SPU-SCOPUS Artificial Intelligence (SPU-SCOPUS AI)

SPU-SCOPUS AI is an artificial intelligence–based expert system developed to support journal identification and selection within the Scopus database. The system is designed to assist researchers in identifying the most appropriate Scopus-indexed journals for manuscript submission by systematically analyzing manuscript characteristics, researcher profiles, and journal performance indicators.
Integrated as the intelligence layer of the SPU Scopus Publication System (SPS), SPU-SCOPUS AI transforms journal selection from a manual, experience-based process into a data-driven, transparent, and evidence-based decision-support mechanism.

The primary purpose of SPU-SCOPUS AI is to:

• Identify Scopus-indexed journals that best align with a manuscript’s scope, methodology, and academic contribution
• Reduce journal mismatch and unnecessary rejection cycles
• Support strategic targeting of journals by Scimago Journal Rank (SJR) quartile (Q1–Q4)
• Enhance publication efficiency and research visibility

The system focuses exclusively on journal identification and recommendation and does not generate research content or guarantee publication acceptance.

1. Manuscript–Journal Matching Engine
SPU-SCOPUS AI analyzes key manuscript attributes, including:

• Research keywords and thematic focus
• Academic discipline and subject classification
• Research methodology and data characteristics
• Article type (empirical, conceptual, review, case study)

These inputs are systematically matched against the scope, aims, and historical publication patterns of journals indexed in the Scopus database.

2. Scopus Journal Intelligence Module
This module utilizes structured journal metadata, including:

• Scopus subject areas and classifications
• Scimago Journal Rank (SJR) quartiles (Q1–Q4)
• Journal scope statements and editorial focus
• Publication frequency and review characteristics

The system evaluates alignment between manuscript content and journal profiles to determine suitability and ranking.

3. Researcher Profile Alignment Module
SPU-SCOPUS AI integrates researcher identification data, including:

• Scopus Author ID
• ORCID
• Web of Science ResearcherID

By considering a researcher’s publication history, subject expertise, and prior journal experience, the system improves the accuracy and relevance of journal recommendations.

4. Journal Recommendation Output
Based on integrated analysis, SPU-SCOPUS AI generates:

• A ranked list of recommended Scopus-indexed journals
• Classification by quartile level (Q1–Q4)
• Rationale for each recommendation (scope fit, discipline alignment, methodological compatibility)
• Strategic guidance on journal selection order (primary and alternative targets)

All recommendations are presented through the SPS dashboard in a clear and interpretable format.

SPU-SCOPUS AI is fully embedded within SPS and supports:

• Manuscript submission workflows
• Get a Quote service pricing recommendations based on target journal quartile
• Editorial and consultation service allocation
• Researcher dashboards and administrative oversight

The integration ensures consistency between journal identification, service planning, and publication strategy.

For researchers, SPU-SCOPUS AI provides:

• Objective and data-driven journal identification
• Reduced trial-and-error in journal selection
• Improved submission confidence and efficiency

For institutions, the system supports:

• Standardized journal selection practices
• Monitoring of targeted journal quartiles
• Strategic planning for Scopus publication output
• Scalable deployment across faculties and partner universities

SPU-SCOPUS AI operates under strict academic and ethical standards:

• No automated manuscript writing or content generation
• No manipulation of bibliometric indicators
• Full transparency in recommendation logic
• Human oversight in all publication decisions

The system serves as a decision-support tool, not a substitute for scholarly judgment or editorial authority.

SPU-SCOPUS AI is developed as a modular and transferable system, allowing:

• Deployment across multiple faculties within SPU
• Adaptation for partner universities through franchising or licensing
• Integration with institutional research databases and CRIS platforms

This scalability positions SPU-SCOPUS AI as a foundational tool for institutional research management and Scopus publication strategy.

SPU-SCOPUS AI, integrated into the SPU Scopus Publication System (SPS), is an artificial intelligence expert system designed to identify the most appropriate journals indexed in the Scopus database, supporting data-driven, ethical, and strategic publication decision-making for researchers and institutions.