Sistem Pakar Untuk Mendiagnosis Penyakit Stroke Hemoragik dan Iskemik Menggunakan Metode Dempster Shafer

  • Jansen Kanggeraldo Politeknik Caltex Riau
  • Rika Perdana Sari Politeknik Caltex Riau
  • Muhammad Ihsan Zul Politeknik Caltex Riau
Keywords: expert system, stroke, Dempster Shafer method

Abstract

Stroke is a disease that associated with bloodstreams to the brain. Usually, stroke is caused by the presence of broken blood vessels or obstructed by a blood clot. According to basic health research data by Health Research and Development Agency of Indonesia Ministry of Health (2013), stroke has become one of the deadliest diseases in Indonesia. One effort made to prevent stroke is to create a system that can diagnose stroke. Based on Indraswari's (2015) research, it was found out that stroke can be diagnosed by risk factor criterion. However, to get the data,  the patient must check to the hospital or laboratory first To overcome these problems, the authors create an expert system that can diagnose stroke without having to consult directly with the doctor. This expert system adopts the expertise of a neurologist. The result of this system diagnosis’ is the type of desease and the percentage of the probability value of stroke. After the black box testing, it was found that all system functionality has been met. Then, based on the white box testing results, the value of cyclomatic complexity after the optimization of the program code is 8, it shows the program code of Dempster Shafer method is simple program code without much risk. The level of expert system accuracy is 97% so that the system can be used as an alternative for patients to make a diagnosis of stroke

 

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References

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Published
2018-06-22
How to Cite
Kanggeraldo, J., Sari, R. P., & Zul, M. I. (2018). Sistem Pakar Untuk Mendiagnosis Penyakit Stroke Hemoragik dan Iskemik Menggunakan Metode Dempster Shafer. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 2(2), 498 - 505. https://doi.org/10.29207/resti.v2i2.268
Section
Information Technology Articles