Expert System Using the Bayes Theorem For the Diagnosis of Diseases Caused by Fungal Infection
-
Febri Rahmadsyah(1*)
Universitas Mercu Buana Yogyakarta
-
Mutaqin Akbar(2)
Universitas Mercu Buana
(*) Corresponding Author
Abstract
Early diagnosis of skin diseases which is caused by fungal infections is necessary to reduce the risk of disease. In this article, an expert system that implements the Bayes’ theorem is proposed as a solution for early diagnosis of skin diseases, especially those caused by fungal infections. Knowledge acquisition from experts, in this case a specialist in skin and venereal diseases, is carried out to obtain a knowledge base. A total of 31 data from medical records were used in this study. Types of skin diseases that can be detected are tinea korporis, tinea unguium, pitiriasis versicolor, and mild mucocutaneous candidosis. Bayes’ theorem is implemented in the inference engine, resulting in a probability of the type of skin disease suffered based on symptom inputs from the user. Results, which are produced by the system, are then validated by expert. Based on the results of the validation, 27 results matched the experts’ validation while 4 results did not, so that the level of system accuracy based on the validation results was 87.1%.
Downloads
References
M. Harahap, Ilmu Penyakit Kulit, 1st ed. Jakarta: Hipokrates, 2000.
S. Kusumadewi, Artificial Intelligence (Teknik dan Aplikasinya), 1st ed. Yogyakarta: Graha Ilmu, 2003.
L. Marlinda, “SISTEM PAKAR DIAGNOSA PENYAKIT KULIT PADA MANUSIA MENGGUNAKAN APOTEK HIDUP MENGGUNAKAN SIMPLE ADDITIVE WEIGHTING,” in Seminar Nasional Sains dan Teknologi 2015, Nov. 2015, pp. 1–5.
M. A. Puspa, “SISTEM PAKAR DIAGNOSA PENYAKIT HIPERTENSI MENGGUNAKAN METODE NAIVE BAYES PADA RSUD ALOE SABOE KOTA GORONTALO,” Ilk. J. Ilm., vol. 10, no. 2, pp. 166–174, Aug. 2018, doi: 10.33096/ilkom.v10i2.304.166-174.
M. H. Qamaruzzaman and S. Sam’ani, “Sistem Pakar Untuk Mendiagnosa Penyakit Mata Pada Manusia Menggunakan Teorema Bayes,” Indones. J. Netw. Secur., vol. 5, no. 4, pp. 7–11, Oktober 2016.
I. Russari, “SISTEM PAKAR DIAGNOSA PENYAKIT BATU GINJAL MENGGUNAKAN TEOREMA BAYES,” J. Ris. Komput., vol. 3, no. 1, pp. 18–22, Feb. 2016.
D. S. I. Fiano and A. S. Purnomo, “Sistem Pakar Untuk Mendeteksi Tingkat Resiko Penyakit Jantung Dengan Fuzzy Inferensi (Mamdani),” Inform. J., vol. 2, no. 2, pp. 64–78, 2017.
Y. O. R. Manik and G. Ginting, “SISTEM PAKAR DIAGNOSA PENYAKIT HEWAN TERNAK BABI DENGAN MENGGUNAKAN METODE FUZZY MAMDANI BERBASIS WEB,” Maj. Ilm. INTI, vol. 5, no. 3, pp. 251–256, Jun. 2018.
N. T. Pradipta, F. Fauziah, and U. Darusalam, “PERANCANGAN SISTEM INFORMASI ANALISIS MEDIK MENGGUNAKAN LOGIKA FUZZY SUGENO BERBASIS DATA REKAM MEDIK PADA PENYAKIT HIPERTENSI,” J. Ilm. Inform., vol. 2, no. 1, pp. 59–67, Jun. 2017, doi: 10.35316/jimi.v2i1.445.
N. I. Kurniati, R. R. E. Akbar, and P. Wijaksono, “Penerapan Metode Fuzzy Tsukamoto pada Sistem Pakar untuk Mendiagnosa Autisme Pada Anak,” Innov. Res. Inform., vol. 1, no. 1, pp. 21–27, Mar. 2019.
S. I. Ali, R. R. Isnanto, and A. B. Praseti, “SISTEM PAKAR DIAGNOSIS PENYAKIT DIFTERI MENGGUNAKAN LOGIKA FUZZY,” J. Sains Dan Teknol., vol. 16, no. 1, pp. 89–104, Jun. 2018.
T. Puspitasari, B. Susilo, and F. F. Coastera, “IMPLEMENTASI METODE DEMPSTER-SHAFER DALAM SISTEM PAKAR DIAGNOSA ANAK TUNAGRAHITA BERBASIS WEB,” J. Rekursif, vol. 4, no. 1, pp. 1–13, Mar. 2016.
M. D. Sinaga and N. S. Br. Sembiring, “Penerapan Metode Dempster Shafer Untuk Mendiagnosa Penyakit Dari Akibat Bakteri Salmonella,” Cogito Smart J., vol. 2, no. 2, pp. 94–107, Desember 2016.
D. T. Yuwono, A. Fadlil, and S. Sunardi, “Implementasi Metode Dempster Shafer Pada Sistem Pakar Diagnosa Gangguan Kepribadian,” J. Sist. Inf. BISNIS, vol. 9, no. 1, p. 25, May 2019, doi: 10.21456/vol9iss1pp25-31.
Copyright (c) 2021 J-Icon : Jurnal Komputer dan Informatika
This work is licensed under a Creative Commons Attribution 4.0 International License.
The author submitting the manuscript must understand and agree that if accepted for publication, authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC-BY) 4.0 License that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal.
