Diagnosis of Kidney Disease Using Fuzzy Logic Method

  • Anggun Andini STMIK Kaputama, Binjai, Sumatera Utara
  • Akim Manaor Hara Pardede STMIK Kaputama, Binjai, Sumatera Utara
  • Marto Sihombing STMIK Kaputama, Binjai, Sumatera Utara
DOI: https://doi.org/10.52362/ijiems.v3i1.1234

Abstract

Kidney disease is a condition in which the kidneys cannot function properly. Kidney disease is one of the diseases that can cause death and disability. Ignorance and lack of information about kidney disease causes the death rate of people with kidney disease to increase every year. Limited special kidney facilities in Indonesia are one of the factors slowing treatment. To distinguish what type of kidney disease sufferers of symptoms need to bring in an expert or specialist in internal medicine for a consultation. However, there are some problems with an expert such as an expert who is not always in place, the cost of consulting an expert is quite expensive, and still limited. Unhealthy lifestyle is also a factor in the increase in kidney disease sufferers. With these problems it can be concluded that it is necessary to create a system that can diagnose diseases without having to consult an expert with an expert system. An expert system is a system that can store expert information in a computer. In the Fuzzy Logic method, the existing data will be inferred by creating a rule in the form of IF_THEN and using the AND operation, then the minimum value (MIN) of several existing variables will be selected. From the results of trials conducted in this study it was found that based on the symptoms that occur the patient suffers from Acute Renal Failure.

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Published
2024-01-23
How to Cite
ANDINI, Anggun; HARA PARDEDE, Akim Manaor; SIHOMBING, Marto. Diagnosis of Kidney Disease Using Fuzzy Logic Method. International Journal of Informatics, Economics, Management and Science, [S.l.], v. 3, n. 1, p. 108-115, jan. 2024. ISSN 2809-8471. Available at: <https://journal.stmikjayakarta.ac.id/index.php/ijiems/article/view/1234>. Date accessed: 06 july 2025. doi: https://doi.org/10.52362/ijiems.v3i1.1234.
Citation Formats
Issue
Vol 3 No 1 (2024): IJIEMS (January 2024)
Section
Articles
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