Improvement of Information Technology Career Path by using Apriori and Ontology on Mobile Application
Sumitra Nuanmeesri1, Lap Poomhiran2
1Sumitra Nuanmeesri*, Assistant Professor in Information Technology, Faculty of Science and Technology, Suan Sunandha Rajabhat University, Thailand.
2Lap Poomhiran, Ph.D. student in Information Technology, Faculty of Information Technology, King Mongkut’s University of Technology North Bangkok, Thailand.
Manuscript received on December 16, 2019. | Revised Manuscript received on December 22, 2019. | Manuscript published on January 10, 2020. | PP: 1736-1741 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8706019320/2020©BEIESP | DOI: 10.35940/ijitee.C8706.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In Thailand, the joblessness rate is continually expanding for new graduates. But information technology careers are nevertheless popular in business in this digital age. Finding a way to support students to know the career direction that is suitable for them and is ready before going out for a job is therefore very valuable. However, most students do not know which occupation is best for them and are concern about the need to educate themselves and build up information that is suitable for their current career. This paper presents the Thai mobile application for predicting a student’s career based on subject results and guidance of training courses for information technology career path using the Apriori algorithm and ontology technique with the longest matching approach in the process of Thai word segmentation. The developed mobile application was tested in black box by experts and evaluated the satisfaction by users. The result shows that the developed mobile application was the highest effective with the high consensus for the evaluation of user satisfaction.
Keywords: Apriori, Association Rules, Future Career, Mobile Application, Ontology, Recommendation.
Scope of the Article: Information Retrieval