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Diagnose Expert System Dental Disease In Humans Method Using Dempster Shafer

Authors

  • Etiani Bu'ulolo STMIK Pelita Nusantara
  • Fricles Ariwisanto Sianturi Lecturer Teknik Informatika, STMIK Pelita Nusantara, Medan

DOI:

10.47709/cnapc.v2i2.426

Keywords:

Dental, Dempster Shafer, Expert System

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Abstract

Dental disease is one of the many health problems Complained of by the people of Indonesia. Dental health is a reflection of human health. Lack of knowledge and limited sources of information on oral health have the caused public awareness to maintain oral and dental health is still low .. The development of one of the fields of information technology namely artificial intelligence has been Widely applied in various fields of life can be used as a solution to Overcome this problem. In this study, the dental and oral disease expert system uses the Dempster Shafer method to control inferences that Contain thought patterns and reasoning mechanisms used by experts in solving problems.

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References

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Elyza, WG, and Prijodiprojo, W., 2013, Prototype Expert System for Detecting Coronary Heart Disease Risk Level Method with Dempster-Shafer, Department of Information Engineering, FTI UII, Yogyakarta.

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Joseph. A Odumeru and Carlos G. León-Velarde. 2012. "Salmonella Detection Methods for Food and Food Ingredients". University of Guelph, Guelph, Ontario, Canada.

Kharismadhan Zakaria "Dental Disease Diagnosis Expert System And Method Using Dempster Shafer Mouth" Proceedings of the Seminar on Information Applicative Polinema 2015 (SIAP ~ 2015).

Micah Dayan Sinaga, Nita Sari Br. Sembiring "Dempster Shafer Implementation Method To Diagnose Disease From the result of Salmonella bacteria" Smart Cogito Journal / VOL. 2 / NO. 2 / DECEMBER 2016.

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ARTICLE Published HISTORY

Submitted Date: 2019-11-28
Accepted Date: 2019-11-28
Published Date: 2020-06-01

How to Cite

Bu’ulolo, E., & Sianturi, F. A. (2020). Diagnose Expert System Dental Disease In Humans Method Using Dempster Shafer. Journal of Computer Networks, Architecture and High Performance Computing, 2(2), 227-230. https://doi.org/10.47709/cnapc.v2i2.426