<![CDATA[Posyandu is one of the village/kelurahan community institutions that accommodates community empowerment in basic social services whose implementation can be synergized with other services according to regional potential. One of the basic social activities at Posyandu is monitoring nutrition for toddlers. During the COVID-19 pandemic, posyandu cadres had difficulty bringing in experts or nutritionists to help check the nutritional condition of toddlers who came to the posyandu. So that posyandu cadres need a decision support information system that can assist in categorizing the nutritional status of toddlers, whether the toddlers are classified as malnourished, undernourished, and well-nourished. In this study, a decision support system will be built using the website-based K-Nearest Neighbor (KNN) method using the Bootstrap framework. The main function of the bootstrap framework is to create responsive websites. The website interface will work optimally on all screen sizes, both on smartphone screens and computer/laptop screens. The flow stage in this research is data collection, data pre-processing, which is then carried out by the mining process to find out the final results of this research. In this study, the classification model starts from the dataset which will be divided into training and testing data using split data which is then mined with a classification algorithm so that a classification model is generated and generates evaluation parameters. The model in this study was generated from the implementation of the K-NN (K-Nearest Neighbor) method. The software development method uses the waterfall method. The developed application is targeted to achieve the product readiness level indicator at level 2 where the technology data equipment to be developed allows it to be applied and the basic elements of the technology to be developed are known.]]>
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