Knowledge base development framework with fuzzy preference based on group decision maker

Helen Sastypratiwi

Abstract


The knowledge base is a critical component in building intelligent systems, especially those related to systems that require expertise. However, one of the problems experienced is when collecting expert knowledge from more than one person. This knowledge is different from each expert that makes opinions and perceptions result in different decision results, and not necessarily, the decision can be accepted by other experts, in this case, psychologists. As a result, decision-makers have difficulty making the right decisions. This study developed a framework and strategies to build a knowledge base from several experts -with fuzzy preferences using a qualitative approach. Developing a framework for determining symptoms and disorders in children was taking a sample. Determining symptoms and disorders in children sometimes requires more than one expert in decision-making. Experts in this case act as decision-makers in giving preference to the symptoms. The result gives 20 symptoms with five behavior disorders in children that often occur. The data of symptoms and disorders obtained formed as much as 19 knowledge in IF- THEN with different weights. In the future, expert system machines can use this knowledge base collection by adding inference methods.


Keywords


Experts;Fuzzy preference;Group decision models;Knowledge base

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References


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DOI: https://doi.org/10.17509/jcs.v5i1.70792

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