Optimization of Stunting Prevention and Reduction through Early Detection Application, Sunting, based on Forward Chaining Inference Machine.

Abstract

Stunting is a chronic malnutrition problem caused by a prolonged lack of sufficient nutrient intake, resulting in impaired growth and shorter stature (dwarfism) in children compared to age standards. In Indonesia, the prevalence of stunting remains high according to WHO standards, mainly due to the limited information available on stunting, particularly regarding preventive measures. In the era of Industry 4.0, rapid technological advancements, especially in the field of healthcare, have provided enhanced access to information and early disease diagnosis through expert system-based applications. The objective of this research is to design an application that assists the community in early detection of stunting in children, enabling timely intervention. The chosen approach involves forward chaining inference machine, testing input symptoms to draw conclusions based on the knowledge rules stored in the knowledge base. The outcome of this research is an application that facilitates parents and integrated service posts in preventing stunting disorders in children. Highlight:  Intervensi Tepat Waktu: Aplikasi ini memungkinkan deteksi dini stunting, memungkinkan intervensi tepat waktu untuk mencegah gangguan pertumbuhan pada anak. Pendekatan Sistem Pakar: Memanfaatkan inferensi rantai maju, aplikasi menggunakan pengetahuan Integrasi Teknologi dan Layanan Kesehatan: Memanfaatkan kemajuan Industri 4.0, aplikasi ini menjembatani kesenjangan antara teknologi dan layanan kesehatan, memberdayakan masyarakat dan pos layanan terpadu untuk memerangi stunting secara efektif. Kata kunci: Stunting, Sistem pakar, Deteksi dini, Pelayanan kesehatan terpadu, Industri 4