https://journalkeberlanjutan.com/index.php/jisdb/issue/feed 2025-09-12T12:38:08+07:00 Jasman Pardede jisdb@journalkeberlanjutan.com Open Journal Systems <p align="justify">The Journal of Information Systems, Digitization and Business (abbreviated as JISDB), published by <a href="https://ahu.go.id/sabh/perseroan/qrcode/?kode=NDAxOTA0MjQzMjIyMzgzN18wXzI0IEFwcmlsIDIwMTlfMjQgQXByaWwgMjAxOQ==&amp;sp=dp">PT Keberlanjutan Strategis Indonesia</a>, p-ISSN <a href="https://issn.brin.go.id/terbit/detail/20221116230678635" target="_blank" rel="noopener">2962-8849</a> and e-ISSN <a href="https://issn.brin.go.id/terbit/detail/20221220060405431" target="_blank" rel="noopener">2963-0819</a> . The International Journal of Information Systems, Digitization and Business published <em>four (4) issues per year</em> in November - January, February - April, May - July, August - October. Journal of Information Systems, Digitization and Business also uses the LOCKSS system to ensure a secure and permanent archive for the journal. The International Journal of Information Systems, Digitization and Business is focuses on publishing original research, communications, and notes as a result of original and high-quality research relating to information systems, Information Systems, Digitalization, and Business. Since 2022, Journal of Information Systems, Digitization and Business member of CrossRef, therefore each article will own a DOI (Digital Object Identifier) number <a href="https://search.crossref.org/?q=2962-8849&amp;from_ui=yes&amp;container-title=Journal+of+Information+Systems+Digitization+and+Business" target="_blank" rel="noopener">10.38142/jisdb</a>, <a href="https://orcid.org/0009-0002-5705-116X" target="_blank" rel="noopener">ORCID Connecting Research and Researchers</a> and other indexing see <a href="https://journalkeberlanjutan.com/index.php/jisdb/Abstract" target="_blank" rel="noopener">Abstract and Indexing</a></p> https://journalkeberlanjutan.com/index.php/jisdb/article/view/1624 2025-09-08T13:05:30+07:00 Nicholas RENALDO nicholasrenaldo@lecturer.pelitaindonesia.ac.id Wilda SUSANTI wilda@lecturer.pelitaindonesia.ac.id Rangga Rahmadian YULIENDI rangga@lecturer.pelitaindonesia.ac.id Yulvia Nora MARLIM yulvia.nora@lecturer.pelitaindonesia.ac.id Wahyu Joni KURNIAWAN wahyu.joni@lecturer.pelitaindonesia.ac.id Gusrio TENDRA gusrio.tendra@lecturer.pelitaindonesia.ac.id

<p>The rapid development of artificial intelligence (AI) has introduced significant innovations in healthcare, particularly through computer vision technologies. This study explores qualitative perspectives on the use of computer vision for external disease identification, focusing on its applications, benefits, challenges, and future potential. A thematic review of literature from 2015 to 2025 was conducted using peer-reviewed journals, policy reports, and case studies. The findings reveal that computer vision has been successfully applied in dermatology, ophthalmology, and oral health, with performance often comparable to or exceeding that of general practitioners. Mobile and cloud-based applications extend these innovations to community healthcare, enabling wider access and patient empowerment. However, limitations remain, including dataset biases, privacy concerns, and the need for ethical frameworks. The study concludes that computer vision offers transformative opportunities for early and accessible disease detection, but its success depends on interdisciplinary collaboration, equitable dataset development, and responsible integration into healthcare systems. Recommendations for future research include longitudinal validation, cross-cultural testing, and integration with multimodal health data.</p>

2025-02-28T00:00:00+07:00 Copyright (c) 2025 Nicholas RENALDO, Wilda SUSANTI , Rangga Rahmadian YULIENDI , Yulvia Nora MARLIM , Wahyu Joni KURNIAWAN, Gusrio TENDRA