Expert System for Classification of Nutrition in Young Children

As an expert system, it is a computer program that is supposed to represent the ability to solve problems (a human expert). The forward sequencing approach, which is a logical method that uses logical reasoning to move from a problem to a solution, is the expert system method used. The goal of this research is to create an expert system that can identify acute malnutrition in young children (aged 0–5 years). The information comes from the nutritionist's response to the query, and the information is collected through the doctors' responses to the questions posed by the researcher in order to collect the target will appear, and the user's nutritional status will be displayed. This data will be used exclusively for this article and to attain the most dependable variables. The user will be able to diagnose and treat a child's eating problem or illness with this system application. This system may be used by any sort of user due to its ease of use. Parents may better understand the significance of preventing acute malnutrition thanks to the system's inclusion of crucial information on acute malnutrition as well as the most recent news regarding children's health, after training and evaluating the data, accuracy results show that the NV approach is more reliable than others. Additionally, it is exceptional in its capabilities, has the benefit of quick training and testing execution, and has the lowest error rate compared to other algorithms. The total number of fixed tries for all algorithms, with SVC having the highest accuracy rate (90%), followed by (KNN).