JSIKTI: Journal of Information Systems and Applied Computer Technology Indonesia, Volume 7 Number 2 (December 2024) features a distinguished collection of applied computing research contributed by Kindai University (Japan), Okayama University (Japan), National Taiwan University of Science and Technology (Taiwan Tech), and the Institut Bisnis dan Teknologi Indonesia (INSTIKI). This issue highlights international collaboration and interdisciplinary innovation across machine learning, financial forecasting, medical analytics, and land suitability assessment.

The articles include an enhanced Random Forest–based classification model for prostate cancer, an LSTM network application for forecasting Ethereum price fluctuations, and a K-Nearest Neighbors approach to classify diabetes risk categories. Additional contributions feature a land suitability analysis using a modified Profile Matching method and a Decision Tree model for predicting Bitcoin prices based on market indicators.

This volume showcases the synergy of global academic expertise and applied research, reinforcing JSIKTI’s role as a platform that bridges international scholarship with real-world technological solutions. Through advanced analytics, data-driven modeling, and interdisciplinary methodologies, this issue supports the journal’s mission to drive innovation and applied research in information systems across Asia and beyond.