Expert System for Diagnosing Early Symptoms of Stroke Using the Fuzzy Mamdani Method Sistem Pakar Diagnosa Gejala Dini Penyakit Stroke Menggunakan Metode Fuzzy Mamdani

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Published: Jun 30, 2021
DOI: https://doi.org/10.21070/pels.v1i2.969
Keywords:
Stroke, Fuzzy Mamdani, Expert System

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Sylfanie Sekar Mayang
Universitas Muhammadiyah Sidoarjo, Indonesia
Ade Eviyanti
Universitas Muhammadiyah Sidoarjo, Indonesia

Abstract

One of the dangerous diseases is stroke because it can disrupt the nervous system system in humans so that sufferers of this disease often experience paralysis in their body parts. Therefore, an application is needed to assist medical personnel when doctors are not available or are not on duty. Expert system applications are needed in early diagnosing the characteristics of the disease suffered by a patient. Expert systems are computer-based systems that use knowledge, facts and reasoning techniques to solve problems. The purpose of this study is to make it easier for researchers to identify problems with stroke based on the symptoms experienced by the patient or a person. The research method used is the fuzzy mamdani method. Data collection techniques are quantitative data techniques. The results that have been achieved from this study are that it can prevent and reduce the risk of stroke that can occur as early as possible in sufferers or the community and reduce the death rate in stroke patients.

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How to Cite
[1]
Sylfanie Sekar Mayang and Ade Eviyanti, “Expert System for Diagnosing Early Symptoms of Stroke Using the Fuzzy Mamdani Method”, PELS, vol. 1, no. 2, Jun. 2021.
Issue
Vol 1 No 2 (2021): Proceedings of the 2nd Seminar Nasional Sains 2021
Section
Computer Science
Crossref
Scopus
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Europe PMC

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