<![CDATA[Lung cancer is one of the one of the leading causes of death in the world. From this data there are several categories of people who are positive and negative for lung cancer, Here the researcher will display information on the exact number of people who contracted lung cancer from the data, and in this study using the Random Forest algorithm because Random Forest This research uses the Random Forest algorithm because Random Forest has a data set selection process. Has a data set selection process. to improve the performance of classification model. With feature selection, Random Forest can certainly work efficiently on big data with complex parameters, which will greatly facilitate the classification of positive and negative lung cancer patients. Observations will be a reference for analyzing the prognosis of lung disease. Observation will be a reference for analyzing the prognosis of lung disease here how the application of data data mining techniques on the prediction analysis of lung cancer analysis and how performance of the random forest algorithm in predicting lung cancer.by applying data mining techniques and has been tested using a survey dataset of lung cancer survey dataset and using software called Rapidminer toanalyze and predict positive patients with lung cancer It was concluded that the It is concluded that the Random Forest algorithm that has obtained the greatest accuracy obtained accuracy results worth 90.61% with an AUC value of 0.941.]]>
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