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BSIT · 2023

DEVELOPMENT OF AN ALUMNI TRACER FOR THE COLLEGE OF COMPUTER STUDIES AND ENGINEERING (CCSE): A WEB-BASED APPLICATION

Researchers

Keith Oddri Cruz, Ailene Jen D. DeleƱa, Reika T. Martinez

Adviser

Jimmy DV. Roldan, MSIT

Abstract

The general objective of this research focuses on developing a viable web-based Alumni database system that will serve as a central data repository for all alumni information, track down the graduates of the College of Computer Studies and Engineering (CCSE), and introduce solutions to overcome the problems faced by existing manual systems. The Development of an Alumni Tracer for the College of Computer Studies and Engineering (CCSE): A Web-Based Application for Tracing Graduates of the Colegio de San Gabriel Arcangel is designed in this project to make searching easier and retrieve alumni details using the admin system. The goals of our system are also directed toward 4th-year students who need housing. Additionally, this project is designed so that it will not be difficult for 4th-year students to find Onthe-Job Training (OJT) opportunities. The CCSE administrator will be able to get in touch with alumni using their contact information if a company needs an intern, allowing for easier communication with graduates. Survey evaluation questionnaires were distributed to alumni of Colegio de San Gabriel Arcangel and one CCSE administrator to rate the performance of the web-based application. After respondents completed the assessment form, the researchers totaled the collected data based on the number of respondents and the number of questions in each category. The major goal of the statistical survey was to see if the system was working properly and meeting its goals and objectives. Researchers gathered data from 15 graduates and 1 administrator from the CCSE Department. The application's evaluation results yielded an overall score of 4.63 for functionality, 4.83 for reliability, 4.76 for usability, and 4.60 for efficiency. This indicates that the proposed Alumni Tracer System has an overall verbal interpretation of Very Good based on the statistical metrics provided by the respondents

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