Whisnu Ulinnuha Setiabudi, Whisnu Ulinnuha
Semarang State University

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Expert System Diagnosis Dental Disease Using Certainty Factor Method Setiabudi, Whisnu Ulinnuha; Sugiharti, Endang; Arini, Florentina Yuni
Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i1.8463

Abstract

Technological development is growing rapidly among with the increasing of human needs especially in mobile technology where the technology that often be used is android. The existence of this android facilitates the user in access of information. This android can be used for healthy needs, for example is detecting dental disease. One of the branches of computer science that can help society in detecting dental disease is expert system. In this research, making expert system to diagnosis dental disease by using certainty factor method. Dental disease diagnosis application can diagnose the patient based on griping of the patient about dental disease so it can be obtained diseases possibility of the patient itself. This application is an expert system application that operates on android platform. Furthermore, in the measurement accuracy of the system test performed by 20 patients, there were 19 cases of corresponding and 1 cases that do not fit. So, from system testing performed by 20 patients resulted in a 95% accuracy rate. 
Expert System Diagnosis Dental Disease Using Certainty Factor Method Setiabudi, Whisnu Ulinnuha; Sugiharti, Endang; Arini, Florentina Yuni
Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i1.8463

Abstract

Technological development is growing rapidly among with the increasing of human needs especially in mobile technology where the technology that often be used is android. The existence of this android facilitates the user in access of information. This android can be used for healthy needs, for example is detecting dental disease. One of the branches of computer science that can help society in detecting dental disease is expert system. In this research, making expert system to diagnosis dental disease by using certainty factor method. Dental disease diagnosis application can diagnose the patient based on griping of the patient about dental disease so it can be obtained diseases possibility of the patient itself. This application is an expert system application that operates on android platform. Furthermore, in the measurement accuracy of the system test performed by 20 patients, there were 19 cases of corresponding and 1 cases that do not fit. So, from system testing performed by 20 patients resulted in a 95% accuracy rate.
Expert System Diagnosis Dental Disease Using Certainty Factor Method Setiabudi, Whisnu Ulinnuha; Sugiharti, Endang; Arini, Florentina Yuni
Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i1.8463

Abstract

Technological development is growing rapidly among with the increasing of human needs especially in mobile technology where the technology that often be used is android. The existence of this android facilitates the user in access of information. This android can be used for healthy needs, for example is detecting dental disease. One of the branches of computer science that can help society in detecting dental disease is expert system. In this research, making expert system to diagnosis dental disease by using certainty factor method. Dental disease diagnosis application can diagnose the patient based on griping of the patient about dental disease so it can be obtained diseases possibility of the patient itself. This application is an expert system application that operates on android platform. Furthermore, in the measurement accuracy of the system test performed by 20 patients, there were 19 cases of corresponding and 1 cases that do not fit. So, from system testing performed by 20 patients resulted in a 95% accuracy rate.