Conferences Deep and Machine Learning in Artificial Intelligence about Diabetics for Student Indonesia-Thailand
DOI:
https://doi.org/10.65818/konektivitas.v1i1.26Keywords:
Artificial intelligence, Deep learning, Diabetes, International seminar, Machine learningAbstract
Background: The rapid advancement of artificial intelligence, particularly deep learning and machine learning, has transformed healthcare, education, and industry, yet many university students remain disconnected from applied understanding of these technologies, especially in addressing diabetes-related health challenges, creating an urgent need for inclusive learning initiatives. International seminars that combine academic expertise, interdisciplinary dialogue, and contextual examples offer a humanistic pathway to reduce anxiety, build confidence, and encourage students to participate actively in technological problem solving while fostering ethical sensitivity, social responsibility, and collaborative learning across cultural and institutional boundaries within higher education systems globally today and sustainably inclusive.
Aims: This community service activity aimed to enhance students’ conceptual and applied understanding of deep learning and machine learning in artificial intelligence through an international seminar focusing on diabetes-oriented healthcare applications.
Methods: The program employed an offline international seminar involving Indonesian and Thai speakers, interactive presentations, case studies, and two-way discussions attended by approximately two hundred fifty students, with effectiveness evaluated using a pretest–posttest design.
Result: Results indicated substantial improvement in participants’ understanding, with mean scores increasing from fifty-six to eighty-eight, alongside heightened engagement, confidence, and critical awareness of ethical artificial intelligence applications in healthcare.
Conclusion: The seminar effectively translated initial educational urgency into meaningful learning outcomes, demonstrating that human-centered international community service initiatives can strengthen artificial intelligence literacy. Future programs should expand practical laboratories, longitudinal evaluation, and interdisciplinary collaboration to support ethical innovation in health technology and student empowerment.
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