Penggunaan Metode Fuzzy Logic Untuk Mendeteksi Gizi Buruk Pada Balita

Abstract

Nutrition has a crucial role in terms of health in life, especially in toddler nutrition. Poor nutrition can affect a child's physical growth, intelligence, and productivity. Factors such as economic conditions, parental attention, and an unsupportive environment can cause cases of malnutrition in toddlers. Less optimal nutritional monitoring in toddlers affects the growth and development of toddlers. This study seeks to develop applications based on Fuzzy Logic as a detection of malnutrition in toddlers, focusing on Pusk-esmas Semidang Alas Seluma Regency. This study discusses the variables of assessing malnutrition in toddlers, applying the Fuzzy Logic method in detecting these conditions, and designing applications to diagnose malnutrition in toddlers. The research also includes counseling the public about weight changes in malnourished toddlers and general nutritional status, by providing input to improve services for malnourished toddlers. Application development involves aspects of display and data, as well as testing with related parties to ensure the accuracy of detection results. User criticism and suggestions become valuable input for the improvement and development of this application.