<![CDATA[The nutritional status of toddlers is an important indicator in assessing the health of a community, especially during the growth period of childhood. Nutritional problems that are not handled properly can have an impact on the physical and cognitive development of toddlers. Therefore, a method is needed that can help health workers classify the nutritional status of toddlers quickly and accurately. This study aims to apply the C.45 algorithm in classifying the nutritional status of toddlers at the Wairasa Health Center. The data used in this study included the age of toddlers, weight, and height, with the output class in the form of nutritional status of toddlers consisting of good nutrition, poor nutrition, and severe malnutrition. The research methods used included data collection, pre-processing of data, application of the C.45 algorithm, formation of a decision tree, and evaluation of the model using a matrix of confusion and accuracy values. The results of the study showed that the C.45 algorithm was able to produce decision trees and classification rules that were easy to understand and had a fairly good level of accuracy in classifying the nutritional status of toddlers. Thus, the application of the C.45 algorithm can be used as a decision support tool for health center staff in determining the nutritional status of toddlers objectively and efficiently.]]>
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