Classification of Lung Diseases Using The Naive Bayes Classifier Method at Madani Hospital Medan in 2025

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Authors: Refi Sulistiasari, Handi Efendi, Agus Sumedi, Marlina Elfa Lubis, Zaim Anshari
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Abstract

The lungs are one of the human organs that are very important in the respiration process. There are several types of lung diseases, including Asthma, Bronchitis, Dyspnea Pleural Effusion, Empyema, Emphysema, Pulmonary Fibrosis, Lung Cancer, Interstitial Lung Disease, Pleurisy, Pneumonia, COPD, Tuberculosis. In this case there are difficulties in the process of classifying lung diseases, because the symptoms shown by sufferers of lung disease have similarities between one lung disease and another. The purpose of this study is to classify lung diseases using the Naive Bayes Classifier method. This method was chosen because it only requires a little training data to determine the estimated parameters needed in the classification process. This research was conducted at Madani General Hospital, Medan Area District, Medan City, North Sumatra, from February 1, 2025 to April 1, 2025. The data taken were medical records of lung disease patients from January 1, 2025 to February 1, 2025, totaling 134 patient data containing 19 disease symptoms and 6 disease diagnoses. From the test results using the Rapidminer application and data separation in the form of 34 test data and 100 training data with a data ratio of 7:3, an accuracy value of 97.06 was obtained

Fields of Study & Subjects

Artificial Intelligence in Healthcare Data Mining and Machine Learning Applications Text and Document Classification Technologies

Publication details

Journal / source
International Journal of Public Health Excellence (IJPHE)
Volume
5
Issue
2
Pages
60–70
Publication date
6 February 2026
Language
EN