Development of an Expert System for Early Detection of Heart Disease Using The Bayes Theorem Method
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Published:
Nov 30, 2020
Keywords:
Bayes Theorem, Cardiovascular Disease, Expert System, Web
Section
Computer Science
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Abstract
Coronary heart disease (CHD) is the leading cause of death and disability in developed and developing countries. In 2014 it was also reported that coronary heart disease is one of the causes of death for both men and women, starting in the 25-29 age group and increasing with age. The highest prevalence of coronary heart disease as a cause of death in the 60-64 year age group and in the 70-74 year age group. The development of science and technology has made information technology usable in various fields including health. So it is hoped that by making an application that can make it easier for users to detect heart disease early and independently. The purpose of this study is to build an application by implementing an expert system using the website-based Bayes Theorem method as a tool for diagnosing heart disease. This application was built using the web programming language & MySQL database. Expert system application to help detect heart disease early.
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How to Cite
Riandari, F. and Ritha Zahara Tarigan (2020) “Development of an Expert System for Early Detection of Heart Disease Using The Bayes Theorem Method ”, Jurnal Mantik, 4(3), pp. 2271-2276. doi: 10.35335/mantik.Vol4.2020.1119.pp2271-2276.
References
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[21] W.E. Gustri, P. Widodo, “Prototype Sistem Pakar untuk Mendeteksi Tingkat Resiko Penyakit Jantung Koroner dengan Metode DempsterShafer (Studi Kasus: RS. PKU Muhammadiyah Yogyakarta)”, IJCCS, Vol.7, No.2, pp. 133-144 , July 2013.
[22] World Health Organisation. World Health Report. 2013. [Cited 2016 June 23]. Available from : http://www.who.int/whr/ 2013/ report/en/.
[23] Y. Simare-mare and F. Riandari, “Expert System For Personal Computer Mendiagnosakerusakan Method Using Certainty Factor,” J. Comput. Networks, Archit. High Perform. Comput., vol. 2, no. 2, pp. 195–202, 2020.
[2] Danaei, G., Ding, E. L., Mozaffarian, D., Taylor, B., Rehm, J., Murray, C. J. L., & Ezzati, M. (2009). The Preventable Causes of Death in the United States: Comparative Risk Assessment of
[3] Desak Putu Siska Dewi , Sistem Pakar Diagnosa Penyakit Jantung dan Paru dengan Fuzzy Logic dan Certainty Factor”, MERPATI VOL. 2, NO. 3, pp.361-370, Desember 2014.
[4] Dietary, Lifestyle, and Metabolic Risk Factors. PLoS Medicine, 6(4), e1000058. doi:10.1371/journal.pmed.1000058.
[5] Horton, R. (2015). Offline: Chronic diseases—the social justice issue of our time. The Lancet, 386(10011), 2378. doi:10.1016/s0140-6736(15)01178-2.
[6] H. T. Sihotang and F. Riandari, “Application expert system diagnoses chickenpox disease in children using case based reasoning method,” J. Crit. Rev., vol. 7, no. 7, pp. 574–579, 2020.
[7] H. T. Sihotang, F. Riandari, and S. Indri Gita Margareth, “Expert system to different mixed disease in baby using CBR (case base reasoning) method,” J. Crit. Rev., vol. 7, no. 5, pp. 48–51, 2020.
[8] H. T. Sihotang, F. Riandari, R. M. Simanjorang, A. Simangunsong, and P. S. Hasugian, “Expert System for Diagnosis Chicken Disease using Bayes Theorem,” J. Phys. Conf. Ser., vol. 1230, no. 1, 2019.
[9] Kementerian Kesehatan. Laporan Riset Kesehatan Dasar (Riskesdas) 2013 BidangBiomedis. Jakarta: Badan Litbangkes,Kemenkes RI; 2014.
[10] Kosen S, Tarigan IU, Rosita T, Indriasih E, Usman Y, dkk. Indonesia: Sample registration System 2014. Jakarta : The National Institute of Health Research and Development; 2015.
[11] L. Situmorang and F. Riandari, “Expert System Mediagnosa Hama On Phon Oil With Certainty Factor Method,” J. Comput. Networks, Archit. High Perform. Comput., vol. 2, no. 2, pp. 268–274, 2020.
[12] Leischik R, Dworrak B, Strauss M, et al. Plasticity of Health. German Journal of Medicine 2016;1:1-17
[13] Merlina N, (2012). Perancangan Sistem Pakar, Penerbit Ghalia Indonesia
[14] Oemiati R, Rustika. Faktor risiko penyakit jantung koroner (PJK) pada perempuan.Buletin Penelitian Sistem Kesehatan. 2015;18(1): 47–55.
[15] P. Jadiaman, P. Viktor H, P. Dwimaryuga, “Sistem Pakar Diagnosa Penyakit Jantung Menggunakan Metode Certainty Factor Berbasis Web”, Seminar Nasional Informatika 2012 (semnasIF 2012), pp 54-61, Juni 2012
[16] Roger, V. L. (2007). Epidemiology of Myocardial Infarction. Medical Clinics of North America, 91(4), 537–552. doi:10.1016/j.mcna.2007.03.007
[17] R.Joko S Dwi,D. Damdan, S. Lioe, “Perancangan Sistem Pakar Diagnosa Penyakit Jantung dengan Metode Forward Chaining Berbasis Android”, Jurnal Sisfotek Global, Vol. 7 No. 2, pp 102-107,Sep. 2017
[18] Sutojo, (2011). Kecerdasan Buatan. Bandung, 1st Published
[19] T. Derist, F. Erick, S. Pandapotan, Dkk, “Sistem Pakar Mendiagnosis Penyakit Jantung dengan Metode Fuzzy Set”, Seminar Nasional Aplikasi Teknologi Informasi (SNATI), Juni 2014.
[20] W. Eka, H. Sri, “Case-Based Reasoning untuk Diagnosis Penyakit Jantung”, IJCCS, Vol.11, No.1, pp. 1-10, January 2017
[21] W.E. Gustri, P. Widodo, “Prototype Sistem Pakar untuk Mendeteksi Tingkat Resiko Penyakit Jantung Koroner dengan Metode DempsterShafer (Studi Kasus: RS. PKU Muhammadiyah Yogyakarta)”, IJCCS, Vol.7, No.2, pp. 133-144 , July 2013.
[22] World Health Organisation. World Health Report. 2013. [Cited 2016 June 23]. Available from : http://www.who.int/whr/ 2013/ report/en/.
[23] Y. Simare-mare and F. Riandari, “Expert System For Personal Computer Mendiagnosakerusakan Method Using Certainty Factor,” J. Comput. Networks, Archit. High Perform. Comput., vol. 2, no. 2, pp. 195–202, 2020.
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