Stunting is a growth disorder in children due to chronic malnutrition and recurrent infections, especially in the first 1,000 days of life. Assessment of stunting status that only relies on height and weight measurements is considered ineffective because it does not cover all aspects that affect a child's nutritional status. At Posyandu Bougenvile, stunting identification is still done manually and is at risk of causing errors in decision making. This study aims to develop a web-based Decision Support System (DSS) using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to assist Posyandu cadres in determining toddler stunting status quickly, accurately, and efficiently. This system processes data from four main anthropometric indicators, namely Height/Age, Weight/Age, Weight/Age, and BMI/Age. The results of the system calculations show agreement with manual calculations, which proves that the system is working optimally. An example of the results shows that toddlers with code A1 (Rafasya Malik) have the lowest preference value of 0, followed by A4 (Ihsan Dwi Hanggoro) with a value of 0.4022149 which is included in the high stunting risk category. This system has proven to be able to help Posyandu cadres in prioritizing the handling of at-risk toddlers, as well as supporting the stunting monitoring process in a more structured and data-based manner.
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