JSIKTI: Journal of Information Systems and Applied Computer Technology Indonesia, Volume 8 Number 2 (December 2025) presents a collection of advanced studies in deep learning, medical imaging, and applied computational methods contributed by researchers from the Institut Bisnis dan Teknologi Indonesia (Indonesia), Okayama University (Japan), Deakin University (Australia), the National Taiwan University of Science and Technology (Taiwan), Universitas Musamus Merauke (Indonesia), and Universitas Mulawarman (Indonesia). This issue highlights rapid developments in artificial intelligence applications for healthcare diagnostics and intelligent image-processing systems.

The published works explore a range of state-of-the-art deep learning architectures, including DenseNet121, MobileNetV2, VGG16, and VGG-19, applied to critical medical classification tasks. These include lung disease detection from chest X-ray images, automated cataract classification, cataract maturity assessment, and tuberculosis and pneumonia identification using CNN-based models. Further contributions propose lightweight MobileNet frameworks optimized for enhanced computational efficiency, enabling real-time lung infection detection suitable for practical clinical environments.

This issue reflects a strong multidisciplinary integration of machine learning, biomedical engineering, computer vision, and applied information systems. It reinforces JSIKTI’s commitment to disseminating impactful, data-driven, and solution-oriented research that contributes to technological innovation, scientific collaboration, and advancements in both national and global healthcare technology ecosystems.