Data Mining Approach To Classify Tumor Morphology Using Decision Tree Algorithm - Fasya Dzul Fikri Akbar; Irfan Darmawan; Rahmat Fauzi (eProceedings of Engineering, 2018)
Abstract— Tumors are a general term used to describe the growth of abnormal masses or tissues in the body that include benign tumors, malignant tumors and unidentified tumors. Malignant tumors are known as cancer. The operation of cancer data using a fairly popular tool that is rapidminer. Topics of discussion about classification of patients with tumor disease using Decision Tree algorithm on Rapidminer tools that use supporting variables such as age, sex and place of tumor on the body / topography. The output of the research is a decision tree with a precision of 85.53% that can be used and implemented by the hospital to facilitate socialize the importance of tumor disease to the community in the hope that the community can prevent as early as possible about the danger of tumor disease. Because most people happen to come to the hospital when it has been affected by a malignant tumor (regardless of cost factor), based on xyz hospital data. Keywords— Data Mining, Decision Tree, Classification, Tumor Disease