Analysis of Tuberculosis (TB) on X-ray Image Using SURF Feature Extraction and the K-Nearest Neighbor (KNN) Classification Method

Reyhan Achmad Rizal, Nurlela Octavia Purba, Lidya Aprilla Siregar, Kristina Sinaga, Nur Azizah

Abstract


With current technological developments, machine learning has become one of the most popular methods, one of the popular machine learning algorithms is k-nearest neighbors (KNN). Machine learning has been widely used in the medical field to analyze medical datasets, in this study the k-nearest neighbors (KNN) machine learning algorithm will be used because of its good level of accuracy in recognition and is included in the supervised learning algorithm group. The results showed the k-nearest neighbors (KNN) method in recognizing x-ray images of tuberculosis (TB) using SURF feature extraction with an average accuracy of 73%.

Keywords


Tuberkulosis, KNN, SURF

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DOI: http://dx.doi.org/10.32497/jaict.v5i2.1979

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