The Forecast Career Path of the New Graduates of Computer Sciences Program at Suan Sunandha Rajabhat University by Decision Tree Technique
Thitiporn Sittichailapa,
Watchara Pantasak and
Rattanathip Rattanachai
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Thitiporn Sittichailapa: Suan Sunandha Rajabhat University, Bangkok, Thailand
Watchara Pantasak: Suan Sunandha Rajabhat University, Bangkok, Thailand
Rattanathip Rattanachai: Suan Sunandha Rajabhat University, Bangkok, Thailand
International Journal of Technology and Engineering Studies, 2016, vol. 2, issue 4, 110-116
Abstract:
The objective of this research was to develop the career path model of the graduates of Computer Sciences Program of Science and Technology Faculty at Suan Sunandha Rajabhat University. This model is gathering result of academic curriculum and the survey employed applications. The satisfaction criteria of grade were 2.75, 2.75 up and less than 2.75. By decision tree technique, we developed the structure of subject to affect the career paths of graduates who followed the computer sciences program in 2006. After that, the model projected a career path to the new graduates and checked information of theirs. We found an important problem in data of a new graduate; it has many records and no information about first occupation, this is important for this research because it develops confidence. However, we built model from completely new data. Finally, we checked the reliability of the model that was discovered to be 70 percent correct and should have developments in the prototype. It aims that our students have to be ready to goal on the future and stick to strong curriculum for the new technology. However, it should not be ignored that 30 percent has missing value (forexample: age, salary, expense, the progress in corporate and etc.). In the future, the researcher is finding out the other factors’ effect.
Keywords: Career Path; Decision Tree Technique; Data Mining; Computer Science (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:apa:ijtess:2016:p:110-116
DOI: 10.20469/ijtes.2.40003-4
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