IMPLEMENTATION OF K-NEAREST NEIGHBOR ALGORITHM FOR CLASSIFICATION OF LUNG CANCER CAUSES - Almeyda, Hanindiya Putri; Khoiri, Zidan Fathannul; Haris, M Sabirin; Alkaff, Nabilah Husen; Sukmadiningtyas, Sukmadiningtyas (Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran, 2024)
Abstract: Lung cancer is most deadly cancers in the world. Identification and classification of the causes of understanding lung cancer is essential for developing more effective prevention and treatment strategies. The issue is that a lot of individuals are unaware about the characteristics and causes of lung cancer. The purpose of this study is to apply the K-Nearest Neighbor (K-NN) algorithm in the classification of the causes of lung cancer and provide education to the public must be aware of the traits of lung cancer patients and, to stay away from the causes of lung cancer. The dataset used consists of 309 samples with 16 relevant attributes. The K-NN algorithm was trained and tested to assess its ability to classify the factors that cause lung cancer. The results showed an accuracy of 90.32%, with a precision for the