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SHANETH C. AMBAT
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Humanities Education Languange, Linguistic, Communication & Media Physics Social Sciences

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Mining crime instance records of Philippine National Police District Vi âA ¸S˘ Province of Cavite, Philippines: An Exploratory Study to Enhance Crime Prevention Programs MENGVI P. GATPANDAN; SHANETH C. AMBAT
Journal of Advanced Research in Social Sciences and Humanities Volume 2, Issue 3, June 2017
Publisher : Journal of Advanced Research in Social Sciences and Humanities

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Aim: This analysis aimed to assess the effectiveness, productivity, and management of one of the country’s national police forces. In this study, especially in the data envelopment analysis, crime management was taken into account as the primary function of the police, which necessitated the use of resources that were viewed as decision-making units.Methodology: To identify productive DMUs, the study combined a Rate-to-Scale (RTS) metric based on scale efficiency with an input-oriented radial measure of efficiency. In the analytical tasks, clustering was used as part of a structured approach to planning data mining activities known as CRISP-DM.Findings: Municipality C is the most efficient DMU based on the 3-year scale efficiency result.Implications/Novelty: Given the current push by the government and the PNP to eradicate criminality and illegal activity in the Philippines, this research couldn’t come at a better time. This research aided police departments and crime scene investigators in identifying patterns of criminal activity and performing geospatial analyses.
Implementing knowledge discovery in enhancing university student services portfolio management in higher education institutions PAULINO H. GATPANDAN; SHANETH C. AMBAT
Journal of Advanced Research in Social Sciences and Humanities Volume 2, Issue 3, June 2017
Publisher : Journal of Advanced Research in Social Sciences and Humanities

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Aim: The Student Welfare and Formation Office (SWAFO) of De La Salle University-Dasmarinas, Philippines, used Classification Techniques and Data Envelopment Analysis to analyze student demographics and disciplinary infractions. This paper describes how Knowledge Discovery was used to improve the management of the university’s portfolio of student services.Methodology: To identify the effective Decision-Making Unit (DMU) attributed to colleges, the Data Envelopment Analysis was used. The correlation between student demographics and offending behavior was analyzed using the CHAID algorithm.Findings: The CHAID algorithm is implemented in a software application that is designed to be a predictive analytical software application that predicts student offenses, and a remediation plan is developed as a result. The SWAFO staff and five (5) IT professionals evaluate the software.Implications/Novelty: This research will help SWAFO’s process improvement initiative and delve deeper into the change by utilizing the remediation system plan. This work adds to our understanding of DEA and the design of remediation systems in higher education.
Co-Authors MENGVI P. GATPANDAN PAULINO H. GATPANDAN