Expert System For Diagnosis of Hypertension Disease Using Naive Bayes Method

Authors

  • Edhy Poerwandono STIKOM Cipta Karya Informatics
  • Prakoso Angga Ilyasa STIKOM Cipta Karya Informatics

DOI:

https://doi.org/10.62951/modem.v3i2.386

Keywords:

Expert Systems, Hypertention, Naive Bayes

Abstract

Hypertension is a disease that occurs to arteries that causes the supply of oxygen and nutrition that the body needs to be blocked. Hypertension is often called a silent killer, because it is a kind of disease that is very harmful but comes without awareness to its victim. People with hypertension in average are up to 40 years old and it happened all of his after life . In common hypertension caused by heredity, unhealthy lifestyle, and triggered by the more salty consumption, alcohol and stress. An expert system could be the solution to solve the problem because this system works just like an expert and was created by the naïve Bayes method with the rules and basic system that are the same just like the hyperantion desease. Through this application, users can consult with this system just like usually people consult with the expert to diagnose the sign that happened to the user and find the solution of what happened to themselves.

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References

[1] D. Sustrani, Lanny, Preview_Hypertension, 2004th ed. Jakarta: PT. Gramedia Pustaka Utama.

[2] Setiawan Dalimartha et al., Book Care Your self - Hypertension, 2008th ed. Penebar Plus+, 2008.

[3] Riskesdas, “Health Research and Development Agency, Ministry of Health, Republic of Indonesia. 2013.,” 2013.

[4] Bustami, “Application of Naive Bayes Algorithm,” J. Inform., vol. 8, no. 1, pp. 884–898, 2014.

[5] Kusrini, Expert System Theory and Application, 2006th ed. Yogyakarta: Andi Publisher.

[6] A. Muchid, “Pharmaceutical care,” Pharm. Care for Rheumatic Arthritis Patients, pp. 53–80, 2006.

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Published

2025-02-15

How to Cite

Edhy Poerwandono, & Prakoso Angga Ilyasa. (2025). Expert System For Diagnosis of Hypertension Disease Using Naive Bayes Method. Modem : Jurnal Informatika Dan Sains Teknologi., 3(2), 30–41. https://doi.org/10.62951/modem.v3i2.386

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