Abstract
The neglect of a healthy lifestyle among the Indonesian population has led to an increased risk of diabetes mellitus, which currently affects 643 million people worldwide. Early and accurate diagnosis is crucial for preventing the progression of the disease. This study utilized the C4.5 machine learning algorithm to develop a model that can classify individuals as diabetic or non-diabetic based on factors associated with diabetes. The data used in this research consisted of medical records from patients with and without diabetes at Padang General Hospital. The model's performance evaluation resulted in a recall value of 91%. By promoting a healthy lifestyle and raising awareness about the importance of regular check-ups, the burden of diabetes can be reduced, and the overall health of the population can be improved.
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