and Artificial Intelligence (AI) as an alternative solution for monitoring children's nutrition to prevent stunting. The system uses the Fuzzy Logic method to process children’s data, such as height, weight, and activity level, through IoT sensors. The analyzed results are then presented in an Android application, providing nutrition recommendations and nutritional status information that parents can easily understand. System accuracy tests showed a precision level of up to 95% in monitoring children’s weight and height. This innovation is expected to enhance parental engagement in nutrition monitoring, thereby accelerating progress toward achieving stunting reduction targets in Indonesia.