<![CDATA[Posyandu in Dawuan Barat determines the nutritional status of children by looking at the growth chart in KIA and calculating the z-score manually and then matching the results to the category table and threshold, this takes a long time and is at risk of being inaccurate. The formulation of the problem in this study is how to do classification of data mining to determine the nutritional status of toddlers and how the evaluation results from the classification model. This study uses the C4.5 algorithm with the CRISP-DM methodology to classify the nutritional status of toddlers and uses a confusion matrix to determine the accuracy, precision, recall and f1-score values of the classification model and then the model is implemented into an application. The evaluation results of the 3 model scenarios in this study stated that scenario 1 produced the best performance among other models with 90% accuracy and 87% value of precision, recall and f1-score]]>
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