Publication Ethics and Malpractice Statement

1. General Statement

Transactions of the Indonesian Association for Computational Linguistics (TINACL) is committed to maintaining high standards of publication ethics, academic integrity, transparency, and responsible scholarly communication. The journal publishes original research in computational linguistics, natural language processing, speech and language technology, multilingual and cross-lingual processing, low-resource languages, language resources, language-centered artificial intelligence, and related fields.

TINACL follows internationally recognized principles of publication ethics and scholarly publishing best practices. The journal expects all parties involved in the publication process, including authors, editors, reviewers, and the publisher, to uphold ethical standards and avoid any form of academic misconduct.

Academic misconduct includes, but is not limited to, plagiarism, data fabrication, data falsification, duplicate publication, inappropriate authorship, citation manipulation, undeclared conflicts of interest, peer-review manipulation, and irresponsible use of artificial intelligence tools.

2. Duties and Responsibilities of Authors

2.1 Originality and Plagiarism

Authors must ensure that submitted manuscripts are original, unpublished, and not under consideration elsewhere. Any text, data, figures, tables, algorithms, software, linguistic resources, datasets, or other materials derived from previous works must be properly cited and acknowledged.

Plagiarism in any form is unacceptable. This includes direct copying, paraphrasing without proper attribution, self-plagiarism, duplicate publication, and the use of unattributed AI-generated text, images, code, or data.

TINACL may use plagiarism detection tools and editorial screening to identify possible overlap with published or unpublished materials. Manuscripts with substantial plagiarism or unethical similarity may be rejected before peer review or retracted after publication.

2.2 Data Accuracy, Integrity, and Reproducibility

Authors are responsible for the accuracy and integrity of all data, methods, experiments, results, analyses, and conclusions presented in their manuscripts.

For empirical studies, authors should clearly describe the datasets, language resources, models, experimental settings, evaluation metrics, annotation procedures, prompts where applicable, hyperparameters, baselines, and statistical procedures used in the study.

When possible, authors are encouraged to provide access to datasets, corpora, source code, annotation guidelines, prompts, trained models, evaluation scripts, or supplementary materials to support reproducibility and further research.

Authors must not fabricate, falsify, selectively omit, or manipulate data, annotations, images, experimental results, evaluation scores, linguistic examples, or qualitative findings.

2.3 Authorship and Contributorship

Authorship should be limited to individuals who have made a substantial scholarly contribution to the conception, design, implementation, data collection, annotation, analysis, interpretation, writing, or revision of the work.

All authors must approve the final version of the manuscript and agree to its submission. All authors are jointly responsible for the integrity of the work.

TINACL does not allow guest authorship, gift authorship, honorary authorship, or ghost authorship. Contributors who do not meet the criteria for authorship should be acknowledged in the Acknowledgements section with their permission.

2.4 Use of Artificial Intelligence Tools by Authors

TINACL allows the responsible use of AI-assisted tools, including language models, grammar checkers, translation tools, coding assistants, transcription tools, and image or figure-generation tools, provided that such use is transparent, ethical, and does not replace the authors' intellectual contribution.

Authors must not list AI tools, chatbots, language models, or other automated systems as authors or co-authors because such systems cannot take responsibility for the submitted work.

When AI tools are used in manuscript preparation, data analysis, coding, translation, annotation assistance, figure generation, literature screening, or other research-related processes, authors must disclose their use where it materially contributes to the work. The disclosure should include the name of the tool, version if available, purpose of use, and the sections or tasks where the tool was used.

Example AI-use disclosure:

The authors used [tool name] to assist with language editing and grammar improvement. The authors reviewed, verified, and take full responsibility for the final content of the manuscript.

For studies where AI systems, language models, or other computational tools are part of the research object or methodology, authors must provide sufficient information about model versions, prompts where applicable, parameters, datasets, evaluation settings, and limitations to support transparency and reproducibility.

Authors remain fully responsible for the accuracy, originality, validity, and ethical compliance of all submitted content, including content generated or assisted by AI tools.

2.5 Multiple, Duplicate, and Redundant Publication

Authors must not submit the same manuscript to more than one journal at the same time. Manuscripts that substantially overlap with previously published work by the same authors or others must clearly acknowledge and cite the earlier work.

If the manuscript is an extended version of a conference paper, preprint, thesis, dataset paper, workshop paper, or technical report, authors must disclose this information during submission and clearly explain the new scholarly contribution of the submitted manuscript.

2.6 Citation Ethics

Authors must cite relevant and reliable sources that directly support the manuscript. Citations should be used to acknowledge previous work, situate the research contribution, and support scholarly claims.

Authors must avoid excessive self-citation, irrelevant citation, coercive citation, citation manipulation, or citation practices intended primarily to increase citation metrics.

2.7 Conflicts of Interest

Authors must disclose any financial, institutional, professional, personal, or other relationships that could influence the research, interpretation, evaluation, or publication of the manuscript.

Examples of potential conflicts of interest include funding relationships, employment, consultancy, patents, commercial interests, institutional affiliations, close personal relationships, or academic competition.

Example statement:

The authors declare no conflict of interest.

2.8 Funding Disclosure

Authors must disclose all sources of financial support, grants, institutional funding, sponsorship, or other support related to the research.

Example statement:

This research received no external funding.

2.9 Human Participants, Personal Data, and Privacy

Research involving human participants, surveys, interviews, experiments, user studies, linguistic fieldwork, social media data, educational data, medical data, speech recordings, or other personal information must comply with applicable ethical standards, institutional requirements, and data protection regulations.

Authors must obtain appropriate consent where required, anonymize or de-identify personal data where necessary, and avoid publishing personally identifiable information unless explicit permission has been obtained.

For computational linguistics and NLP research, authors should exercise particular care when using datasets that may contain personal information, sensitive attributes, private communications, copyrighted content, offensive material, or other potentially harmful data.

2.10 Dataset, Language Resource, Software, and Model Ethics

Authors submitting research involving datasets, corpora, treebanks, lexicons, speech resources, annotation datasets, software, pretrained models, language models, or other computational resources must ensure that such materials are obtained and used lawfully and ethically.

Authors should clearly describe, where applicable, the source of datasets and language resources, licensing conditions, data collection procedures, preprocessing steps, annotation procedures, known biases, limitations, and relevant usage restrictions.

If a dataset, corpus, or model contains sensitive, harmful, biased, offensive, private, or restricted content, authors should explain how relevant risks were identified and mitigated.

For research involving generative AI, large language models, multilingual models, automated evaluation systems, or other language technologies, authors should report relevant limitations, potential bias, hallucination or factuality risks where applicable, evaluation uncertainty, and responsible-use considerations.

Research involving low-resource, minority, Indigenous, endangered, or otherwise underrepresented languages should give appropriate consideration to ethical data collection, community interests, consent, attribution, representation, and responsible reuse of linguistic resources where applicable.

3. Duties and Responsibilities of Editors

3.1 Editorial Independence

Editors are responsible for making publication decisions based on the scholarly quality, originality, methodological soundness, relevance, clarity, and ethical integrity of the manuscript.

Editorial decisions must not be influenced by the authors' nationality, ethnicity, gender, race, religion, political views, language, geographic location, institutional affiliation, seniority, or personal relationships.

3.2 Fair Peer Review

Editors must ensure that manuscripts are handled fairly, confidentially, and objectively. Manuscripts that pass the initial editorial screening will be sent for peer review by qualified reviewers with relevant expertise.

Reviewers should be selected based on their scholarly competence and suitability for evaluating the subject matter of the manuscript.

3.3 Confidentiality

Editors and editorial staff must keep all submitted manuscripts, reviewer comments, author responses, editorial communications, and other unpublished materials confidential.

Manuscript materials must not be shared or used for personal, professional, academic, or commercial advantage by editors, reviewers, or editorial staff.

3.4 Conflicts of Interest

Editors must recuse themselves from handling manuscripts where they have a conflict of interest. This includes manuscripts submitted by close collaborators, colleagues from the same institution, students, supervisors, family members, or individuals with whom the editor has a financial, professional, or personal relationship that could affect impartiality.

When a conflict of interest exists, the manuscript should be assigned to another appropriate editor.

3.5 Handling Misconduct

Editors are responsible for investigating suspected publication misconduct, including plagiarism, data fabrication, falsification, duplicate submission, authorship disputes, peer-review manipulation, citation manipulation, undeclared conflicts of interest, unethical data practices, and inappropriate or undisclosed use of AI tools.

If misconduct is confirmed, the journal may reject the manuscript, request corrections, publish an expression of concern, retract the article, notify relevant institutions, or take other appropriate editorial actions.

4. Duties and Responsibilities of Reviewers

4.1 Contribution to Editorial Decisions

Reviewers assist editors in evaluating the quality, originality, validity, clarity, methodological rigor, and relevance of submitted manuscripts.

Reviewer comments should help editors make informed editorial decisions and help authors improve the scholarly quality of their work.

4.2 Objectivity and Constructive Feedback

Reviews should be conducted objectively, respectfully, and constructively. Reviewers should provide clear scholarly reasons for their recommendations and avoid personal criticism of authors.

Reviewers should evaluate, where relevant, the manuscript's contribution, methodology, linguistic and computational analysis, literature coverage, data or resource quality, evaluation methodology, reproducibility, ethical issues, and suitability for TINACL.

4.3 Confidentiality

Reviewers must treat manuscripts as confidential documents. They must not share, discuss, reproduce, distribute, cite, or use unpublished manuscript content without permission from the editor.

4.4 Conflicts of Interest

Reviewers must decline a review invitation if they have a conflict of interest with the authors, institutions, funders, research topic, datasets, projects, or competing work that could compromise their objectivity.

4.5 Identification of Ethical Concerns

Reviewers should inform the editor if they suspect plagiarism, duplicate publication, data manipulation, inappropriate dataset use, image or figure manipulation, unethical research practices, inappropriate use of AI tools, or other forms of research or publication misconduct.

4.6 Use of AI Tools by Reviewers

Reviewers must not upload manuscripts, figures, datasets, tables, supplementary files, or other confidential review materials to external AI tools, chatbots, or third-party platforms unless explicitly permitted by the journal and confidentiality can be adequately guaranteed.

If reviewers use permitted AI-assisted tools for limited purposes such as language checking or organizing their own review notes, they remain fully responsible for the content, accuracy, confidentiality, independence, and integrity of their review.

AI-generated assessments must not replace the reviewer's own scholarly judgment.

5. Peer Review Process

TINACL applies a rigorous peer-review process to support the quality and integrity of published articles.

The standard editorial process includes:

1. Initial editorial screening: The editor checks whether the manuscript fits the journal's focus and scope, follows the author guidelines, and meets basic scholarly and ethical standards.

2. Plagiarism and ethics screening: The manuscript may be checked for similarity, plagiarism, duplicate publication, ethical issues, AI-use disclosure, conflicts of interest, and completeness of required statements.

3. Peer review: Manuscripts that pass the initial screening are sent to qualified reviewers with appropriate expertise.

4. Editorial decision: Based on reviewer comments and editorial evaluation, the decision may include accept, minor revision, major revision, resubmit for review, or reject.

5. Revision and author response: Authors are expected to address reviewer and editor comments carefully and revise the manuscript where appropriate. A detailed response to reviewers may be required.

6. Final decision: The editor makes the final publication decision based on the revised manuscript, reviewer recommendations, scholarly quality, and compliance with journal policies and ethical standards.

6. Research and Publication Misconduct

TINACL defines research and publication misconduct as any action that compromises the integrity, reliability, or transparency of scholarly publication.

This includes, but is not limited to:

• Plagiarism

• Self-plagiarism

• Data fabrication

• Data falsification

• Manipulation of datasets, annotations, images, or figures

• Duplicate submission

• Redundant publication

• Undeclared conflicts of interest

• Gift, guest, honorary, or ghost authorship

• Citation manipulation

• Peer-review manipulation

• Misuse of confidential information

• Unethical collection or use of language data

• Undisclosed or irresponsible use of AI tools

• Submission of manuscripts generated substantially by AI without meaningful human scholarly contribution

• Use of fake identities, fake reviewers, or fraudulent peer-review suggestions

When misconduct is suspected, TINACL will investigate the matter fairly and confidentially. Authors may be asked to provide explanations, raw data, source data, annotation records, documentation, ethics approval, consent documentation, or other supporting materials where relevant.

7. Corrections, Retractions, and Expressions of Concern

TINACL is committed to maintaining the integrity and reliability of the scholarly record.

7.1 Corrections

A correction may be published when an article contains an honest error that does not invalidate the overall findings, conclusions, or scholarly contribution of the work.

Corrections will be clearly identified and linked to the original publication where technically possible.

7.2 Retractions

An article may be retracted when there is clear evidence of unreliable findings, plagiarism, data fabrication, falsification, unethical research, duplicate publication, serious methodological or factual errors, fraudulent authorship or peer review, or other major misconduct.

Retraction notices will identify the affected article and explain the basis for the retraction while maintaining appropriate confidentiality and fairness.

7.3 Expressions of Concern

An expression of concern may be published when serious concerns have been raised about a publication but an investigation has not yet been completed or the available evidence remains inconclusive.

Corrections, retractions, and expressions of concern will be made available to readers and linked to the original article whenever possible.

8. Complaints and Appeals

Authors, reviewers, readers, or other parties may submit complaints or appeals regarding editorial decisions, publication ethics, the peer-review process, conflicts of interest, corrections, retractions, or suspected misconduct.

Complaints and appeals should be submitted to the TINACL editorial office through the journal's official contact channel.

The editorial team will review complaints and appeals fairly, confidentially, and in accordance with the journal's ethical standards. Where necessary, a case may be referred to the Editor-in-Chief, editorial board, publisher, or an independent expert.

Appeals against rejection decisions must provide clear scholarly reasons and should not be based solely on disagreement with reviewer comments.

9. Post-Publication Discussion

TINACL welcomes responsible and evidence-based post-publication discussion.

Readers, researchers, authors, or other members of the scholarly community who identify possible errors, ethical concerns, methodological problems, or other issues in a published article may contact the editorial office.

Where appropriate, the journal may investigate the concern and issue a correction, clarification, expression of concern, retraction, or other appropriate notice.

10. Open Access, Copyright, and Licensing

TINACL is an open-access journal. Published articles are freely available to readers without subscription barriers.

Authors retain copyright in their articles and grant the journal the right of first publication in accordance with the journal's copyright and licensing policy.

Unless otherwise stated, articles published by TINACL are distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0).

This license permits others to read, download, copy, distribute, print, search, link to, share, reproduce, and adapt published work, provided that appropriate credit is given to the original authors and publication source.

11. Publisher Responsibilities

The publisher, Indonesian Association for Computational Linguistics (INACL), supports the editorial independence of TINACL and is committed to ensuring that editorial decisions are based on scholarly merit, methodological quality, relevance, originality, and ethical standards.

The publisher supports the journal's publication infrastructure, scholarly communication activities, metadata quality, accessibility, long-term availability of published content, and ethical publication practices.

The publisher will not improperly interfere with editorial decisions and will cooperate with the editorial team in matters involving suspected misconduct, corrections, retractions, complaints, appeals, or other publication ethics issues.

Commercial interests, sponsorship, institutional relationships, or financial considerations must not improperly influence editorial decisions.

12. Archiving and Long-Term Access

TINACL is committed to maintaining long-term access to its published scholarly content.

The journal will make reasonable efforts to preserve article metadata, publication files, issue archives, supplementary materials where applicable, and related publication records.

TINACL may use recognized digital preservation services, institutional repositories, indexing services, archival networks, or other trusted preservation systems to support long-term accessibility.

Information concerning active participation in specific preservation services will be updated on the journal website when applicable.

13. Ethical Oversight for Computational Linguistics and Language Technology Research

Because TINACL publishes research involving computational linguistics, natural language processing, speech and language technologies, language resources, and artificial intelligence, authors should carefully consider the ethical implications of their research.

Authors are encouraged to discuss relevant risks and limitations, including where applicable:

• Bias, fairness, and linguistic representation

• Privacy and personal data protection

• Consent and responsible collection of linguistic or speech data

• Dataset and corpus licensing

• Copyright and intellectual property

• Representation of low-resource and underrepresented languages

• Harmful, toxic, offensive, or sensitive content

• Model hallucination and factual reliability

• Misuse potential of language technologies

• Annotation quality and data provenance

• Evaluation limitations and uncertainty

• Transparency and reproducibility

• Human and societal impacts

• Environmental or computational costs, where relevant

Manuscripts presenting datasets, corpora, models, prompts, software, language resources, or computational methods with potential ethical or misuse risks should describe relevant limitations, safeguards, restrictions, or responsible-use considerations where appropriate.

TINACL particularly encourages responsible research practices that support linguistic diversity, multilingualism, low-resource languages, reproducibility, and inclusive development of language technologies.

14. Contact for Publication Ethics

Questions, complaints, appeals, or reports of suspected publication misconduct should be directed to:

Editorial Office
Transactions of the Indonesian Association for Computational Linguistics (TINACL)
Indonesian Association for Computational Linguistics (INACL)
Website: https://acspub.id/index.php/tinacl

The official editorial email address should be provided on the journal's Contact page and used for publication ethics correspondence.