Sistem Pakar dalam Mengidentifikasi Gejala Stroke Menggunakan Metode Naive Bayes

Authors

  • Fajri Karim Universitas Putra Indonesia YPTK Padang
  • Gunadi Widi Nurcahyo Universitas Putra Indonesia YPTK Padang
  • S Sumijan Universitas Putra Indonesia YPTK Padang

DOI:

https://doi.org/10.37034/jsisfotek.v3i4.69

Keywords:

Expert System, Identification, Symptom, Stroke, Naive Bayes

Abstract

Stroke is a disease caused by brain damage caused by disruption of the blood supply to the brain. At this time in general, people are still not very familiar with how this stroke disease or do not realize the symptoms that may have appeared from the start. People also tend to be hesitant to visit the hospital to check their symptoms and feel they are delaying further examinations. This is certainly a scourge that continues to make the number of strokes increase. In assisting the community in identifying stroke disease, an expert system is needed that is able to identify the type of stroke based on the symptoms felt. The data used in this study were obtained from Brain Hospital. Dr. Drs. M. Hatta Bukittinggi which was later developed into a website-based system using the PHP Framework Laravel programming language and MySQL as the database. The system is built based on the Naive Bayes method which is one of the Expert System methods that has a high accuracy value. The use of this system is expected to be able to provide knowledge to the public about the symptoms that might lead to what type of stroke the user might suffer, so that the user can use the results of the system as a reference to visit the hospital and immediately get more targeted help. This system can perform calculations that match the results of the doctor's diagnosis with an accuracy value of 100% in identifying the type of stroke from 10 data samples used.

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Published

2021-09-03

How to Cite

Karim, F. ., Nurcahyo, G. W. ., & Sumijan, S. (2021). Sistem Pakar dalam Mengidentifikasi Gejala Stroke Menggunakan Metode Naive Bayes. Jurnal Sistim Informasi Dan Teknologi, 3(4), 221–226. https://doi.org/10.37034/jsisfotek.v3i4.69

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