About the Journal

Advanced in Artificial Intelligence and Machine Learning (AAIML) is a peer-reviewed, open-access scholarly journal dedicated to publishing high-quality original research papers, review articles, and case studies in the fields of artificial intelligence (AI) and machine learning (ML). The journal aims to advance theoretical foundations, innovative methodologies, and real-world applications of intelligent systems that contribute to technological and scientific progress.

AAIML serves as an interdisciplinary academic platform for academics, researchers, and practitioners to exchange ideas, foster collaboration, and disseminate cutting-edge research findings. The journal covers a broad range of topics, including deep learning, natural language processing, computer vision, robotics, data analytics, and intelligent decision support systems, reflecting the rapidly evolving landscape of AI and ML research.

By encouraging global scholarly contributions, Advanced in Artificial Intelligence and Machine Learning (AAIML) seeks to promote the ethical, responsible, and sustainable development of artificial intelligence and machine learning technologies. The journal aims to bridge theory and practice by supporting research that delivers meaningful technological innovation and positive societal impact at local, national, and global levels.

Journal Information

  • ISSN (Electronic): 2656-2448

  • Publication Frequency: Biannual (2 issues per year)

  • Issue Schedule: December and June

  • Mode of Publication: Online

  • Language of Publication: English

  • Submission Email: admin@goodwoodpub.com

  • Keywords: Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Data Analytics, Intelligent Systems.

Publication Frequency

Advanced in Artificial Intelligence and Machine Learning (AAIML) is published biannual, with two regular issues released annually in December and June.

Language Policy

AAIML requires that all manuscripts be written in English. Authors are encouraged to use clear, concise, and academically appropriate language, with proper grammar and spelling to ensure clarity and international readability.

Types of Published Articles

AAIML publishes peer-reviewed scholarly manuscripts that make significant contributions to both academic literature and professional practice in the fields of artificial intelligence (AI) and machine learning (ML). The journal accepts the following types of submissions:

1. Research Articles

Research articles present original theoretical or empirical studies demonstrating methodological rigor, analytical depth, and clear contributions to academic literature and/or professional practice. Submissions employing quantitative, qualitative, mixed-methods, or replication approaches are welcomed.

2. Review Articles

Review articles provide a systematic and critical synthesis of existing literature on topics relevant to the journal’s scope. These articles should identify conceptual, methodological, or empirical gaps and offer clear directions for future research.

All published articles must comply with ethical research and publication standards and are subject to a double-blind peer-review process.

Publisher

AAIML is published by Goodwood Publishing, an Indonesian academic publisher committed to disseminating high-quality and impactful scholarly research to the global academic community.

Plagiarism Screening

All submitted manuscripts are screened for plagiarism using professional plagiarism detection software to ensure originality and compliance with academic integrity standards. The software that can be use for screening plagiarism are