About the Journal

Indonesian Journal of Machine Learning and Intelligent Systems (IJMLIS, Indones. J. Mach. Learn. Intell. Syst., e-ISSN 3164-2756) is a peer-reviewed international journal dedicated to advancing research on theoretical developments and practical implementations in the dynamic fields of machine learning, artificial intelligence, and intelligent systems, published by the Indonesian Artificial Neural Network Society (IdNNS). The IJMLIS journal aims to advance intelligent technologies and data-driven innovations while supporting the development of responsible, impactful AI solutions that contribute to scientific progress and societal benefit.

Anyone who would like to submit a manuscript is advised to read the aims and scope section and the author guidelines of this journal. All manuscripts must be submitted to the IJMLIS Editorial Office using the Online Submission Service at https://journal.idnns.org/index.php/ijmlis/submission.

Abbreviation: Indones. J. Mach. Learn. Intell. Syst.
e-ISSN: 3164-2756 (online)
Editor-in-chief: Prof. Media Anugerah Ayu, Ph.D, SMIEEE | more info
Scope: Machine learning, artificial intelligence, intelligent systems | more info
Publication types: Original Research Articles, Review Articles | more info
Distribution: Open Access | more info
Peer-review: Blind review | more info
Frequency: Triannually (April, August, and December)
Indexing: Google Scholar| more info
Submission: Author guidelines, Submission process, Editorial team
Commencement: April 2026 | Current issue, More issues

Current Issue

Vol. 1 No. 1 (2026)
					View Vol. 1 No. 1 (2026)

The Indonesian Journal of Machine Learning and Intelligent Systems (IJMLIS) is a scholarly publication dedicated to advancing research in the dynamic fields of machine learning and intelligent systems. Published triannually in January, May, and September by the iDNNS association, the journal provides a consistent and timely forum for researchers, academics, and practitioners to disseminate their latest findings. As a publication managed by iDNNS, IJMLIS aims to foster a collaborative community, focusing on high-quality, peer-reviewed content that explores both theoretical developments and practical applications within these rapidly evolving technological domains.

Published: 2026-01-31
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