Artificial Intelligence (AI) & Generative AI Policy

Jurnal Kimia VALENSI, published by the Department of Chemistry, Faculty of Science and Technology, UIN Syarif Hidayatullah Jakarta, is committed to responsible, transparent, and ethical use of artificial intelligence in scientific research, manuscript preparation, peer review, and editorial publishing.

The journal recognizes the development of artificial intelligence, machine learning, computational modeling, and other AI-assisted technologies as important advances in modern chemical science. These technologies may support scientific analysis, computational research, and manuscript preparation, provided their use is transparent, scientifically justified, and subject to meaningful human supervision.

However, the use of generative AI in scientific writing must not compromise the originality, authenticity, methodological reliability, intellectual contribution, confidentiality, or scientific integrity of submitted and published research.

This policy applies to authors, peer reviewers, editors, Editorial Board members, and other individuals involved in the journal's publication process. It should be read together with the journal's Declaration of Generative AI in Scientific Writing, Publication Ethics, and other relevant editorial policies.

Artificial intelligence may support scientific work, but it must not replace human responsibility for experimental validity, theoretical reasoning, scientific interpretation, originality, or publication decisions. Human researchers and editorial personnel remain accountable for the accuracy, reliability, ethics, and integrity of their respective contributions.

Jurnal Kimia VALENSI permits the use of generative AI and AI-assisted writing technologies for limited supporting purposes intended to improve the readability and language quality of scientific manuscripts.

Permitted supporting activities include:

• Grammar and Spelling: Correcting grammatical errors, spelling mistakes, punctuation, and linguistic inconsistencies.
• Language Readability: Improving sentence clarity and readability without modifying the original scientific meaning.
• Scientific Language Editing: Assisting authors in improving the English presentation of text originally prepared through their own research and intellectual work.
• Translation Assistance: Supporting language translation, provided chemical terminology, scientific concepts, and research interpretations are independently verified.
• Technical Language Consistency: Identifying inconsistent wording or linguistic expressions, subject to author verification.

Authors must carefully review and edit all AI-assisted text before submission. AI-generated suggestions must not be accepted without verifying scientific accuracy, proper terminology, references, and consistency with the original research.

The journal recognizes that artificial intelligence, machine learning, and computational algorithms may constitute legitimate scientific methods within chemical research.

Relevant applications may include:

• Computational Chemistry: AI-assisted molecular modeling and predictive computational approaches.
• Chemoinformatics: Chemical database analysis, molecular descriptors, and predictive property modeling.
• QSAR and Molecular Prediction: Quantitative structure-activity relationship modeling and prediction of molecular properties.
• Analytical Chemistry: Machine-learning methods for spectral classification, chromatographic interpretation, chemometric analysis, and analytical pattern recognition.
• Materials Chemistry: Data-driven prediction of material properties, structure-property relationships, and candidate materials.
• Environmental Chemistry: Predictive modeling of contaminants, environmental processes, or chemical exposure.
• Drug Discovery and Natural Products: Computational screening, molecular interactions, and prediction of relevant chemical or biological properties.

Where AI or machine learning forms part of the scientific methodology, the manuscript must provide sufficient information for critical evaluation and reproducibility.

The journal prohibits the use of AI technologies in ways that compromise research authenticity, scientific reliability, originality, or publication ethics.

Unacceptable practices include:

• Fabricated Experimental Data: Generating fictitious laboratory measurements, chemical analyses, experimental observations, or research findings.
• Fabricated Analytical Evidence: Creating or altering NMR, FTIR, UV-Vis, XRD, mass spectrometry, chromatography, or other analytical outputs and falsely presenting them as authentic measurements.
• Manipulated Scientific Images: Generating or modifying microscopy images, material characterization images, reaction documentation, or laboratory photographs in ways that misrepresent actual observations.
• False Scientific References: Citing nonexistent journal articles, fabricated DOIs, imaginary experimental methods, or unverified bibliographic sources.
• Misrepresentation of Computational Results: Presenting invented computational outputs, molecular predictions, or simulation results as if produced by documented scientific methods.
• Replacement of Scientific Reasoning: Presenting AI-generated interpretations, discussions, or conclusions as the authors' independently established scientific findings without meaningful verification or contribution.
• Concealment of Plagiarism: Using AI paraphrasing or rewriting to disguise copied or improperly attributed scholarly material.
• Unauthorized Disclosure: Uploading confidential research records, unpublished findings, protected intellectual property, or identifiable research information to external AI systems without appropriate authorization.

Authors must transparently disclose the use of generative AI and AI-assisted technologies in scientific writing when submitting manuscripts to Jurnal Kimia VALENSI.

The declaration should identify:

1. The name of the AI tool or technology used.
2. The purpose of its use.
3. The part of the manuscript affected.
4. The nature of the assistance provided.
5. How the authors reviewed and verified the output.

Authors should provide relevant information about AI-assisted manuscript preparation during submission and must include the required declaration in the manuscript.

All declarations must accurately reflect the technologies actually used. Authors must not make false or misleading statements concerning AI assistance.

Artificial intelligence systems, chatbots, large language models, and other automated technologies must not be listed as authors or co-authors of manuscripts submitted to Jurnal Kimia VALENSI.

Authorship is reserved for individuals who make qualifying intellectual contributions and can assume responsibility for the accuracy, originality, scientific integrity, and ethical conduct of the research.

Human authors remain responsible for:

• Originality and scientific accuracy of the manuscript.
• Authenticity of experimental data and laboratory records.
• Accuracy of computational procedures and model outputs.
• Validity of analytical interpretations and conclusions.
• Appropriate attribution and verification of references.
• Compliance with research ethics and relevant institutional requirements.
• Identification and correction of AI-generated inaccuracies, biases, or misleading statements.
• Final review and approval of the submitted manuscript.

Chemical research may involve unpublished experimental findings, proprietary molecular structures, commercially sensitive formulations, confidential industrial collaborations, and ethically protected biological information.

Authors must ensure that the use of external AI systems does not violate research confidentiality, intellectual property rights, contractual obligations, or applicable ethical requirements.

The following information must not be uploaded to external AI services without appropriate authorization and safeguards:

• Unpublished experimental datasets or confidential laboratory records.
• Proprietary chemical formulas, processes, or molecular designs.
• Patent-sensitive findings and undisclosed inventions.
• Restricted industrial research or sponsor-provided information.
• Confidential chemical synthesis protocols or protected research methods.
• Identifiable human biological or clinical research information.
• Confidential research collaborations or restricted institutional documents.
• Unpublished manuscripts and private editorial correspondence.

Figures, chemical structures, graphs, spectra, chromatograms, microscopy images, molecular representations, and other visual materials must accurately represent the research methods and findings described in the manuscript.

Authors must observe the following requirements:

• Experimental Images: AI must not generate fictitious laboratory photographs, microscopy images, or experimental documentation and present them as authentic data.
• Instrumental Results: AI-generated analytical patterns must not be represented as actual instrument measurements.
• Chemical Structures: Molecular formulas, chemical structures, stereochemistry, and reaction schemes must be verified for scientific accuracy.
• Computational Visualizations: Visualizations derived from computational research must be clearly identified and supported by the documented methodology.
• Graphical Illustrations: AI-assisted illustrative content, where used, must not misrepresent experimental findings and must comply with applicable disclosure and intellectual property requirements.
• Image Integrity: Scientific images must not be altered in ways that conceal, fabricate, or distort research evidence.

Where synthetic data, simulated spectra, predicted molecular structures, or AI-generated visualizations constitute part of a valid research methodology, they must be clearly identified as computational or simulated outputs rather than experimental observations.

Peer reviewers must conduct evaluations independently, objectively, and confidentially using their own scientific expertise.

Reviewers must not:

• Upload unpublished manuscripts, supplementary data, figures, or reviewer reports to external AI systems without explicit editorial permission and adequate confidentiality safeguards.
• Use AI-generated evaluations as substitutes for independent scientific judgment.
• Allow AI tools to independently determine the reliability or acceptability of research.
• Disclose unpublished chemical structures, experimental methods, proprietary findings, or other confidential manuscript information.
• Use confidential information obtained through peer review for personal, academic, or commercial advantage.

Reviewers who consider using AI tools for review-related assistance must first obtain appropriate editorial authorization. Any permitted AI assistance must be disclosed to the journal, and the reviewer remains responsible for independently verifying the evaluation.

Editors and Editorial Board members must maintain editorial independence, manuscript confidentiality, and responsibility for decisions affecting scholarly publication.

The following principles apply:

• AI systems must not independently make decisions to accept, revise, or reject manuscripts.
• Final editorial decisions remain the responsibility of the Editor-in-Chief or appropriately authorized human editors.
• Unpublished manuscripts, reviewer reports, confidential author correspondence, and restricted editorial records must not be disclosed to external AI services without appropriate permission and safeguards.
• AI-assisted tools used for authorized editorial support, such as technical formatting checks, metadata consistency, or similarity assessment, must remain subject to human verification.
• AI-assisted outputs must not be treated as definitive evidence of plagiarism, research misconduct, or unreliable findings.
• Editors must handle suspected misuse of AI fairly and in accordance with the journal's research-integrity procedures.

Editorial personnel remain responsible for the fairness, accuracy, confidentiality, and transparency of the publication process.

Suspected violations of this policy may be evaluated under Jurnal Kimia VALENSI's Publication Ethics, Allegations of Research Misconduct Policy, and relevant corrective-action procedures.

Depending on the seriousness of the concern, available evidence, and implications for scientific reliability, editorial actions may include:

1. Requesting clarification concerning AI usage.
2. Requiring the submission of an accurate AI-use declaration.
3. Requesting revision or independent verification of affected manuscript content.
4. Examining original experimental data or computational documentation where appropriate.
5. Conducting additional scientific or research-integrity assessment.
6. Temporarily suspending editorial processing during investigation.
7. Rejecting manuscripts when serious violations are substantiated.
8. Consulting relevant research institutions or independent experts.
9. Issuing a correction, Expression of Concern, or retraction after publication when justified.

Editorial action must be proportionate to the evidence and the effect of the violation on research originality, ethics, and reliability. A minor omission in an AI-use declaration does not automatically justify rejection or retraction.

Jurnal Kimia VALENSI may periodically review and update this policy in response to developments in artificial intelligence, computational chemistry, scientific publishing, data protection, intellectual property, and publication-ethics standards. Any updates should remain consistent with the journal's other editorial policies.

Jurnal Kimia VALENSI supports the responsible development and application of artificial intelligence in chemical science while protecting the authenticity of experimental evidence, reliability of computational results, independence of scholarly interpretation, confidentiality of research information, and accountability of human researchers and editorial personnel.

Questions regarding AI-assisted manuscript preparation, AI disclosure, research data confidentiality, computational methodology, or suspected violations of this policy may be directed to the Jurnal Kimia VALENSI Editorial Office.