Child Nutritional Development Monitoring System Using Fuzzy Logic Method
DOI:
https://doi.org/10.58761/jurtikstmikbandung.v14.i2.197Keywords:
child nutrition monitoring system, fuzzy logic, Fuzzy Inference System, toddler nutrition monitoring, anthropometry, nutritional statusAbstract
This study developed a Child Nutrition Monitoring System based on the web that utilizes a Fuzzy Inference System (FIS) to automatically assess the nutritional status of toddlers. The system was designed with a fuzzy logic module comprising fuzzification, inference rules, and defuzzification to process anthropometric data such as weight, height, and age. The system was tested using an anthropometric dataset of ≥10 toddlers and compared with manual assessments based on WHO Z-score standards. Evaluation results show that the system can produce nutritional status classifications consistent with manual calculations, and help posyandu cadres monitor toddlers’ nutritional development regularly through an interactive dashboard. This study demonstrates that the integration of information technology with fuzzy logic can enhance the efficiency and accuracy of child nutrition monitoring at the community level. Recommendations for further development include expanding the dataset and integrating digital sensors for automatic data input.
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