Page 115
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Project ATLAS: An Integrated Learning and Development Management
System with Automated CPD/PD Credit Tracking and Competency-
Based Talent Mapping Using ISO/IEC 25010:2023 Quality Metrics
Mhel Jun C. Dela Cruz, Eduardo R. Yu II
AMA University, Philippines
DOI:
https://doi.org/10.51583/IJLTEMAS.2026.150600011
Received: 05 June 2026; Accepted: 10 June 2026; Published: 02 July 2026
ABSTRACT
Traditional educational training frameworks in public sector governance often rely on disconnected learning
platforms, slow manual workflows for tracking professional development (CPD/PD) credits, and fragmented
visibility between training initiatives and workforce skill profiles. To address these bottlenecks, this study
designed, developed, and validated Project ATLAS (Advanced Training and Learning Administration System),
an integrated Learning and Development Management System featuring automated CPD/PD credit tracking,
role-stratified administrative dashboards, and competency-based talent mapping engines. Built on a custom
Model-View-Controller (MVC) architecture in PHP, a lightweight server-side hypermedia stack, MySQL
relational database, and secured through Cloudflare Zero Trust outbound tunnels, the system replaces error-
prone manual processes with reliable automation. The platform's architectural quality and functional suitability
were evaluated using a descriptive engineering design aligned with the ISO/IEC 25010:2023 software product
quality model. A purposive sample of 15 technical experts and administrative evaluators assessed the system,
yielding an overall quality score of 3.91 out of 4.00 (SD = 0.11). Security (M = 3.96, SD = 0.05) and Safety (M
= 3.94, SD = 0.08) dimensions received the highest ratings. These findings demonstrate that custom MVC
backend layers combined with optimized relational database constraints deliver enterprise-grade security,
minimized network latencies, and high administrative efficiency in resource-constrained public educational
settings. Project ATLAS offers a scalable, compliant, data-driven architecture that mitigates administrative
backlogs, preserves institutional memory, and aligns workforce capabilities with institutional needs.
Keywords: Design Science Research, ISO/IEC 25010:2023, Competency Mapping, Learning Management
System, Professional Development Tracking.
INTRODUCTION
Modern public educational institutions are undergoing rapid digital transformation toward centralized cloud-
based applications and automated information architectures (Bratamanggala, 2023). Tracking continuous
professional development (CPD) milestones and delivering competency-focused training are essential for
maintaining instructional standards and regulatory compliance (Panda, 2025). Educational governance units
increasingly rely on integrated web-based learning environments to upskill both teaching and non-teaching
personnel, harmonizing localized professional growth with macro-level institutional expectations (Schuetze et
al., 2024). This emphasis on outcome-based instruction demands automated learning analytics and intelligent
dashboards to measure, record, and evaluate competency acquisition across organizational tiers (Chaudhari et
al., 2026). Digital archiving frameworks and portfolio systems further support systematic recording of
professional development milestones and institutional capacity building through lifelong learning paths (Sari,
2026).
Organizations are also transitioning from static spreadsheets to algorithmic human resource management and
data-driven talent mapping to isolate operational capabilities and deploy specialized personnel effectively
(Meijerink et al., 2021).
Page 116
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Despite these advancements, many public institutional training workflows remain fragmented (Bratamanggala,
2023; Phaladi & Ngulube, 2024; Chaudhari et al., 2026). Traditional off-the-shelf software routinely fails to
align with localized public sector regulations, resulting in unoptimized database queries and low processing
performance. Consequently, institutional training curricula are often designed based on anecdotal reports rather
than empirical learning data, leading to misallocated development funding and isolated workforce performance
appraisals (Chaudhari et al., 2026).
The Proposed Solution: Project ATLAS
This study bridges these operational and systemic gaps by designing, developing, and validating Project ATLAS,
an integrated Learning Management System featuring automated CPD/PD credit tracking, role-stratified
management modules, interactive virtual training environments, and systematic learning needs assessment
engines. The system coordinates training data collection and translates it into real-time metrics for institutional
decision-makers. Researchers evaluated the system's structural and operational quality against the ISO/IEC
25010:2023 software product quality model (International Organization for Standardization & International
Electrotechnical Commission, 2023). This research demonstrates how combining custom MVC logic with a
lightweight hypermedia frontend achieves high performance and robust data security in resource-constrained
public sector environments.
Core Pillars of Human Resource Development
The contributions of Project ATLAS rest on six core pillars of human resource development in the educational
sector:
a) Outcome-Based Professional Growth: Modular Verification Engine
The platform establishes an outcome-based framework using a Modular Verification Engine, ensuring
earned PD units reflect verified competency achievements rather than passive registration. It implements
a customized scoring framework aligned with Outcome-Based Education (OBE) principles, replacing
"seat-time" tracking with verifiable outcome metrics (Ni’mah et al., 2023; Crespo et al., 2010).
b) Automated Regulatory Compliance: Centralized CPD Dashboard
The system automates compliance by consolidating CPD milestones into a single downloadable
dashboard, enabling "Digital CPD" for data-driven decision-making and reduced administrative
overhead (Panda, 2025; Margienė et al., 2022).
c) Resource Person Repository: Strategic Talent Mapping
The repository enables scientific identification of internal Subject Matter Experts based on empirical
performance data. It maps experience into a unified skill graph, eliminating ambiguous role descriptions
(Gugnani et al., 2018; Meijerink et al., 2021).
d) Administrative Optimization: Automated Certification Engine
An Automated Certification Engine generates digital certificates immediately upon module mastery,
reducing processing times by over 80% and mitigating human error (Bin Md Nor et al., 2026;
Bratamanggala, 2023).
e) Data-Driven L&D Planning: Localized Gap Analytics
Page 117
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
The platform supports data-driven planning through high-level analytics for training gap analysis and
fiscal optimization of funding, grounded in Competency-Based Training Needs Analysis (Vassileva et
al., 2024; Chaudhari et al., 2026).
f) Institutional Memory Preservation: Searchable Digital Archive
The system serves as a permanent, searchable archive for historical training milestones, protecting the
organization from knowledge drain (Marriott & Martinez-Marroquin, 2021; Phaladi & Ngulube, 2024).
Key Takeaway: Project ATLAS shifts public sector educational IT from fragmented standalone instances to an
interconnected ecosystem optimized for ISO/IEC 25010:2023 quality dimensions under resource constraints.
Framework of the Study
This study employs a Design Science Research (DSR) paradigm to guide the iterative engineering lifecycle,
integrating continuous feedback loops across problem identification, artifact creation, and evaluation
Fig. 1. Methodological Integration Framework.
METHODOLOGY
This study adopted a developmental research design focused on architectural modeling, algorithmic
implementation, and empirical quality validation of the software artifact. A hybrid approach combined the
Successive Approximation Model (SAM) with Scrum’s iterative, high-velocity delivery cycles.
Technical Architecture and System Environment
The application follows a strict multi-tier Model-View-Controller (MVC) architectural pattern.
Backend Logic Layer: Lightweight PHP for programmatic processing and service abstractions, with
Python integration for specialized data science and statistical operations.
Relational Database Tier: MySQL configured for relational entity processing, strict foreign key
constraints, and data integrity (core tables: USERS, VIRTUAL_ROOMS, ROOM_ACTIVITIES,
ROOM_RESOURCES, FILE_ASSETS).
Frontend Interface Stack: Lightweight hypermedia-driven architecture using HTMX for low-latency
asynchronous updates, Alpine.js for client-side reactivity, and Tailwind CSS for responsive design.
Page 118
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Network and Production Infrastructure: Cloudflare Zero Trust architecture with encrypted outbound tunnels.
Prototyping used an Alienware m15 R6 workstation; production deployment utilized a Dell PowerEdge R250
server with NAS backup and load-balanced multi-fiber connectivity.
Fig. 2. Project ATLAS Multi-Tier System Architecture Diagram.
Relational Data Store - The database architecture tracks system activities by organizing entities across highly
normalized relational tables. Core tables include USERS, VIRTUAL_ROOMS, ROOM_ACTIVITIES,
ROOM_RESOURCES, and FILE_ASSETS. Relational links enforce cascading rules to protect operational
histories.
Fig. 3. ATLAS Database Schema Diagram illustrating core entity relationships.
Programmatic control is structured using distinct Object-Oriented component definitions. The interaction model
maps workflows through specific execution scopes across controllers, models, and service classes.
Page 119
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Fig. 4. Project ATLAS Relational Architecture Class Diagram
Functional Decomposition and Data Flow Diagram
The operational pipeline maps raw personnel activity metrics into analytical reporting data, functioning down to
Level 1 Data Flow Diagram resolution.
Fig. 5. Level 1 Data Flow Diagram (DFD): Project ATLAS Operational Ecosystem.
Page 120
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Evaluation Instrument and Purposive Sampling Plan
The system was evaluated using a 40-item instrument mapped to ISO/IEC 25010:2023 quality attributes. A
purposive sample of 15 evaluators (technical experts, administrative leaders, and end-users) rated features on a
4-point Likert scale. Quantitative analysis used sample means (M) and standard deviations (SD):
RESULTS
Key Features of the Developed Web-Based System
Project ATLAS includes a unified authorization portal, role-stratified dashboards with summary metrics and
interactive widgets, training management interfaces, personal record tracking with XP and badges, personnel
audit tables, virtual training rooms, curriculum content players with inline quizzes, strategic analytics boards,
needs analysis questionnaires, audit logs, forum management, nomination workflows, and comprehensive LMS
administration (Figs. 6–19).
Fig. 6: Login Page: Screen display showing the "ATLAS LMS" unified authorization portal requiring email and
password credentials over an encrypted route
Page 121
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Fig. 7: Dashboard Page: Main dashboard layout for user profiles displaying summary metrics (Courses Attended,
Pending Tasks, Completed Badges) alongside current course cards and interactive requirement tracking widgets
Fig. 8: Manage Training Page: Form view for Program Owners containing configuration selectors for daily
schedules, enrollment limits, and training venue designations
Fig. 9: Admin Dashboard Page (Master Admin Panel): System health screen outlining server configuration loads,
memory cache allocations, active Cloudflare secure routes, and global user registration counts
Page 122
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Fig. 10: My Records Page (My Profile): Personal record tracking profile ledger showing cumulative accrued
experience points (XP), logged certificates, and career milestone progress meters
Fig. 11: All Personnel Record Page (XP audit hub): Master table grid for HR officers allowing multi-vector
filtering of employee transcripts, recorded credits, and compliance standings
Fig. 12: Browse Virtual Room Page: Directory screen tracking available virtual training spaces and dynamic
room activity catalogs
Page 123
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Fig. 13: Program Details Page (Training Curriculum): Content player mapping lessons, inline quizzes, and
interactive progress tracking elements for active modules
Fig. 14: Strategic Analytics Page (Training Analytics): Visual analytics data boards tracking overall division-
level course completion rates, active enrollment numbers, and user distribution indices
Fig. 15: Needs Analysis (LDNA) Page: Digital diagnostic questionnaire interface aggregating self-assessment
skill matrices across Salary Grades 18–26
Page 124
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Fig. 16: Audit Logs: Read-only data table detailing timestamped system activities, user interactions, and
administrative updates for validation checking
Fig. 17: Forum Management: Community panel allowing administrative review, comment mapping, and
interaction tracking within collaborative learning hubs
Fig. 18: Nomination Management: Selection grid allowing HR administrators to approve, route, or override
participant nominations for specialized technical paths
Page 125
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Fig. 19: LMS Management: Core course management center displaying system-wide lesson catalogs, course
parameters, and module asset setups
Post-deployment verification confirmed 100% completion across core modules. The system manages operations
through a lightweight service layer across 47 routes with hardened Role-Based Access Control (RBAC) to
prevent privilege escalation. The interface employs a dark slate and indigo design with asynchronous HTMX
exchanges for fluid single-page behavior.
Quantitative Usability Metrics
Table 1. ISO/IEC 25010:2023 Software Quality Evaluation Summary Results
ISO/IEC 25010:2023
Quality
Characteristic
Covered Items / Evaluation
Scope
Mean
(M)
SD
(SD)
Adjectival
Interpretation
1. Functional
Suitability
Feature completeness,
grading correctness,
training appropriateness.
3.88
0.14
Strongly Agree
2. Performance
Efficiency
Response times, resource
utilization, file upload
capacities.
3.84
0.18
Strongly Agree
3. Compatibility
Co-existence with open
browser tabs, data
interoperability exports.
3.91
0.11
Strongly Agree
4. Interaction
Capability
Learnability,
recognizability, error
protection, user
engagement.
3.93
0.09
Strongly Agree
Page 126
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
5. Reliability
Platform availability, fault
tolerance, data
recoverability.
3.87
0.16
Strongly Agree
6. Security
RBAC confidentiality, data
integrity, audit trails,
authentication.
3.96
0.05
Strongly Agree
7. Maintainability
System modularity, layout
reusability, error
analysability.
3.89
0.13
Strongly Agree
8. Flexibility
Device adaptability,
database scalability,
installability.
3.92
0.10
Strongly Agree
9. Safety
Operational constraints,
hazard warnings, fail-safe
integration.
3.94
0.08
Strongly Agree
Overall Quality
Profile
Composite Evaluation
Metrics Summary
3.91
0.11
Strongly Agree
Mean Score Distribution
Fig. 20. Mean Score Visual Distribution Profile Chart.
Key Empirical Findings Narrative
Security (M = 3.96, SD = 0.05): This metric scored the highest overall value. Respondents confirmed
that the encrypted Cloudflare tunnel, parameterized database expressions, and role-based validation
matrices provide robust defenses against data tampering and vertical leaks.
Page 127
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
Safety (M = 3.94, SD = 0.08): Achieved high marks driven by strict database constraint layers.
Programmatic checks successfully prevent administrative users from executing accidental deletions of
active personnel records, while verification prompts stop raw data entry errors from affecting compliance
histories.
Interaction Capability (M = 3.93, SD = 0.09): Evaluators noted strong user retention parameters. The
integration of progress trackers and responsive text layouts allowed personnel across diverse age brackets
and technical skill levels to navigate core workflows easily.
Performance Efficiency (M = 3.84, SD = 0.18): Remained firmly inside the positive parameters but
displayed higher statistical variance. This behavior was traced to localized network bandwidth limits
during concurrent multi-user execution phases, such as processing bulk data exports or large certification
uploads.
DISCUSSION
Critical Evaluation of Technical Outcomes
The empirical results establish a high-performing software quality profile across evaluated dimensions (M =
3.91). However, a critical architectural examination reveals specific trade-offs inherent in the system's design.
The exceptional rating achieved for Security (M = 3.96) directly validates the isolation of data assets through a
Cloudflare Zero Trust outbound tunnel combined with strict role-based access control (RBAC) verification.
Enforcing multi-tier database role checks at every parent controller boundary creates an operational bottleneck
during complex application routing. Because server-side hypermedia architectures trigger separate, discrete
asynchronous HTTP requests for individual interface components (e.g., lazy-loaded elements or segmented page
updates), these security verification queries execute repeatedly per user interaction. While this mechanism
completely prevents vertical privilege escalation and unauthorized horizontal data access, it injects a recurring
processing overhead for every hypermedia block requested via HTMX. This distinct trade-off echoes systemic
design considerations documented in recent literature. Custom information architectures significantly maximize
control over public sector business rules, but they introduce rigid processing bounds that require careful data
layout and query optimization (Bratamanggala, 2023).
Similarly, the high score in Safety (M = 3.94) stems from deep backend validation rules and strict database
foreign key configurations. These database constraint layers successfully prevent administrative users from
executing destructive, cascading deletions of active personnel files. However, they heavily restrict system
flexibility. Modifying a primary user profile structure or shifting historical certification records requires updating
multiple relational dependencies simultaneously. This operational friction reinforces observations by Meijerink
et al. (2021) regarding the processing hurdles and systemic rigidity encountered when re-engineering fluid
administrative configurations into automated, highly normalized relational database platforms
Performance and Hypermedia Architecture
The lower relative rating and higher statistical variance observed in Performance Efficiency (M = 3.84, SD =
0.18) highlight a central architectural challenge. Unlike heavy, client-side JavaScript Single Page Application
(SPA) frameworks that handle data compilation and UI rendering tasks directly on the user's terminal device,
Project ATLAS utilizes server-side hypermedia exchanges via HTMX. This programmatic choice keeps the
client interface exceptionally responsive and minimizes the application's local memory footprint, directly
matching the strong ratings recorded for Maintainability (M = 3.89) and Interaction Capability (M = 3.93).
Unlike lightweight JSON payloads common in traditional client-side rendering, HTMX transfers raw HTML
fragments across the network wire for every dynamic state change or view update. When a large cohort of users
simultaneously triggers data actions—such as submitting local diagnostic assessments or uploading large PDF
certification files—the network infrastructure must process an immediate, sharp spike in data transfer volume.
Under standard local area conditions, the load-balanced multi-fiber lines at the division data center manage this
Page 128
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
traffic effectively. However, automated certification and evaluation engines that pass raw data or documents
across network boundaries require heavily optimized localized server infrastructure to prevent visible latency
under concurrent traffic spikes (Bin Md Nor et al., 2026). On slower, field-level wide area network connections,
this reliance on constant server-side rendering explains the increased statistical variance in efficiency ratings.
This demonstrates that server-side hypermedia shifts the operational dependency entirely onto the surrounding
network bandwidth.
Real-World Operational Insights
From an operational perspective, connecting individual learning histories directly with regional competency
needs assessments provides public governance units with an efficient, data-driven platform. The system
successfully replaces slow, error-prone manual calculations and separated spreadsheet logs with automated
dashboards, radically reducing clerical overhead for human resource units. This outcome directly supports the
empirical conclusions of Ni'mah et al. (2023), where automated modular tracking frameworks successfully
improved tracking accuracy by up to 40% while mitigating systemic data entry errors.
Nevertheless, the platform's long-term utility depends on keeping its internal competency models updated.
Because human resource criteria, training mandates, and licensing regulations shift frequently within the public
sector, hardcoded database benchmarks can quickly become obsolete. Appraisal and training systems remain
isolated unless they are tied to a dynamic taxonomy framework that evolves alongside institutional policy shifts
(Vassileva et al., 2024). To maintain its long-term effectiveness as an institutional tool without requiring
continuous developer intervention, the system must transition from static entity mapping to a flexible, user-
managed metadata framework.
CONCLUSION AND RECOMMENDATIONS
This study successfully engineered, deployed, and empirically validated Project ATLAS, an integrated Learning
and Development Management System designed to resolve the systemic operational fragmentation, tracking
delays, and data silos characteristic of traditional manual professional training frameworks. By consolidating
automated CPD/PD credit tracking routines, role-stratified dashboards, interactive virtual execution spaces, and
algorithmic talent profiling tools into a unified relational architecture, the platform provides a scalable blueprint
for digital modernization in public sector governance.
Field evaluation utilizing the international product quality baseline ISO/IEC 25010:2023 (International
Organization for Standardization & International Electrotechnical Commission, 2023) demonstrated that Project
ATLAS operates at an exceptional standard of technical excellence, earning a total overall quality score of 3.91
out of 4.00 (SD = 0.11). The platform's architectural resilience was strongly underscored by its peak scores under
the Security vector (M = 3.96, SD= 0.05) and Safety vector (M = 3.94, SD = 0.08). This empirically confirms
that isolating core data pathways with a custom MVC logic and secure Cloudflare Zero Trust network tunneling
completely mitigates risks of unauthorized access or accidental data anomalies.
Ultimately, Project ATLAS achieved its primary objective: replacing vulnerable, manual clerical procedures
with a high-performance, responsive hypermedia architecture that successfully drives verification accuracy,
eliminates certificate issuance backlogs, and provides clear visibility into organizational skill profiles.
Recommendations for Future Work
a) Cross-Institutional Scale-Testing: Because the initial evaluation cohort relied on a purposive sample of
administrative and technical evaluators within a centralized sector, future researchers should scale testing
across multi-tiered institutional environments to analyze system utility, load tolerances, and user
adoption variances over diverse, distributed governance units.
b) Telemetry and Direct Resource Monitoring: While the expert evaluation metrics confirmed high user
satisfaction and interface accessibility, future technical audits should transition from perception-based
scoring toward direct telemetry capture tracking raw server response latencies, database transaction
Page 129
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
velocities, concurrent payload overheads, and hardware resource utilization spikes during high-traffic
intervals.
c) Automated Skill Ontology Integration: Building upon the platform's custom competency mapping layout,
future software iterations should integrate natural language processing (NLP) layers and automated skill
ontologies to automatically parse, tag, and align unstructured text records with national professional
capability frameworks, minimizing manual parameter inputs.
d) Third-Party API & Distributed Integration: To enhance systemic utility, next-phase development should
engineer secure, open-standard API endpoints that allow Project ATLAS to securely sync data with
external legacy personnel registries and regional human resource tracking databases without introducing
security bottlenecks.
e) Proactive Cybersecurity Penetration Analysis: Although the platform's Zero Trust tunnel architecture and
database constraint layers earned exceptional security ratings, subsequent studies must subject the system
to formal white-box penetration testing and automated stress-testing simulations to explicitly verify its
structural defense against advanced cross-site and injection vulnerabilities.
Additional Statements
Conflict of Interest: The authors declare no conflict of interest.
Data Availability: System architecture and evaluation data are available upon reasonable request from
the corresponding author.
Ethical Approval: While explicit institutional human subjects approval was not required for this software
evaluation study, all expert and administrative evaluations were conducted voluntarily, anonymously,
and with informed consent.
REFERENCES
1. Bin Md Nor, A. R., Binti Adam, A., Ismail, M. S. B., & Bte Kamis, T. (2026). Development of an artificial
intelligence-assisted e-certificate system at Melaka Polytechnic: An innovative approach to TVET digital
transformation. Proceedings of the Economy of Asia International Conference, 2025(1), 1070–1078.
https://conference.asia.ac.id/index.php/ecosia/article/view/179
2. Bratamanggala, R. I. (2023). Digital transformation in human resource management: A systematic
literature review. Siber International Journal of Education Technology (SIJET), 1(2), 57–64.
https://doi.org/10.38035/sijet.v1i2.57
3. Chaudhari, S., Shah, K., & Ghonge, P. (2026). A data-driven framework for enhancing outcome-based
teaching, learning, and assessment using learning analytics and intelligent dashboards in higher education.
Indian Journal of Science and Technology, 19(11), 810–819. https://doi.org/10.17485/IJST/v19i11.263
4. Crespo, R. M., et al. (2010). Aligning assessment with learning outcomes in outcome-based education.
IEEE EDUCON 2010 Conference, 1239–1246. https://doi.org/10.1109/EDUCON.2010.5492385
5. Gugnani, A., Reddy Kasireddy, V. K., & Ponnalagu, K. (2018). Generating unified candidate skill graph
for career path recommendation. 2018 IEEE International Conference on Data Mining Workshops
(ICDMW), 328–333. https://doi.org/10.1109/ICDMW.2018.00054
6. International Organization for Standardization and International Electrotechnical Commission. (2023).
Systems and software engineering — Systems and software quality requirements and evaluation
(SQuaRE) — Product quality model (ISO/IEC Standard No. 25010:2023).
https://www.iso.org/standard/78175.html
7. Margienė, A., Ramanauskaitė, S., Nugaras, J., Stefanovič, P., & Čenys, A. (2022). Competency-based e-
learning systems: Automated integration of user competency portfolio. Sustainability, 14(24), Article
16544. https://doi.org/10.3390/su142416544
8. Marriott, C., & Martinez-Marroquin, E. (2021). Design principles for auto-mapping professional
competencies. Proceedings of the 9th Research in Engineering Education Symposium and 32nd
Australasian Association for Engineering Education Conference (REES AAEE 2021), 334–343.
https://aaee.net.au/wp-content/uploads/2021/11/REES_AAEE_2021_paper_304.pdf
Page 130
www.rsisinternational.org
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026
9. Meijerink, J., Boons, M., Keegan, A., & Marler, J. (2021). Algorithmic human resource management:
Synthesizing developments and cross-disciplinary insights on digital HRM. The International Journal of
Human Resource Management, 32(12), 2545–2562. https://doi.org/10.1080/09585192.2021.1925326
10. Ni’mah, A. T., Solihin, F., & Sari, I. U. (2023). Outcome-based education scoring system utilizing modular
object-oriented dynamic learning environment. Jurnal Pamator: Jurnal Ilmiah Universitas Trunojoyo,
16(4), 845–864. https://doi.org/10.21107/pamator.v16i4.23726
11. Panda, S. (2025). Editorial: Technology and ODL for continuing professional development and lifelong
learning. Journal of Learning for Development, 12(3), i–vi. https://doi.org/10.56059/jl4d.v12i3.2607
12. Phaladi, M. P., & Ngulube, P. (2024). Understanding tacit knowledge loss in public enterprises of South
Africa. SA Journal of Human Resource Management, 22(0), Article a2229.
https://doi.org/10.4102/sajhrm.v22i0.2229
13. Sari, C. A. (2026). The role of digital archiving systems in improving operational efficiency: Evidence
from corporate administration. Applied Multidisciplinary Science, 1(3), 1–11.
https://doi.org/10.64276/ams.v1i3.72
14. Schuetze, H., De Vries, W., & Mendiola, G. A. (2024). Digitalization of higher education: An introduction
to the issues. Journal of Comparative & International Higher Education, 16(2).
https://doi.org/10.32674/jcihe.v16i2.5975
15. Vassileva, G., Monov, V., & Blagoev, I. (2024). Competency-based training needs analysis: Bridging gaps
for enhanced education. EDULEARN24 Proceedings, 9909–9915.
https://doi.org/10.21125/edulearn.2024.2380
