IMPLEMENTASI METODE K-NEAREST NEIGHBOR UNTUK KLASIFIKASI PENYAKIT PARU-PARU PADA ANAK

Risma Alfiatul Karima
Zaehol Fatah

Jurnal Ilmiah Multidisiplin Ilmu
Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)

Lung disease, especially in children, is a significant health problem and can have serious consequences if not diagnosed and treated quickly. Implementation of the K-Nearest Neighbor method as a classification of lung disease in children. This algorithm allows medical data analysis to identify patterns related to lung disease symptoms to achieve a high level of accuracy in predicting lung disease risk. The results of the test show that K-Nearest Neighbor can produce an effective and accurate prediction model, with CAP data accuracy of 83.33%, and provides useful insights for early diagnosis and decision-making in children's health care.