
JSIKTI: Journal of Information Systems and Applied Computer Technology Indonesia, Volume 6, Number 1 (September 2023) presents a diverse collection of research papers from Institut Bisnis dan Teknologi Indonesia (INSTIKI), Universitas Kristen Duta Wacana (UKDW), Politeknik Pertanian Negeri Samarinda, and Universitas Megarezky. This issue highlights the implementation of intelligent systems, decision support models, and digital transformation in various applied contexts.
The published articles discuss a range of topics, including the use of Simple Additive Weighting (SAW) and TOPSIS methods for tourism destination decision-making systems, the digitalization of cultural heritage through a 360-degree virtual reality platform, and the application of deep learning and machine learning algorithms—such as GRU and KNN—for hypertension risk prediction based on health and lifestyle data.
This edition underscores the journal’s dedication to advancing interdisciplinary research in applied computing and fostering collaboration between academic institutions in Indonesia and beyond. It reflects JSIKTI’s mission to bridge information technology innovations with real-world problem solving in tourism, health, and digital transformation.
Published: 2023-12-30
Articles
Implementation of the Simple Additive Weighting (SAW) Method in a Decision Support System for Tourist Destination Selection in North Bali
450-459
DOI : https://doi.org/10.33173/jsikti.261 Abstract views: 87 , PDF downloads: 49Implementation of the TOPSIS Method for a Decision Support System in Recommending Tourist Destinations in Tabanan
460-469
DOI : https://doi.org/10.33173/jsikti.262 Abstract views: 86 , PDF downloads: 44Digitalization of Bale Beleq in Pejanggik Village Based on a 360-Degree Virtual Reality Tour Website
470-480
DOI : https://doi.org/10.33173/jsikti.263 Abstract views: 31 , PDF downloads: 56Hypertension Risk Prediction Using GRU-Based Deep Learning Optimized with Stochastic Gradient Descent
481-494
DOI : https://doi.org/10.33173/jsikti.264 Abstract views: 44 , PDF downloads: 77KNN-Based Prediction Model for Assessing Hypertension Risk from Lifestyle Features
495-505
DOI : https://doi.org/10.33173/jsikti.265 Abstract views: 47 , PDF downloads: 51







