Web-Based Skill Management and Task Recommender System for Military Reserve Force Mobilization
2026 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS), (2026), pp. 353-358
Dennis S. Nava
a
,
Ace C. Lagman
b
,
Isagani M. Tano
c
,
Keno C. Piad
d
,
Jayson M. Victoriano
e
,
Jonilo C. Mababa
f
,
Carlo A. Dendiego
g
,
Joseph D. Espino
f
a Graduate School Department, La Consolacion University Philippines Bulihan, City of Malolos, Philippines
b Graduate School Department, FEU Institute of Technology, Manila, Philippines
c Graduate School Department, Quezon City University, Quezon City, Philippines
d College of Information and Communications Technology, Bulacan State University, Malolos, Philippines
e Research Management Office, Bulacan State University, Malolos, Philippines
f Graduate School Department, La Consolacion University Philippines, Malolos, Philippines
g Open University System, Polytechnic University of the Philippines, Manila, Philippines
Abstract: The operational readiness of military reserve forces underpins national security and disaster response, yet persistent skill mismatches and manual task assignment hinder effective mobilization. This study developed a Web-Based Skill Management and Task Recommender System for Military Reserve Force Mobilization that integrates reservist profiling, skill tagging, task creation, automated recommendation, and notification delivery through a hybrid pipeline composed of (i) a rule-based filter that enforces minimum qualification constraints and (ii) a weighted multi-criteria scoring layer that ranks qualified personnel by skillset match, availability, proximity, and rank suitability. The system was built using the Agile methodology, and synthetic data modeled on the structure of real reservist profiles were used throughout development and evaluation to address confidentiality and operational security concerns. The system was evaluated by 26 respondents (11 IT experts and 15 military officers) selected through purposive sampling, using a structured questionnaire derived from the ISO/IEC 25010 Software Quality Model. The system was rated Very Acceptable across all eight quality characteristics, with weighted means ranging from 3.73 to 3.91. The hybrid approach was designed as a decision-support tool that surfaces transparent, auditable recommendations to reduce potential skill-to-task mismatches, while final deployment authority remains with qualified military personnel.