Alumni Tracer and Management System with Data Analytics: Enhancing Alumni Engagement and Data Management for South East Asian Institute of Technology, Inc

Alumni Tracer Systems track graduates’ career paths and determine whether they correspond with their undergraduate degrees. These systems help institutions understand employment trends and how well their programs prepare students for the workforce. South East Asian Institute of Technology, Inc. (SEAIT) lacks a system to monitor its alumni, making it difficult to determine whether graduates pursued careers related to their studies. To address this, the SEAIT Alumni Tracer and Management System with Data Analytics was developed as a practical solution by integrating multiple features to improve alumni tracking and engagement. It was designed to aid the institution in keeping track of and strengthening its connection with its graduates. The system was created using the Agile methodology, with iterative sprints ensuring continuous improvements based on survey feedback and data-driven decision-making through data analytics. The System Usability Scale (SUS) evaluation yielded a high average score of 86.67, confirming the system’s usability and effectiveness. The system proved to be practical and viable in assisting SEAIT in monitoring its graduates and enhancing its academic programs by evaluating career alignment with fields of study and supporting data-driven improvements in education. Therefore, the implementation of the system was strongly recommended.

Authors

Publication Details

Journal
International Journal of Research and Innovation in Social Science
Published
2025-01-01
DOI
https://doi.org/10.47772/ijriss.2025.90400370
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Alumni Tracer and Management System with Data Analytics: Enhancing Alumni Engagement and Data Management for South East Asian Institute of Technology, Inc

Hernan Jr. E. Trillano, Reginald S. Prudente, Lina A. Mondejar
International Journal of Research and Innovation in Social Science
Big Data and Business Intelligence
article

Alumni Tracer and Management System with Data Analytics: Enhancing Alumni Engagement and Data Management for South East Asian Institute of Technology, Inc

Hernan Jr. E. Trillano, Reginald S. Prudente, Lina A. Mondejar
article en

Abstract

Alumni Tracer Systems track graduates’ career paths and determine whether they correspond with their undergraduate degrees. These systems help institutions understand employment trends and how well their programs prepare students for the workforce. South East Asian Institute of Technology, Inc. (SEAIT) lacks a system to monitor its alumni, making it difficult to determine whether graduates pursued careers related to their studies. To address this, the SEAIT Alumni Tracer and Management System with Data Analytics was developed as a practical solution by integrating multiple features to improve alumni tracking and engagement. It was designed to aid the institution in keeping track of and strengthening its connection with its graduates. The system was created using the Agile methodology, with iterative sprints ensuring continuous improvements based on survey feedback and data-driven decision-making through data analytics. The System Usability Scale (SUS) evaluation yielded a high average score of 86.67, confirming the system’s usability and effectiveness. The system proved to be practical and viable in assisting SEAIT in monitoring its graduates and enhancing its academic programs by evaluating career alignment with fields of study and supporting data-driven improvements in education. Therefore, the implementation of the system was strongly recommended.

International Journal of Research and Innovation in Social ScienceVol. IX(IV)
Openalex Percentile: Top 83%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.