Acreditation Sinta
Article Template
Jurnal Bali Membangun Bali is committed to maintaining high standards of academic integrity, transparency, and publication ethics. As Artificial Intelligence (AI) and Generative AI technologies evolve, the journal management establishes the following provisions regarding AI use for Authors, Peer Reviewers, and Editors.
| Stakeholder | Policy Provisions & Requirements |
|---|---|
| Authors |
No AI Authorship: AI tools or LLMs do not qualify for authorship. AI lacks legal personality, cannot sign copyright agreements, and cannot be held accountable for manuscript content. Mandatory Disclosure: Authors must explicitly disclose the AI tool name, version, and specific section/purpose (e.g., grammatical editing, translation, data analysis) in the Methods or Acknowledgements section. Full Accountability: Authors bear full responsibility for content accuracy, integrity, and originality, ensuring outputs are free from plagiarism or data fabrication. |
| Peer Reviewers |
Confidentiality: Reviewers are prohibited from uploading or processing reviewed manuscripts into public AI tools without written permission from the Editor. Human Judgment: AI tools must not be used to generate review texts or evaluation decisions. Assessment must strictly reflect the reviewer's critical evaluation. |
| Editors |
Confidentiality & Editorial Decisions: Editors are prohibited from uploading submitted manuscripts into AI systems that store data for model training. All editorial decisions must rely on human judgment and collective editorial evaluation. |
This policy is structured based on the 4 main pillars of the COPE position statement on AI tools in research papers:
|
1. Authorship Accountability
Authorship carries legal and ethical responsibility. Authors must be capable of defending the methodology, data validity, and arguments presented. Because AI systems are software applications rather than legal entities, AI cannot grant consent, face litigation, or hold ethical accountability. |
2. Transparency & Replicability
Openness and replicability are core principles of science. When AI is employed in analytical processes or text generation, readers and reviewers are entitled to know the extent of technological intervention to keep research traceable. |
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3. Confidentiality Protection
Most public AI platforms store text inputs to train their models. Uploading unpublished manuscripts to public AI platforms equates to leaking unreleased work into the public domain, violating author copyright and review confidentiality. |
4. Prevention of Hallucination
Generative AI operates on statistical word prediction rather than factual truth, creating potential for "hallucinations" (fictitious citations or false data). Authors must manually verify all references and facts to prevent literature contamination. |