Diagnosis of Pulmonary Tuberculosis Using the Certainity Factor

EasyChair Preprint 5788

Abstract

The purpose of this research was to early diagnose pulmonary infectious tuberculosis,
commonly known as tuberculosis (TBC). This disease is caused by Mycobacterium tuberculosis
through active TB sufferers who cough and excrete small droplets of saliva. Then an expert system
is created that can assist in diagnosing and providing solutions to patients based on the symptoms of
TB disease experienced by patients so that patients can detect it early and do not have to consult
directly with a doctor. In this research, the method of Certainty Factor (CF) was used to calculate
the certainty value in order to make the final decision clearer. There are several steps used to
diagnose someone with TB disease: (1) Collecting disease and symptom data, (2) Creating rules
from existing symptoms based on expert references and literature, (3) Calculating the certainty value
with the CF method used. From the results of the system testing conducted on 20 people, the results
of these trials and compared with the doctor's opinion, the accuracy of this system is 85% accurate,
indicating that the results of the pulmonary tuberculosis diagnosis expert system can help doctors in
diagnosing types of TB disease. based on the symptoms experienced by the patient and can provide
first aid or early diagnosis by providing solutions to users.

Keyphrases: Tuberculosis, World Health Organization, active tuberculosis, expert system

@booklet{EasyChair:5788,
  author    = {Wanda Ilham and Dasril Aldo and Widya Army and Pertrus Sokibi and Ilwan Syafrinal and Irvandori Aplana and Yogi Eriawan},
  title     = {Diagnosis of Pulmonary Tuberculosis Using the Certainity Factor},
  howpublished = {EasyChair Preprint 5788},
  year      = {EasyChair, 2021}}