About the Journal

Journal of Machine Learning and Knowledge Systems (JMLKS) is an peer-reviewed and open-access scientific journal dedicated to publishing high-quality original research articles, review papers, and technical notes in the fields of Artificial Intelligence (AI), Machine Learning, and intelligent computing. All submitted manuscripts undergo a rigorous double-blind peer-review process to ensure scientific quality, originality, technical soundness, and relevance to the journal's scope. JMLKS provides a global platform for researchers, academics, and practitioners to disseminate novel theories, methodologies, algorithms, computational models, and practical applications that advance intelligent technologies.

The journal welcomes interdisciplinary research covering, but not limited to, machine learning, deep learning, generative AI, knowledge representation and reasoning, knowledge graphs, computational intelligence, explainable AI, trustworthy AI, intelligent decision support systems, computer vision, natural language processing, data mining, reinforcement learning, multi-agent systems, optimization, human-centered AI, and AI applications in healthcare, education, industry, agriculture, transportation, cybersecurity, smart cities, and environmental sustainability. The journal aims to foster scientific innovation by promoting the integration of data-driven and knowledge-driven intelligence to develop robust, interpretable, and scalable AI solutions for addressing complex real-world challenges. Through a rigorous peer-review process, adherence to high publication ethics, and international collaboration, JMLKS seeks to contribute to the advancement of next-generation intelligent systems and the global Artificial Intelligence research community.

Focus and Scope         :

  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Knowledge-Based Systems
  • Knowledge Representation and Reasoning
  • Knowledge Graphs
  • Ontology Engineering
  • Expert Systems
  • Intelligent Systems
  • Data Mining and Knowledge Discovery
  • Explainable Artificial Intelligence (XAI)
  • Trustworthy and Responsible AI
  • Natural Language Processing
  • Computer Vision and Pattern Recognition
  • Reinforcement Learning
  • Evolutionary Computation and Swarm Intelligence
  • Intelligent Decision Support Systems
  • Semantic Web Technologies
  • Information Retrieval
  • Multi-Agent Systems
  • Soft Computing and Computational Intelligence
  • AI Applications in Healthcare, Education, Agriculture, Industry, Finance, Smart Cities, Environment, and Social Sciences

Frekuensi Terbitan     : Biannually (twice a year), with issues released in June and December.