E3S Web Conf.
Volume 31, 2018The 2nd International Conference on Energy, Environmental and Information System (ICENIS 2017)
|Number of page(s)||6|
|Section||10. Industrial Information Systems|
|Published online||21 February 2018|
Expert System Application of Forward Chaining and Certainty Factors Method for The Decision of Contraception Tools
Magister Program of Information System, School of Postgraduate Studies, Diponegoro University, Semarang – Indonesia 50242
2 Department of Physics, Faculty of Science and Mathematics, Diponegoro University, Semarang – Indonesia 50275
3 Department of Computer Science, Faculty of Science and Mathematics, Diponegoro University, Semarang – Indonesia 50275
* Corresponding author: firstname.lastname@example.org or email@example.com
The choice of contraceptive tools is not an easy thing because the risks or effects will give impact on the body that never using it previously. in the other side, there is no contraception always suit for everybody because the circumstances of each body is different, so the extensive knowledge must be needed to know the advantages and disadvantages of each contraceptive tools then adjusted to the user's body.The expert system for contraceptive tools uses Forward Chaining search method combined with Certainty Factors Method. These method value the patient’s indication. The Expert system gives the output data which define the kind of tool uses of the patient. the results obtained will be able to help people to find indications that lead to appropriate contraceptive tools and advice or suggestions about these tools. The success rate of the contraceptive tools decision experienced by experienced by the user by using forward chaining combined with the CF computation method is also influenced by the number of indication criteria selected by the user. Based on testing that has been done, expert system contraception tools has accuracy level equal to 75%.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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