Penerapan Metode MFCC dan Naive Bayes untuk Deteksi Suara Paru-Paru

  • Ni Made Ayu Suandewi universitas udayana
  • I Gede Arta Wibawa
  • I Gusti Ngurah Anom Cahyadi Putra
  • I Komang Ari Mogi
  • Ngurah Agus Sanjaya ER
  • Cokorda Rai Adi Pramartha

Abstract

Lung disease is an unpleasant illness that can be dangerous if not treated properly. This is because lung disease can infect others. The lungs are an important part of the human organ that distributes oxygen throughout the body, so this lung disease needs to be treated with proper procedures. Lung disease problems can be solved using an expert system. Expert systems can help doctors work to provide an early diagnosis of ear diseases. The method used in this study is the MFCC method, which provides compelling information about lung disease and provides treatment solutions based on the symptoms of each existing disease. This system is performed by calculating the symptom weights of the disease, which is obtained from expert experience, and produces the optimum value in the form of the maximum value. The highest value data provides the results of the disease diagnosis at the level of confidence in the form of percentage values. Based on the test results, the goodness of fit between the system diagnostics using the system validation test method and the expert diagnostic results is 90%. The results of the tests performed show that the system is operating normally according to its capabilities.

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Published
2022-07-08
How to Cite
AYU SUANDEWI, Ni Made et al. Penerapan Metode MFCC dan Naive Bayes untuk Deteksi Suara Paru-Paru. JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 11, n. 1, p. 75-82, july 2022. ISSN 2654-5101. Available at: <https://ojs.unud.ac.id/index.php/jlk/article/view/87005>. Date accessed: 12 june 2024. doi: https://doi.org/10.24843/JLK.2022.v11.i01.p08.

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