About the Journal

The International Journal of Applied Methods in Electronics and Computers (IJAMEC) is a peer-reviewed, open-access journal dedicated to publishing high-quality research in the fields of electronics and computer science. Established in 2013, the journal provides a platform for interdisciplinary studies and innovative applications addressing real-world challenges in these dynamic fields.

The journal welcomes research papers in all significant areas of electronics and computers that have practical applications in scientific problem-solving. It allows authors to retain unrestricted copyright and publishing rights.  Open Access under the CC-BY license. IJAMEC does not impose any fees for article submissions or processing. It is free of charge.

  • ISSN: 3023-4409
  • DOI Prefix: 10.58190/ijamec
  • Frequency: Quarterly

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Announcements

International Journal of Applied Methods in Electronics and Computers is now indexed in the ICI Journals Master List for 2024

12-09-2025

We are thrilled to announce that the International Journal of Applied Methods in Electronics and Computers (ISSN: 3023-4409) has successfully passed the evaluation process and is now indexed in the ICI Journals Master List for 2024. Furthermore, the journal has been awarded an Index Copernicus Value (ICV) of 100.00 for 2024. 

Read more about International Journal of Applied Methods in Electronics and Computers is now indexed in the ICI Journals Master List for 2024

Current Issue

Vol. 14 No. 2 (2026)
Published: 30-06-2026

Research Articles

  • Analysis of Potato Diseases Using Image Processing Methods for Detection

    Muhammed Ali Akçay, Ibrahim Demirci , Yavuz Selim Taspinar
    59-69
    DOI: https://doi.org/10.58190/ijamec.2026.170
  • Performance Analysis of Machine Learning Algorithms on Wisconsin Diagnostic Breast Cancer Data Set Enriched with Data Augmentation Technique

    Ayça Acet, Abdullah Erhan Akkaya
    70-80
    DOI: https://doi.org/10.58190/ijamec.2026.171
  • An Offline-First Mobile Reporting System for Digital One Health Surveillance in Resource-Constrained Settings

    Edoghogho Olaye, Daniel Obuh
    81-88
    DOI: https://doi.org/10.58190/ijamec.2026.172
  • Comparative Evaluation of Machine Learning Algorithms for Raisin Variety Classification Based on Morphological Features

    Hüseyin Bulduk, Kadir SABANCI
    89-101
    DOI: https://doi.org/10.58190/ijamec.2026.173
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