Vol. 9 No. 01 (2026): J-KOMA: Journal of Computer Science and Applications
This Issues presents six research articles spanning computer science, applied statistics, and information systems. This edition features a broad spectrum of analytical and modeling approaches, from the Vector Error Correction Model (VECM) for examining the long- and short-term relationships between taxation and Indonesia's economic growth, to discriminant analysis methods—Linear and Quadratic Discriminant Analysis—for early cervical cancer risk prediction based on behavioral and psychosocial attributes. The articles in this volume also demonstrate extensive applications of machine learning and deep learning: sentiment analysis using Random Forest to gauge public opinion on the reinstatement of academic streaming policy in senior high schools, a comparative study of lexicon-based and machine learning approaches (SVM, Naïve Bayes, Random Forest) for classifying sentiment in Indonesian telemedicine reviews, and a CNN-based transfer learning approach using MobileNetV2 and DenseNet121 for automated lung disease diagnosis from MRI imaging. Rounding out this volume is a systems development study presenting the optimization of a web-based room information management system (SIPERAD) using the Waterfall method. Overall, the contributions in this volume illustrate the application of modern computational and statistical methods to real-world problems across the fiscal, educational, healthcare, and higher-education administration domains, making it relevant reading for researchers, data science practitioners, health informatics scholars, and policymakers.
