Benedict D. Alvarez
StudentBSIT Student Specializing in Business Analytics
Quezon, Metro Manila · FEU Institute of Technology
Personal Information
Short Biography
Benedict Alvarez is a fourth-year BSIT student specializing in Business Analytics at FEU Institute of Technology. He has strong leadership experience, having served in various organizations since primary school. Skilled in quality analysis, process evaluation, and data-driven problem solving, he is passionate about ensuring accuracy and efficiency in business processes. Outside of tech, he enjoys singing as a worship and wedding singer in his church.
🛠️ Skills
Time Management
Expert (84%)
Communication
Competent (70%)
Active Listening
Expert (90%)
Problem-Solving
Competent (70%)
Teamwork
Advanced (80%)
🎓 Educational Qualification
Tertiary · Sep 2022 - Present
Bachelor of Information Technology
Business Analytics · FEU Institute of Technology - Manila
Secondary · Jul 2020 - Aug 2022
Dr. Carlos S. Lanting College - Quezon City
Secondary · Aug 2016 - Aug 2020
Dr. Carlos S. Lanting College
Primary · Mar 2011 - Mar 2016
Placido Del Mundo Elementary School
Preschool · Jun 2007 - Jun 2008
Jesus Almighty
🏆 Honors and Awards
With Honors
Issued by Dr. Carlos S. Lanting College on August 05, 2018
Joy of Public Service Awardee
Issued by Placido Del Mundo Elementary School on August 30, 2016
It is hereby institutionalized to recognize students in the Grade 6 and Grade 12 levels who have aptly demonstrated the value of service above self by showing exemplary commitment to the service of the school, its communities and its students.
Student of the month
Issued by Dr. Carlos S. Lanting College on August 03, 2016
MTAP
Issued by Placido Del Mundo Elementary School on June 30, 2016
School Level - Individual Category - 5th Place Division Level - Group Category - Champion Regional Level - Group Category - 2nd Place
Champion
Radio Broadcasting (English) - Overall Champion
Issued by Placido Del Mundo Elementary School on October 20, 2014
Issued by Division School Press Conference 2016 English Group Category - Champion
📜 Licenses and Certifications
PMI Project Management Ready
Issued by Project Management Institute on March 14, 2025
View Credential
👨🏻🏫 Seminars and Trainings
Attendee
Gartner 2023 Leadership Vision for Technology Innovation
Awarded by Gartner on May 03, 2023
Attendee
Create a Robust AI Strategy – From Plan to Execution
Awarded by Gartner on May 02, 2023
Attendee
Journalism
Awarded by Sta Lucia High School on October 29, 2015
👥 Organizations and Memberships
FEU Tech Artist Connection - Manila
Member · September 30, 2022 - April 20, 2023
Supreme Student Government - Quezon City
President · October 13, 2016 - September 13, 2022
PDMES Library Organization - Quezon City
President · October 29, 2015 - October 28, 2016
Journalism - Quezon City
Assistant Editor in Chief · October 22, 2015 - August 27, 2016
Red Cross Youth - Quezon City
President · September 13, 2015 - October 13, 2016
Research Publications
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Conference Paper · 10.1109/ICTKE67052.2025.11274439
Predicting Intention to Use OceanGuardian: a Sustainable E-Commerce for Marine Conservation Products using Machine Learning Techniques2025 23rd International Conference on ICT and Knowledge Engineering (ICT&KE), (2025), pp. 1-6
Marine ecosystems face unprecedented threats from pollution, overfishing, and climate change, creating an urgent need for conservation initiatives. While consumer awareness of ocean degradation is increasing, there remains a persistent gap between environmental concern and actual purchasing behavior toward sustainable products. This study aims to examine public readiness to adopt OceanGuardian, a sustainable e-commerce platform for marine conservation products, by integrating behavioral, technological, and environmental perspectives. Using a modified Extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, survey data from 600 respondents were analyzed with machine learning models, including Support Vector Machines, Random Forests, and XGBoost, to identify key determinants of consumer intention and use behavior. Results indicate that social influence, performance expectancy, affordability, and habit formation significantly predict adoption, with Support Vector Machines achieving the highest predictive accuracy (92.5%). The findings highlight the potential of artificial intelligence to enhance consumer behavior analysis while recognizing challenges such as economic barriers and consumer skepticism. The study offers theoretical contributions by extending UTAUT2 with environmental factors and provides practical insights for policymakers and businesses to design strategies that foster sustainable shopping and strengthen marine conservation efforts.