JTAM (Jurnal Teori dan Aplikasi Matematika)

Aims & Scope

JTAM (Jurnal Teori dan Aplikasi Matematika)publishes high-quality, peer-reviewed research that bridgestheoretical mathematics and interdisciplinary applications. The journal emphasizes the integration ofcomputation, modeling, educational innovation, and cultural perspectivesto advance mathematical understanding and its role insustainable development, digital transformation, and inclusive scientific literacyacross global and local contexts.(Jurnal Teori dan Aplikasi Matematika)focuses on the following research areas:Computational and Applied Mathematics. This area covers original research on mathematical modeling, numerical methods, simulation, and computational analysis for solving real-world problems. It includes applied mathematics studies addressing complex systems in physics, engineering, finance, epidemiology, environmental science, and socio-technical systems. Topics include numerical optimization, dynamical systems, computational fluid dynamics, inverse problems, and simulation-based modeling that establish strong links between mathematical theory and practical applications. Emphasis is given to research contributing to algorithmic innovation, computational efficiency, and multidisciplinary modeling frameworks.Mathematical Foundations, Modeling, and Analytical Approaches in Data Science, Artificial Intelligence, and Machine Learning. This focus highlights the mathematical and analytical foundations of data-driven technologies. It welcomes studies on the formulation, analysis, and validation of algorithms, hybrid intelligent systems, uncertainty modeling (fuzzy, stochastic, or probabilistic), and optimization theory in AI and machine learning contexts. Particular attention is given to works that connect mathematical rigor with AI innovation, such as explainable AI (XAI), mathematical interpretability of neural models, and analytical guarantees of learning algorithms. Applications include healthcare, climate prediction, economics, cybersecurity, and education.S

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Source: OpenAlex · Each year’s green bar = citations earned by that year’s papers, counted to date — so recent years look lower simply because their papers haven’t had time to be cited yet.

Subject Classification