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 journal is committed to maintaining high ethical standards in scholarly publishing and adheres to established guidelines for research integrity and publication ethics. The IJMLIS provides a scientific platform for researchers, academics, policymakers, and industry practitioners to disseminate original findings, innovative methodologies, theoretical advancements, and practical applications of intelligent technologies across various domains. The journal welcomes original research articles and review papers that advance the understanding and practical deployment of intelligent systems across healthcare, finance, cybersecurity, smart cities, and industrial automation. IJMLIS focuses on the development and implementation of machine learning algorithms, data-driven intelligence, and intelligent computing systems that support decision-making, automation, and advanced analytics. The journal encourages interdisciplinary research integrating computer science, data science, artificial intelligence, robotics, and intelligent information systems. The scope of the journal includes, but is not limited to: Learning problems: Clustering, classification, regression, recognition, prediction, and prescription/recommendation; Artificial intelligence and learning methods: Supervised/unsupervised learning, reinforcement learning, ensemble methods, connectionist networks (deep learning), Bayesian networks, and evolutionary-based methods; Intelligent systems structure: intelligent agents, multi-agent systems, expert systems, and cognitive computing; Data and information processing: Data mining, information retrieval, pattern recognition, pattern visualization, image/video processing, voice recognition, and natural language processing (NLP); Applications: Computer vision, AI-powered robotics, intelligent control systems, IoT, cybersecurity and information assurance, financial modeling, bioinformatics, medical imaging, healthcare informatics, game playing, digital governance, and smart cities; System and theoretical analysis: Theoretical frameworks, performance evaluation, algorithm design, and computational complexity analysis; Emerging technologies: Sustainable/green IT, brain-machine interfaces, and human-centered AI