Journal of Statistics and Data Analytics

AI Tools Usage Policy

AI Usage Summary: Journal of Statistics and Data Analytics (JSDA) recognizes that artificial intelligence, machine learning, and generative AI tools are increasingly used in research, data analysis, programming, visualization, and scholarly writing. The journal permits responsible and transparent use of AI-assisted tools, provided that human authors remain fully accountable for the accuracy, originality, methodological validity, ethical compliance, and integrity of the submitted work. AI systems cannot be listed as authors, co-authors, reviewers, editors, or responsible scholarly contributors.

This policy establishes the principles governing the use of artificial intelligence and AI-assisted technologies in manuscripts submitted to JSDA. The policy seeks to promote responsible innovation while protecting research integrity, authorship accountability, data confidentiality, statistical validity, and transparency.

Authors remain fully responsible for all content submitted to JSDA, including content created, modified, suggested, or assisted by artificial intelligence tools. Authors must independently verify all:

• statistical results;
• mathematical derivations;
• computer code;
• citations and references;
• data descriptions;
• analytical interpretations;
• tables and figures;
• conclusions;
• factual statements.

Artificial intelligence systems and generative AI tools cannot be credited as authors or co-authors. Authorship requires human responsibility for scholarly decisions, accuracy, integrity, ethical compliance, conflict-of-interest disclosure, and accountability for the published work. These responsibilities cannot be assigned to an AI system.

When AI tools are used to assist with statistical modeling, model selection, data preprocessing, feature engineering, classification, clustering, forecasting, optimization, or other analytical procedures, authors must independently verify the scientific validity of the methodology. Authors remain responsible for:

• choosing appropriate statistical methods;
• evaluating model assumptions;
• checking analytical calculations;
• validating model performance;
• identifying potential data leakage;
• evaluating overfitting;
• interpreting uncertainty;
• assessing limitations;
• ensuring conclusions are supported by the data.

AI-generated or AI-assisted code may be used, but authors must independently review, test, validate, and document its behavior. Authors must not assume that AI-generated code is statistically, mathematically, or computationally correct. Where code forms a substantial part of the methodology, authors should provide sufficient information to support reproducibility.

If artificial intelligence or generative models are used to create synthetic data, simulated observations, augmented datasets, or artificial samples, this must be clearly and transparently reported. Authors should explain:

• why synthetic data were used;
• how the data were generated;
• which AI or computational method was used;
• how synthetic and real data were distinguished;
• how data validity was assessed;
• limitations associated with the generated data.

AI tools must not be used to fabricate, falsify, or intentionally misrepresent research content. Prohibited practices include:

• fabricating research data;
• creating fictitious participants or observations;
• generating non-existent references or DOIs;
• fabricating statistical results;
• inventing experimental procedures;
• manipulating results to support a preferred conclusion;
• disguising plagiarism;
• creating deceptive figures or data visualizations;
• fabricating peer-review reports;
• impersonating authors, reviewers, editors, or institutions.

Authors must independently verify every citation and bibliographic reference included in the manuscript. AI tools may generate incorrect, incomplete, or non-existent references. Submission of fabricated or unverifiable citations remains the responsibility of the authors and may result in editorial action.

Authors should disclose the substantive use of generative AI or AI-assisted technologies when such tools materially contributed to:

• data generation;
• data preprocessing;
• statistical analysis;
• computer programming;
• model development;
• research interpretation;
• figure generation;
• substantial manuscript content.

The disclosure should, where relevant, identify the tool, its role, and the manner in which the generated output was verified by the authors.

Authors may use a statement such as the following, adapted to the actual use:

Use of artificial intelligence does not remove the authors' responsibility to ensure originality. Authors must verify that AI-assisted content does not reproduce copyrighted, published, or unpublished material without proper attribution. AI tools must not be used to conceal plagiarism through automated paraphrasing or text transformation.

Authors are responsible for ensuring that AI-assisted content does not infringe copyright, licensing, privacy, confidentiality, or other intellectual-property rights. Materials created with AI assistance must still comply with JSDA's Copyright and License Policy.

Authors should not upload confidential, restricted, personally identifiable, proprietary, or otherwise sensitive research data to external AI systems unless they have appropriate authorization and the use complies with applicable ethical, privacy, legal, and institutional requirements.

Figures, graphs, charts, and data visualizations produced with AI assistance must accurately reflect the underlying data. AI-generated visual content must not alter, fabricate, or exaggerate scientific evidence. Where AI contributes materially to the creation of a figure, authors should disclose the relevant use when appropriate.

Peer reviewers are responsible for maintaining the confidentiality of manuscripts and review materials. Reviewers should not upload manuscripts, unpublished data, figures, methods, or other confidential material to external generative AI systems when doing so could compromise confidentiality, privacy, copyright, or research integrity.

Reviewers remain personally responsible for the intellectual content and accuracy of their review reports. AI-generated review reports must not replace the reviewer's own scholarly assessment.

Editors and editorial staff must protect confidential manuscript information. Submitted manuscripts, review reports, author correspondence, and unpublished research materials should not be uploaded to external generative AI systems when confidentiality and data protection cannot be appropriately assured. Editorial decisions must remain the responsibility of qualified human editors.

Results from automated AI-content detection tools, when used, should not be treated as conclusive evidence of inappropriate AI use. Editorial assessment should consider the manuscript, available evidence, author explanations, and the nature of the suspected issue.

Inappropriate use of AI may be treated as a research or publication-ethics concern when it results in fabrication, falsification, plagiarism, misrepresentation, breach of confidentiality, copyright infringement, or other serious misconduct. Such cases may be handled under the journal's Publication Ethics and Retraction, Correction and Withdrawal Policy .

Responsible AI, Human Accountability

Journal of Statistics and Data Analytics supports responsible innovation in the use of artificial intelligence for statistical, computational, and data-driven research. AI may assist researchers and authors, but it does not replace human scholarly judgment, scientific responsibility, ethical accountability, or methodological verification. The integrity of all research published in JSDA ultimately remains the responsibility of human authors, reviewers, and editors.

Journal of Statistics and Data Analytics
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E-mail: jsda@gammabeta.id

Journal of Statistics and Data Analytics
Statistics • Data • Analytics

Published by PT. Gammabeta Edu and Tech