Citation

Lee, Chin Poo and Ng, Zhong Bo and Low, Yong Ee and Lim, Kian Ming (2020) Expert System for University Program Recommendation. In: 2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), 26-27 Sept. 2020, Kota Kinabalu, Malaysia.

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Abstract

Deciding on the most suitable university program to pursue after completing secondary education is a major step for school-leavers as it sets the tone of the career path they will embark on in the future. Undeniably, deciding on the university program is a sophisticated problem that involves a broad range of factors, such as geographic location, overall cost, campus security, personality, etc. Most of these factors, for instance, geographic location and campus security only have temporary impact on the school-leavers while they are attending to university. Nevertheless, the personality factor appears to be the long-term and the most crucial determinant of the success in their professional life. When choosing the university program, school-leavers often make the mistake of following friends' footsteps or adhering to parents' decisions, only to realize years later that it is not what suits their personality or what they want. Considering these challenges, this work studies on the Holland's Personality Test to examine the personality of school-leavers. There are six personality types in Holland's Personality Test, represented as RIASEC code or Holland code. On top of that, this work also compiles a comprehensive list of university programs with their corresponding Holland code. An expert system is then engineered to encode the information into the knowledge base. Upon taking the Holland Personality Test, the expert system will update the facts list based on the answers given. Subsequently, the inference engine activates the production rules if the conditions are fulfilled. Ultimately, the personality type and recommended university program are presented to the school-leavers.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Expert system
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	23 Sep 2021 04:06
Last Modified:	23 Sep 2021 04:06
URII:	http://shdl.mmu.edu.my/id/eprint/8266

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