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DIGITAL TWIN DRIVEN SMART CAMPUS DEVELOPMENT: CONCEPTS, CHALLENGES AND OPPORTUNITIES Jusia Amanda Ginting; I Gusti Ngurah Suryantara; Raphael Benedict Manuel
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.595

Abstract

This study aims to examine the development and implementation of digital twin technology in supporting smart campus ecosystems through a Systematic Literature Review approach. The study focuses on identifying technological trends, implementation opportunities, and various challenges that arise in the adoption of digital twin systems within higher education environments. The SLR method was conducted using the PRISMA framework to ensure a transparent and systematic article selection process. A total of 765 initial articles were identified from various academic databases with a publication range from 2015 to 2025. After undergoing the screening and selection process, 36 relevant articles were obtained for further analysis. The results show that digital twin technology has significant potential in supporting smart campus management through real-time monitoring of campus infrastructure, predictive maintenance of facilities, energy management optimization, and data-driven decision-making in university operations. In addition, this review also identifies several challenges in implementing digital twin systems, including data integration complexity, cybersecurity risks, high infrastructure investment requirements, and organizational readiness in facing digital transformation.
ANALISIS SENTIMEN DAN STRUKTUR SOSIAL DALAM PERDEBATAN DARING MENGENAI KEBIJAKAN MAKAN BERGIZI GRATIS (MBG) DI INDONESIA Jusia Amanda Ginting; I Gusti Ngurah Suryantara; Agustinus Fritz Wijaya; Teady Matius Surya Mulyana; Raphael Benedict Manuel
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.596

Abstract

Public policy discussions increasingly take place on social media, where public opinion is shaped not only by message content but also by patterns of user interaction. This study analyzes online conversations related to Indonesia’s Free Nutritious Meal (MBG) policy on platform X by integrating Social Network Analysis (SNA) and sentiment analysis. The dataset consists of 3,459 tweets collected between January 8 and February 11, 2025. Communication networks were constructed based on reply and mention relationships to identify interaction patterns and influential accounts. Sentiment analysis was conducted using a Natural Language Processing approach, with initial labeling based on BERT and further classification using a Support Vector Machine (SVM). Model performance was evaluated using accuracy, achieving a score of 91.78%. The findings reveal that MBG discussions form a relatively sparse yet highly centralized network dominated by a small number of accounts. Most tweets express neutral sentiment, while temporal analysis indicates a significant spike in activity on February 10, 2025. This study demonstrates that integrating network and sentiment analysis provides a more comprehensive understanding of how public opinion evolves in digital environments.