IMPLEMENTASI METODE FUZZY TSUKAMOTO DAN TOPSIS DALAM PENENTUAN STATUS GIZI ANAK BERDASARKAN INDEKS MASSA TUBUH (IMT)

Abstract

The nutritional status of children is a critical factor that affects physical and cognitive development. This study aims to develop a web-based Decision Support System (DSS) to determine children's nutritional status using the Body Mass Index (BMI) as the primary indicator. The system integrates the Fuzzy Tsukamoto method to handle linguistic variables related to BMI and the TOPSIS method to rank alternatives based on multiple criteria, including age, weight, height, arm circumference, and BMI. A quantitative descriptive approach was applied, and data were collected from health centers through direct measurements and secondary sources. The system calculates BMI, applies fuzzy rules to classify nutritional status, and uses TOPSIS to support decision ranking. Results show that the system effectively classifies children's nutritional status into three categories: undernutrition, good nutrition, and very good nutrition. The implementation demonstrates that the combined methods enhance the accuracy and objectivity of assessments, making it a valuable tool for health workers at community health posts and clinics. However, the system's reliance on BMI alone and the limited dataset present constraints. Future improvements should include additional health indicators and integration with real-time health data systems.