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All Journal Voice Of Informatics E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi IT (INFORMATIC TECHNIQUE) JOURNAL Indonesian Journal of Electrical Engineering and Computer Science Majalah Ilmiah UPI YPTK INFOSYS (INFORMATION SYSTEM) JOURNAL Indonesian Journal of Contemporary Multidisciplinary Research
Edy Victor Haryanto
Universitas Potensi Utama
Aerospace Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Social Sciences

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Introduction to Image-Based Computer Vision Applications in Modern Medical Practice Rika Rosnelly; Bob Subhan Riza; Edy Victor Haryanto; Wahyu Saptha Negoro; Iwan Fitrianto Rahmad; Vidi Agung Fragastia; Annisa Ashari
Majalah Ilmiah UPI YPTK Vol. 33 (2026) No. 1
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jmi.v33i1.224

Abstract

The development of Artificial Intelligence (AI)—specifically image-based computer vision—has significantly contributed to modern medical practice by enabling more accurate and efficient medical image analysis. However, understanding and practical skills regarding the implementation of computer vision within community and educational settings remain relatively limited. This community service initiative aimed to enhance participants' conceptual understanding and foundational skills in applying image-based computer vision to medical contexts through a hands-on learning approach. The program was conducted via an integrated workshop that combined theoretical instruction with practical exercises using the cloud-based platform Google Colab. Evaluation was carried out using pre- and post-tests alongside practical assessments. Results showed an increase in participants' understanding, with the average score rising from 54.2 to 82.6 (a 52.4% improvement). Notably, 85% of participants were able to execute image processing modules independently, and 88% successfully completed the practical case study. Participant satisfaction reached a score of 4.6 out of 5. This initiative contributes to improving technological literacy and bridging the gap between conceptual understanding and practical competence in the application of AI within the healthcare sector.
Co-Authors Annisa Ashari Arselan Ashraf Asbon Hendra Azhar Bob Subhan Riza Daifira Daifira Ega Refredo Banurea Fragastia, Vidi Agung Frinto Tambunan Habi Puja Grasandy Ika Sartika Ika Sartika Ivy Lazuli Iwan Fitrianto Rahmad Lahmudin Sipahutar M. Barkah Akbar Mara Akhir Putra Bungsu Muhammad Fauzi Muhammad Habib Muhammad Siddik Negoro, Wahyu Saptha Nita Sari Br Sembiring Noprita Elisabeth Sianturi Puji Utari Rahmat Rizal Ratih Adinda Destari Rika Rosnelly Sinaga, Mikha Dayan Teddy Surya Gunawan Zuriati Janin