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All Journal PELS (Procedia of Engineering and Life Science)
Muhammad Arif Fa’i
Universitas Muhammadiyah Sidoarjo
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Expert System Diagnosing Stroke Disease Using Android-Based Bayes Theorem Method Muhammad Arif Fa’i; Ade Eviyanti
Procedia of Engineering and Life Science Vol 1 No 2 (2021): Proceedings of the 2nd Seminar Nasional Sains 2021
Publisher : Universitas Muhammadiyah Sidoarjo

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Abstract

. In the current era there are still many people who are not routinely even reluctant to do sports and unwittingly such a lifestyle is stimulating bias for stroke. Moreover, coupled with the character of citizens who are reluctant to spend money and also take the time to go to the doctor to consult about his health. And also there are still many residents who underestimate some of the symptoms that can stimulate stroke. Stroke if left untreated and not immediately taken to an expert doctor can also have an impact on cell death in the brain so that it can cause paralysis of part of the limbs, if it has become severe can also result in death. Therefore, the authors of this study aimed to create an android-based application that can diagnose the potential of a person with stroke, which later from the diagnosis using this application is expected to help in taking further medical action if it has the potential of stroke. The test results using the blackbox method got the result that all the features and functions of the system run according to what has been designed. The author also conducted tests using the UAT method to get the results that the application has an attractive look, the diagnosis menu is very useful for users, the data of disease symptom information is informative, and also easy to use.
Co-Authors Ade Eviyanti