Zulyan Herlani
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IMPLEMENTASI CERTAINTY FACTOR UNTUK DIAGNOSA PENYAKIT PARU – PARU Zulyan Herlani; Bebas Widada; Wawan Laksito Yuli Saptomo
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 7, No 1 (2019): Jurnal TiKomSiN
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (14.249 KB) | DOI: 10.30646/tikomsin.v7i1.425

Abstract

The lungs are one of the most important organs in the human body. Many people today pay less attention to the health of these vital organs. This is evidenced by the many people who consume cigarettes which will have a negative impact on lung health. The lack of public attention to lung health and the high cost of examinations make this problem slow to deal with, by because it requires a system that can be used to diagnose lung disease that can be accessed by the public in general. The Certainty Factor method is a classification algorithm that uses the principles of the assessment of an expert to assess each variable or symptom in each disease in this case and has the accuracy is quite good in conducting data classification, so this method is considered appropriate for diagnosing lung disease based on the symptoms experienced. Data used in this study is expert assessment data on symptoms in each disease, this data is obtained from l interview with pulmonary specialist doctors at Moewardi Hospital Surakarta. The results obtained in this study are the accuracy of the certainty factor algorithm for diagnosing lung disease with diagnostic testing data of 10 data patients with an accuracy of 70%. While the results of functional system testing using the Black Box, it was found that all components of the system have been tested and in accordance with the expected output.Keywords: Diagnose, Certainty Factor, Lung Disease