Penerapan Teorema Bayes untuk Mendiagnosa Penyakit Telinga Hidung Tenggorokan (THT)
DOI:
https://doi.org/10.30812/matrik.v18i2.398Keywords:
Ear, Nose and Throat disease, Bayes theorem, expert systems, computational timeAbstract
Ear, Nose and Throat Disease (ENT) is a common disease that is often considered a harmless disease by people, so they assume there is no need to see a doctor. But in fact, ENT disease can also provide serious disorders if not treated early and right, so the expert system of ENT is needed for early detection before the patient decided to see a doctor or not. Based on these problems, this study proposed the application of the Bayes theorem for early detection of ENT disease. The types of diseases used in this study were six types and had 22 symptoms. User inputs the symptoms of a disease, then the system will provide a diagnosis. This diagnosis can be used as an initial reference for sufferers and can be used as a reference for young doctors who are taking medical education with an ENT specialist. In this initial research, testing was carried out to calculate the computational time needed by the system to diagnose ENT disease. Based on this research, we found that the average computing time needed by the system to diagnose is 00:09:54 or Nine minutes, fifty-four seconds.
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References
[1] S. V., “Karakteristik penderita tonsilitis kronis yang diindikasikan tonsilektomi Di RSUD Raden Mattaher Jambi,†Skripsi, 2013
[2] N. K. Pebriyanti and A. W. Andika, “Sistem Pakar Penentuan Tanaman Obat pada Penyakit THT berbasis Web,†SINTECH (Science Inf. Technol. J., vol. 1, no. 1, pp. 34–40, 2018
[3] Y. R. Nasution and Khairuna, “Sistem pakar deteksi awal penyakit tuberkulosis dengan metode bayes,†Klorofil, vol. 1, no. 1, pp. 17–23, 2017
[4] R. Ramadhan, “Pemodelan Sistem Pakar Diagnosa Penyakit Tanaman Cabai Merah Dengan Metode Fuzzy-Ahp.,†Repos. J. Mhs. PTIIK UB., vol. 6, no. 7, 2015
[5] Hamdani, “Sistem Pakar Untuk Diagnosa Penyakit Pada Manusia,†J. Inform. Mulawarman, vol. 5, no. 2, pp. 13-21., 2010
[6] M. A. Fahmy, I. P. Ningrum, and J. Y. Sari, “Sistem pakar diagnosis penyakit hewan sapi dengan metode forward chaining,†no. December, 2018
[7] Y. Hendriana, “PROGRAM BANTU IDENTIFIKASI PENYAKIT THT,†in Simposium Nasional Teknologi Terapan (SNTT), 2013, pp. 58–63
[8] S. Wahyu, P., Muhammad A.W. dan Bagus, “Sistem pakar berbasis web untuk diagnosa awal penyakit THT,†in Prosiding SNATI Yogyakarta, 2008
[9] H. T. Sihotang, E. Panggabean, and H. Zebua, “Sistem Pakar Mendiagnosa Penyakit Herpes Zoster Dengan Menggunakan Metode Teorema Bayes,†J. Inform. Pelita Nusant., vol. 3, no. 1, pp. 33–40, 2018
[10] C. Vikasari., “Modernisasi Teknologi Realtime pada Pelelangan Ikan dalam Menumbuhkan Perekonomian Berbasis Kemaritiman,†JUITA J. Inform., 2018.
[2] N. K. Pebriyanti and A. W. Andika, “Sistem Pakar Penentuan Tanaman Obat pada Penyakit THT berbasis Web,†SINTECH (Science Inf. Technol. J., vol. 1, no. 1, pp. 34–40, 2018
[3] Y. R. Nasution and Khairuna, “Sistem pakar deteksi awal penyakit tuberkulosis dengan metode bayes,†Klorofil, vol. 1, no. 1, pp. 17–23, 2017
[4] R. Ramadhan, “Pemodelan Sistem Pakar Diagnosa Penyakit Tanaman Cabai Merah Dengan Metode Fuzzy-Ahp.,†Repos. J. Mhs. PTIIK UB., vol. 6, no. 7, 2015
[5] Hamdani, “Sistem Pakar Untuk Diagnosa Penyakit Pada Manusia,†J. Inform. Mulawarman, vol. 5, no. 2, pp. 13-21., 2010
[6] M. A. Fahmy, I. P. Ningrum, and J. Y. Sari, “Sistem pakar diagnosis penyakit hewan sapi dengan metode forward chaining,†no. December, 2018
[7] Y. Hendriana, “PROGRAM BANTU IDENTIFIKASI PENYAKIT THT,†in Simposium Nasional Teknologi Terapan (SNTT), 2013, pp. 58–63
[8] S. Wahyu, P., Muhammad A.W. dan Bagus, “Sistem pakar berbasis web untuk diagnosa awal penyakit THT,†in Prosiding SNATI Yogyakarta, 2008
[9] H. T. Sihotang, E. Panggabean, and H. Zebua, “Sistem Pakar Mendiagnosa Penyakit Herpes Zoster Dengan Menggunakan Metode Teorema Bayes,†J. Inform. Pelita Nusant., vol. 3, no. 1, pp. 33–40, 2018
[10] C. Vikasari., “Modernisasi Teknologi Realtime pada Pelelangan Ikan dalam Menumbuhkan Perekonomian Berbasis Kemaritiman,†JUITA J. Inform., 2018.
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Published
2019-05-29
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Articles
How to Cite
[1]
I. Imamah and A. Siddiqi, “Penerapan Teorema Bayes untuk Mendiagnosa Penyakit Telinga Hidung Tenggorokan (THT)”, MATRIK, vol. 18, no. 2, pp. 268–275, May 2019, doi: 10.30812/matrik.v18i2.398.
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