Artificial Intelligence (AI) Policy

Keteg: Jurnal Pengetahuan, Pemikiran dan Kajian Tentang Bunyi acknowledges the rapid advancement and increasing use of Artificial Intelligence (AI) tools, including Large Language Models (LLMs) such as ChatGPT, Claude, and Gemini, in academic research and writing. To maintain the highest standards of scientific integrity, we strictly adhere to the guidelines set forth by the Committee on Publication Ethics (COPE) regarding AI authorship and usage.

  1. Authorship and Accountability
    AI tools and LLMs cannot be credited as an author, co-author, or corresponding author on any submitted manuscript. AI systems cannot take legal, ethical, or intellectual responsibility for the published work, nor can they assert the presence or absence of conflicts of interest. Human authors hold full and absolute responsibility for the accuracy, originality, and integrity of the entire manuscript, including any AI-generated content. Authors must carefully review AI outputs to ensure there are no fabricated data, biased statements, or factual hallucinations.
  2. Transparency and Disclosure
    Authors who use AI tools to assist in the writing process (e.g., for language polishing, translation, or structural editing), data collection, or data analysis must explicitly disclose this usage in the manuscript. This disclosure must be placed in the Methods section or a dedicated Acknowledgments section, clearly stating the name of the AI tool, its version, and specifically how it was utilized.
  3. Image and Media Generation
    The use of generative AI to create or manipulate images, musical notations, or figures is strictly prohibited unless the AI-generated media is the direct subject of the research (e.g., a study on AI-generated music). This exception must be clearly justified in the methodology. All visual and audio data must represent genuine, human-led research or creative processes.
  4. Confidentiality in Peer Review
    Peer-reviewers and editors are strictly prohibited from uploading submitted manuscripts into public AI tools or LLMs to assist in evaluating the paper or generating review reports. Doing so is a direct violation of the journal's double-blind peer-review confidentiality policy, as public AI tools may retain, learn from, and potentially leak the uploaded unpublished data.