Matematika

Scope & Guideline

Cultivating Insightful Mathematics for All

Introduction

Welcome to the Matematika information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of Matematika, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN0127-8274
PublisherPENERBIT UTM PRESS
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationMATEMATIKA / Matematika
Frequency2 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressPENERBIT UTM PRESS, SKUDAI, JOHOR 81310, MALAYSIA

Aims and Scopes

The journal 'Matematika' focuses on a wide array of mathematical applications, methodologies, and theories. Its core areas reflect a commitment to advancing mathematical knowledge and its practical applications across various fields.
  1. Applied Mathematics:
    The journal emphasizes applied mathematics, particularly in modeling real-world phenomena such as environmental issues, engineering processes, and economic models.
  2. Computational Methods:
    There is a strong focus on computational techniques, including numerical methods, simulations, and algorithm development for solving complex mathematical problems.
  3. Statistical Analysis and Forecasting:
    Many publications involve statistical modeling and forecasting methods, showcasing the journal's dedication to data-driven decision-making across various domains.
  4. Interdisciplinary Research:
    The journal promotes interdisciplinary studies, integrating mathematics with fields such as biology, economics, and engineering to address complex challenges.
  5. Mathematical Modeling:
    A consistent theme is the development and analysis of mathematical models that describe dynamic systems, particularly in health, finance, and environmental studies.
Recent years have seen the emergence of several themes within 'Matematika' that reflect current trends in mathematics and its applications. These themes indicate a shift towards addressing contemporary challenges through innovative mathematical approaches.
  1. Data Science and Machine Learning:
    An increasing focus on data science and machine learning applications highlights the relevance of mathematical techniques in analyzing large datasets and making predictions.
  2. Health and Epidemiological Modeling:
    The rise in publications related to health models, particularly in the context of infectious diseases like COVID-19 and tuberculosis, underscores the importance of mathematics in public health.
  3. Environmental Mathematics:
    There is a growing trend towards environmental applications, including modeling pollution, climate change, and resource management, reflecting societal concerns.
  4. Cryptocurrency and Financial Modeling:
    Emerging research on cryptocurrency pricing and financial forecasting indicates a shift towards applied mathematics in finance, showcasing the intersection of technology and economics.
  5. Complex Systems and Network Analysis:
    Recent papers signal an interest in the mathematical analysis of complex systems and networks, particularly in understanding interactions within biological and social systems.

Declining or Waning

While 'Matematika' has maintained a broad focus, certain themes have shown signs of decline in recent years. This may reflect shifts in research priorities or emerging areas of interest.
  1. Theoretical Mathematics:
    There appears to be a waning interest in purely theoretical mathematics, with fewer papers focusing solely on abstract mathematical theories without practical applications.
  2. Traditional Statistical Techniques:
    The journal has seen a decline in the publication of traditional statistical methods, possibly due to the rise of more advanced and hybrid modeling approaches.
  3. Basic Mathematical Education Research:
    Research focused on basic mathematical education and pedagogy has decreased, suggesting a shift towards more applied or technical studies.
  4. Static Models:
    There is a noticeable reduction in studies involving static mathematical models, as the trend moves towards dynamic and time-dependent modeling approaches.

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