Mining Disciplinary Records of Student Welface and Formation Office : An Exploratory Study to Enhance the  University Services Portfolio

Gatpandan, Paulino H.; Ambat, Shaneth C.

doi:10.5121/ijitca.2017.7202

Cited by 2 publications

(3 citation statements)

References 25 publications

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“…Data mining was used by [32] in developing state-of-the art data mining applications for Customer Relationship Management while [33] posited data mining as application of concepts and techniques in processing the gathered data. Accordingly, data mining refers to the method or process of examining enormous and large amount of data [1,34] with myriad opportunities to investigate and provide informed decision and better the organizational performance.…”

Section: B Data Mining and Predictive Analyticsmentioning

confidence: 99%

“…Researches of [1,34] implemented data mining on its exploratory study to enhance the crime prevention program in the Philippines, while [35] used data mining in measuring the performance and productivity of selected BPO companies in the Philippines. Both of these studies employed Data Envelopment Analysis and Clustering Techniques.…”

Section: B Data Mining and Predictive Analyticsmentioning

confidence: 99%

“…Also, [44] used information retrieval and filtering research, and Lu [45] who developed personalized e-learning material recommender system using the data mining and knowledge discovery techniques. Further, [1,34] used decision tree in identifying patterns and developed a recommender system to enhance the university services portfolio and portfolio management for student welfare and formation program.…”

Section: B Data Mining and Predictive Analyticsmentioning

confidence: 99%

See 2 more Smart Citations

Implementing Classification Techniques in Predicting Incidents in a Higher Education Institution in the Philippines

Dasig¹,

Taduyo²,

Gatpandan³

et al. 2020

IJRTE

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The holistic success of the student in the university heavily relies on the curricula and student development programs. In this milieu, the increasing demand for designing, implementing, monitoring and controlling of major and minor violations of the students' demands formative, reformative, rehabilitative, and restorative remediation programs. This paper presents the implementation of classification technique in predicting incidents, develop a predictive model, and implement the model in a recommender system. The researchers utilized a Descriptive Developmental research design. During the development, business rules, use cases and processes of an HEI were used in developing the recommender system and evaluated using ISO 9126 for Software Quality. The developed predictive model was tested using Classification and Regression (C&R) Tree, C5.0, Quest Tree, Logistic Regression, random tree and Classification technique. On the basis of the findings, the Classification Technique was adopted since it had a higher accuracy rate. The recommender system helped improve employees in incident resolutions, productivity and efficiency, and have provided a significant reduction of students’ major and minor offences based on the classifiers using the CHAID Algorithm. The researchers recommend that further studies and empirical investigation be conducted on the analytical reports, and other data mining techniques may be applied to further improve the system, processes, and student services.

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Section: B Data Mining and Predictive Analyticsmentioning

confidence: 99%

Section: B Data Mining and Predictive Analyticsmentioning

confidence: 99%