<![CDATA[Lung cancer is one of the leading causes of death worldwide. Early detection of this disease is crucial to improving patients' chances of recovery. In this study, lung cancer prediction was conducted using the C4.5 algorithm applied to a secondary dataset from Kaggle. The dataset consists of 150 records, divided into 80% for training data and 20% for testing data. The classification process was performed using RapidMiner software. The results indicate that smoking is the most significant factor influencing lung cancer prediction. The generated decision tree model demonstrated a relatively high accuracy level, making it a useful tool for assisting in the early detection of lung cancer in patients]]>
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