Current Volume 6
This research used the quantitative approach utilizing a descriptive-developmental research design and survey questionnaire technique to efficiently gather data and establish a systematic way of designing and evaluating University Support System Program Placement using a Predictive Decision Tree Data Model employing a Rapid Application Development (RAD) in the development. The researcher used a standardized set of questions based on the constructs of ISO/IEC 25010 to measure the user acceptability of the system. The survey forms were distributed after finishing the testing phase of the proposed system were held to obtain data from ten (10) information technology experts as alpha evaluators, six (6) BulSU - Bustos admin council as beta evaluators, and four (4) admission clerk as gamma evaluators are chosen using purposive sampling. Results show that University Support System Program Placement using Decision Tree Data Model is excellent in terms of functional suitability (M=4.72), performance efficiency (M=4.78), compatibility (M=4.72), usability (M=4.80), reliability (M=4.67), security (M=4.58), maintainability (M=4.73), portability (M=4.77) recording a grand mean of 4.72 interpreted as excellent. It means that the system satisfies both software quality standards and end-user requirements. Thus, it is ready for adoption. Along with its implementation, it is recommended to gather feedback regularly and conduct an impact analysis of the effectiveness of using the university support system program placement using a decision tree data model.
Decision Tree, Datamining, Program Placement, Decision Support System, RAD
Alaina Thea V. Concepcion , Joseph D. Espino "University Support System Program Placement Using Predictive Decision Tree Data Model" Iconic Research And Engineering Journals Volume 6 Issue 11 2023 Page 98-107
Alaina Thea V. Concepcion , Joseph D. Espino "University Support System Program Placement Using Predictive Decision Tree Data Model" Iconic Research And Engineering Journals, 6(11)