Penerapan Algoritma Klasifikasi Nearest Neighbor Dalam Mendeteksi Penyakit Diabetes

Abstract

The purpose of writing this article is to determine the application of the nearest neighbor classification algorithm in diabetes detection. This nearest neighbor classification algorithm is a classification method often used to classify objects based on available data. This method works by searching for the closest objects in the dataset and classifying the new objects based on the closest object category. The application of the KNN algorithm can be carried out in various fields, such as analyzing the feasibility of credit granting, classifying online news materials or diagnosing diabetes. In this article, the researcher uses a literature review research method assisted by a descriptive analysis approach, to analyze the data and by describing the data that has been previously collected where the author describes data that has been obtained from various literary sources such as journals, data and others. The data obtained will be analyzed and interpreted in accordance with the objective of this research, which is to determine the application of nearest neighbor classification to detect diabetes.