<![CDATA[Lung cancer is one of the deadliest types of cancer worldwide. Therefore, efforts to predict the likelihood of developing lung cancer are very important in its prevention and treatment. One way to predict the likelihood of getting lung cancer is to use a linear regression algorithm. This study aims to develop a predictive model that can identify a person's likelihood of developing lung cancer based on certain factors, such as age, passive smoker and level or severity. The data used in this study were collected from 100 patients diagnosed with lung cancer and their severity. The results of the analysis show that the linear regression algorithm can be used to predict the probability of getting lung cancer with an accuracy of about 90% and is able to give good results with a Root Mean Squared Error: 0.686 +/- 0.000 and Squared Error: 0.471 +/- 0.546]]>
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