The Journal of Applied Technology and Innovation (JATI), e-ISSN: 2600-7304, is an electronic, open access, peer-reviewed journal that publishes original research articles on novel theories, methods, and applications in the fields of electrical, electronics, mechatronics, telecommunication, computer, information technology, and software engineering. JATI follows a rigorous peer-review process, with article evaluations typically completed within four (4) weeks, and accepted manuscripts published in the forthcoming issue upon receipt of the final version. The journal publishes four (4) issues per year. JATI is published by the Asia Pacific University of Technology & Innovation (APU) through its Strategic Research Institute (SRI).

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Current Areas of Interest

Computer Science and Advanced Data Analytics Digital Transformation and Smart Systems Educational Technology and Learning Innovation Emerging Technologies and Digital Innovation Engineering Applications and Technological Solutions FinTech, Blockchain and Business Technology Green Technologies and Sustainable Engineering Nanotechnology and Advanced Materials Petroleum Engineering and Energy Technologies Smart Cities, Infrastructure and Ethical Technology Use

Current Issue

Vol. 9 No. 4 (2025)
View Vol. 9 No. 4 (2025)

Addressing the dynamic intersection of technological innovation and societal well-being, this published issue presents multidisciplinary research spanning energy sustainability, digital security, environmental impact, and intelligent healthcare systems. Featured studies examine mitigation techniques for solar grid integration through hybrid energy storage and Time-of-Use pricing, as well as cybersecurity awareness among university students. The issue further explores the climate implications of offshore oil and gas exploration, alongside emerging challenges and opportunities associated with IoT adoption within Malaysia’s digital economy. In addition, contributions highlight advances in artificial intelligence for MRI-based brain tumor detection and assess the impact of mindfulness training on academic performance among students with special needs.

 

 

Published: 2025-12-01

Original Research

Review Article

  • Exploration of Offshore Oil and Gas Onshore Climate Alterations and Implication

    DOI : 10.65136/jati.v9i4.33
    Husna Aini Swarno (1), Nurnida Elmira Othman (2), Fadhilah Mohd Sakri (3), Fatin Ayuni Mohd Suhaimi (4), Wong Siew Fan (5), Ahmad Faiz Mohammad (6)
    (1) School of Engineering, Asia Pacific University of Technology & Innovation, Kuala Lumpur , Malaysia ,
    (2) School of Mechanical Engineering, College of Engineering Universiti Teknologi MARA, Selangor, Malaysia ,
    (3) School of Engineering, Asia Pacific University of Technology & Innovation, Kuala Lumpur , Maldives ,
    (4) University Kuala Lumpur Malaysian Institute of Aviation Technology, Selangor, Malaysia ,
    (5) School of Engineering, Asia Pacific University of Technology & Innovation, Kuala Lumpur, Malaysia ,
    (6) Malaysia-Japan International Institute of Technology, University Teknologi Malaysia, Kuala Lumpur, Malaysia
    33-43
    Abstract : 231
    PDF : 122

  • IoT Challenges and Opportunities in Malaysia’s Digital Economy

    DOI : 10.65136/jati.v9i4.34
    Kamalanathan Shanmugam (1), Naresh Kumar Appadurai (2), Lau Yong Zheng (3), Subasree Ramish (4), Ramana Sarathy (5), Tulasi Appalasamy (6)
    (1) Asia Pacific University of Technology & Innovation Technology, Kuala Lumpur, Malaysia ,
    (2) Asia Pacific University of Technology & Innovation Technology, Kuala Lumpur, Malaysia ,
    (3) KG College of Arts and Science, Coimbatore, Tamil Nadu, India ,
    (4) KG College of Arts and Science, Coimbatore, Tamil Nadu, India ,
    (5) KG College of Arts and Science, Coimbatore, Tamil Nadu, India ,
    (6) Asia Pacific University of Technology & Innovation Technology, Kuala Lumpur, Malaysia
    44-52
    Abstract : 239
    PDF : 140
  • Artificial Intelligence-Based Detection of Brain Tumor with MRI Dataset

    State-of-the-Art Review and Future Directions in Artificial Intelligence-Based Detection of Brain Tumors Using MRI Datasets

    DOI : 10.65136/jati.v9i4.35
    Kohinur Parvin (1), Mohammad Rashed Hasan Polas (2), Onome Bendalene Irikefe (3)
    (1) Department of Computer Science and Engineering, Netrokona University, Netrokona, Bangladesh ,
    (2) Department of Business Administration, Sonargaon University, Dhaka, Bangladesh ,
    (3) School of Medicine, St. George’s University, University Centre, Grenada, West Indies, Grenada
    53-73
    Abstract : 556
    PDF : 134

Case Study

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