Expert System Diagnosing Heart Disease using Bayes' Theorem Method
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Abstract
Heart disease is one of the leading causes of death in Indonesia. The high number of deaths from heart disease is caused by the lack of cardiologists, the lack of public awareness of conducting regular heart health checks and the poor lifestyle of patients. So we need an application that can make it easier for users to detect heart disease early and independently. In this study, the aim is to build an application using the website-based Bayes Theorem method as a tool for diagnosing coronary heart disease. In this application, patients do not have to wait long for treatment by a doctor, but it can be an alternative to anticipate treatment quickly and precisely. How to use this application, the admin inputs questions in the form of symptoms that will be answered by the user, then the system will process all user answers using the Bayes theorem method and the system will issue output in the form of diagnostic results in the form of heart disease and various solutions. This application uses a Web programming language and Php & Mysql as a database. The system that has been built can assist patients in knowing the type of heart disease that is being suffered by the patient and according to the analysis of heart disease experts.
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D. Setiawan, “Dampak perkembangan teknologi informasi dan komunikasi terhadap budaya,” J. SIMBOLIKA Res. Learn. Commun. Study, vol. 4, no. 1, pp. 62–72, 2018.
N. NADHIROH, “PENGARUH MODEL PEMBELAJARAN INQUIRY TERHADAP HASIL BELAJAR BIOLOGI MATERI SISTEM PEREDARAN DARAH SISWA KELAS VIII DI MTS. MA’ARIF BAKUNG UDANAWU BLITAR TAHUN AJARAN 2018/2019,” 2019.
T. A. Wihastuti, S. Andarini, and T. Heriansyah, Patofisiologi Dasar Keperawatan Penyakit Jantung Koroner: Inflamasi Vaskular. Universitas Brawijaya Press, 2016.
M. Iskandar, Health Triad. Elex Media Komputindo, 2013.
M. Suwardi, Rahasia Dibalik Penciptaan Organ Tubuh Manusia. 2015.
R. Bahana, I. Indrajani, R. Kosala, and Y. Heryadi, “Aplikasi Informasi Kesehatan Dan Diagnosa Penyakit Jantung Berbasis Android,” in Seminar Nasional Teknologi Informasi Komunikasi dan Industri, 2018, pp. 10–16.
A. S. Sitio, “Sistem Pakar Untuk Mendiagnosa Penyakit Jantung Menggunakan Metode Dempster Shafer,” J. Inform. Pelita Nusant., vol. 3, no. 1, 2018.
R. E. Kowalski, Terapi hipertensi. PT Mizan Publika, 2010.
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, 2018.
Y. I. Za’iim, “Sistem Pakar untuk Diagnosa Penyakit Jantung Koroner Menggunakan Metode Perceptron,” Skripsi, Fak. Ilmu Komput. Univ. Dian Nuswantoro, 2013.
L. Hoki, “Perancangan Sistem Pakar Diagnosa Ispa Dengan Metode Forward Chaining,” J. TIMES, vol. 8, no. 1, pp. 63–72, 2019.
S. Winiarti, “Pemanfaatan Teorema Bayes dalam Penentuan Penyakit THT,” J. Inform., vol. 2, no. 2, pp. 189–198, 2008.
V. Pawaka, “Sistem Pakar Deteksi Diabetes Mellitus Menggunakan Metode Bayesian Berbasis Web,” JUSTIN (Jurnal Sist. dan Teknol. Informasi), vol. 3, no. 2, pp. 39–43.
A. J. F. Purba, “Perbandingan Metode Bayes Dan Certenty Factor Pada Sistem Pakar Mendiagnosa Penyakit Varisela Pada Anak-Anak,” Heal. Contemp. Technol. J., vol. 1, no. 1, pp. 20–25, 2020.
H. Pramudia and A. Nugroho, “Sistem Informasi Kerusakan Laptop Menggunakan Metode Naive Bayes,” Teknol. Elektro, Univ. Mercu Buana, vol. 5, no. 2, pp. 135–155, 2017.
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