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All Journal Vox Dei : Jurnal Teologi dan Pastoral Global Science: Journal of Information Technology and Computer Science
Royke Lantupa Kumowal
Unknown Affiliation
Religion Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Social Sciences

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"Dumia Umbanua” : Misi Kontekstual Dalam Moderasi Beragama Di Desa Laikit Kabupaten Minahasa Utara Royke Lantupa Kumowal; Kalintabu, Heliyanti; Charolin Geby Bambung
Vox Dei: Jurnal Teologi dan Pastoral Vol 5 No 2 (2024): Desember 2024
Publisher : Sekolah Tinggi Teologi Ekumene Jakarta.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46408/vxd.v5i2.488

Abstract

The dumia umbanua tradition has important historical and cultural values ​​for the local community. However, the implementation of the Dumia Umbanua traditional ceremony often gives rise to differences in views and interpretations between custom and religion, as well as giving rise to conflict between communities. Some Christian religious figures in Minahasa even consider that the dumia umbanua traditional ceremony is not in accordance with the Christian faith. The aim of this research is to examine the dumia umbanua tradition; connecting dumia umbanua in the study of contextual mission theology and implementation in religious moderation. The research method used is a descriptive qualitative research approach. using literature studies and field data. The results of research on contextual mission services in the Laikit community are an approach to church service that emphasizes the importance of contextual understanding in dealing with traditional controversies. Contextual mission ministry includes all church efforts to present the message of the good news (gospel) and God's salvation in a relevant way through that tradition. Through the Missio Dei, God gives the Missio Ecclesiae, namely the authority to the church to carry out God's mission which is non-exclusive, tolerant and contextual.
Digital Twin-Driven Cybersecurity Risk Assessment Model for Industrial Internet of Things (IIoT) Networks in Manufacturing 4.0 Atika Mutiarachim; Royke Lantupa Kumowal; Nigar Aliyeva
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 2 (2025): June: Global Science: Journal of Information Technology and Computer Science
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i2.175

Abstract

This study explores the development and application of a digital twin-driven cybersecurity risk assessment model for Industrial Internet of Things (IIoT) networks. The increasing complexity and interconnectivity of IIoT systems have expanded the attack surface, making them vulnerable to a wide range of cyber threats. The digital twin model addresses this challenge by creating real-time virtual replicas of physical systems, which can simulate and predict network vulnerabilities and attack vectors. The model uses machine learning algorithms and real-time data to simulate cyberattacks, including Distributed Denial of Service (DDoS), malware, and data breaches. By providing continuous monitoring and dynamic risk predictions, the digital twin model enhances the resilience of IIoT networks compared to traditional cybersecurity frameworks. The findings indicate that the model's ability to predict potential cyber threats and simulate various attack scenarios provides a more proactive and accurate approach to cybersecurity in IIoT environments. Additionally, the study highlights key mitigation strategies, including adaptive security mechanisms, real-time anomaly detection, and the use of lightweight encryption for resource-constrained devices. Despite its effectiveness, challenges such as computational requirements, integration with legacy systems, and scalability were identified. This research underscores the strategic importance of digital twin models in securing IIoT systems and advancing Manufacturing 4.0 ecosystems. Future research should focus on enhancing model accuracy, expanding its application to diverse industrial sectors, and improving interoperability with legacy systems to further strengthen the security posture of IIoT networks.
Co-Authors Atika Mutiarachim Charolin Geby Bambung Heliyanti Kalintabu Nigar Aliyeva