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Implementing knowledge discovery in enhancing university student services portfolio management in higher education institutions
Author(s) -
Paulino H. Gatpandan,
Shaneth C. Ambat
Publication year - 2017
Publication title -
journal of advanced research in social sciences and humanities
Language(s) - English
Resource type - Journals
eISSN - 2597-7040
pISSN - 2579-8480
DOI - 10.26500/jarssh-02-2017-0306
Subject(s) - chaid , knowledge management , portfolio , higher education , novelty , demographics , computer science , data science , process management , psychology , engineering , business , artificial intelligence , decision tree , sociology , finance , political science , law , social psychology , demography
The academic and holistic success of a student depends on their interests and support system by means of academic enablers to emphasize the motivational and cognitive development. The academic and student affairs were structured to align student activities with the priorities of the academic division, and it allows them to develop closer relationships with faculty in order to more effectively help students learn in a holistic and coordinated manner. This paper presents an implementation of Knowledge Discovery in Enhancing University Student Services Portfolio Management of the Student Welfare and Formation Office (SWAFO) of De La Salle University-Dasmarinas, Philippines where demographics and student offenses were analyzed using the Classification Techniques and Data Envelopment Analysis. The Data Envelopment Analysis was utilized to determine the efficient Decision-Making Unit (DMU) attributed as colleges. CHAID algorithm will be used to determine the relationship between the demographic profile of the students and the category of offenses. Also, Cross Tabulation is a tool used to analyze categorical data and present the multivariate frequency distribution of the variables. A remediation plan will be developed as an implementation of CHAID algorithm in a software application that is intended to be a predictive analytical software application which forecasts student offenses. The software application will be evaluated by the personnel of SWAFO and five (5) IT Experts. The results will be interpreted using weighted mean and standard deviation. The researchers recommend considering other knowledge discovery techniques in efficiency measurement or empirical analysis related to university service portfolio management.

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