Wearable Health Technology dengan AI Prediktif untuk Pencegahan Stunting Anak di Indonesia - Yustinus (PT. PENERBIT TIGA MUTIARA, 2025)
Stunting remains a crucial public health issue in Indonesia as it has multidimensional impacts on physical growth, cognitive development, productivity, and the long-term quality of human resources. This study aims to analyze the potential application of predictive Artificial Intelligence (AI)-based Wearable Health Technology in preventing child stunting, with an emphasis on the integration of technology into the health system, socio-cultural interrelations, and ethical dimensions that need to be anticipated. The research employed a qualitative approach through a systematic literature review, analysis of national health policies, and examination of reports on the implementation of digital health technologies related to child health. The results indicate that wearable devices are effective in recording health indicators in real-time, while predictive AI algorithms enable early detection of stunting risks, allowing interventions to be carried out quickly, accurately, and in a personalized manner. However, the success of implementation is highly dependent on the support of the digital health ecosystem, including adaptive regulations, infrastructure readiness, digital literacy among communities, as well as multi-stakeholder collaboration involving the government, medical professionals, the technology industry, and families. This study affirms that the integration of Wearable Health Technology and predictive AI is not merely an additional tool in medical services, but rather a representation of a health system transformation towards a more preventive, predictive, precise, and participatory paradigm. Thus, the utilization of evidence-based digital innovations has the potential to strengthen the effectiveness of stunting prevention programs in Indonesia while accelerating the achievement of national health development targets within the context of technological disruption and global dynamics.