Analisa Data Mining Untuk Prediksi Penyakit Kanker Paru Dengan Algoritma Regresi Linear

Abstract

Lung cancer often causes no symptoms in its early stages. New symptoms appear when the cancer is large enough or has spread to surrounding tissues and organs. So that patients with lung cancer will only feel pain after the cancer spreads to the pleural layer, the thin layer that covers the lungs. This study aims to analyze lung cancer in early prevention. This study uses prediction techniques and stages in data mining to predict data on patients suffering from lung cancer with a linear regression algorithm method using rapidminer tools. training and 10% data testing. The results of the tests that have been carried out show that the variables or attributes used in this study (age, smoking, and test results) have a significant effect on this study, as evidenced by using a linear regression algorithm to provide good results with a Root Mean Squared Error value: 0.379 +/- 0.000 and Squared Error: 0.144 +/- 0.229. The conclusion of the research conducted by applying the linear regression algorithm can be made a prediction based on the functional relationship on the variables or attributes in the data.

Keywords: Lung cancer, linear regression algorithm, Rapidminer