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Ucok Darussalam
Universitas Nasional
Computer Science & IT

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Web-Based Expert System for Diagnosing Human Eye Disease Using the Naïve Bayes Method Ahmad; Ucok Darussalam; Benrahman B
Jurnal Teknik Informatika C.I.T Medicom Vol 12 No 1 (2020): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1030.624 KB) | DOI: 10.35335/cit.Vol12.2020.18.pp16-25

Abstract

The eye is one of the organs of the body that is very important for humans, so it must be kept in good health, but as humans age and the unhealthy lifestyle of many people in Indonesia experience problems with their eyes. Based on the existing problems this study discusses the application of expert systems to diagnose eye diseases. The data used for the study consisted of 22 symptoms and 5 eye diseases. Expert system that was built using the Naïve Bayes method. There are two stages of work from this application. First, the system asks the patient to choose the symptoms they are experiencing. Secondly, the system will automatically display the diagnosis results of the eye disease suffered by the patient through the calculation of Naïve Bayes. This system has advantages compared to the existing system in the reference journal, namely in the design of the symptom page display, making it easier for users to answer according to the symptoms felt. The results of subsequent system diagnoses are compared with the results of diagnoses from actual experts. The system trial used data of 15 eye disease patients. From the experimental results, the percentage of diagnostic suitability of 86%.
Co-Authors Ahmad Ben Rahman