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Cybersecurity and Innovative Technology Journal
Published by Gemilang Maju Publikasi Ilmiah
ISSN : -     EISSN : 30256682     DOI : http://dx.doi.org/10.53889/citj.v2i1.338
Core Subject : Science,
Computer Science & IT
Cybersecurity and Innovative Technology Journal is a peer-reviewed journal that covers research publications and review articles in the field of cybersecurity and innovative technology. Cybersecurity and Innovative Technology Journal is published by Gemilang Maju Publikasi Ilmiah (GMPI). Cybersecurity and Innovative Technology Journal has become a Crossref member since year 2023 with prefix 10.53889. Therefore all articles published by Cybersecurity and Innovative Technology Journal will have uniques DOI numbers since Vol.1, No.1, September 2023. Since Vol.1, No.1, September 2023. Cybersecurity and Innovative Technology Journal uses Anti-Plagiarism Software "Turnitin" to check the authenticity article.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 5 Documents
 1 
Search results for , issue "Vol 2, No 2 (2024)" : 5 Documents clear
Analysis of Teacher Readiness to Implement Bioinformatics to Biology Learning in Senior High School Sari, Indah Juwita; Setiawati, Eli; Aisy, Rihadatul; Bayoh Jr, Alpha
Cybersecurity and Innovative Technology Journal Vol 2, No 2 (2024)
Publisher : Gemilang Maju Publikasi Ilmiah (GMPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53889/citj.v2i2.454

Abstract

This study aimed to analyze teachers' readiness in applying bioinformatics to biology learning in senior high schools. Bioinformatics is a combination of computer science, statistics, and biology to analyze and interpret complex biological data. The application of bioinformatics into learning can foster students' realization of the real-life commitment of bioinformatics, enhance their understanding, and expand their curiosity about bioinformatics. The application of bioinformatics into biology learning needs to be supported by teacher readiness in terms of understanding, skills and factors that influence teacher readiness in applying bioinformatics. This research used a case study method with a qualitative descriptive approach to analyze the readiness of biology teachers from several senior high schools in Banten province in implementing bioinformatics into biology learning. The results of this study show that most teachers understand and realize the importance of bioinformatics in learning, on the other hand some teachers also feel not fully confident and able to apply bioinformatics into learning effectively. Although most teachers have adequate access to technology, teachers are not familiar with bioinformatics concepts and software such as BLAST and NCBI.  Therefore, to fulfill the aspect of teachers' understanding and skills in applying bioinformatics to learning, focused training is needed that discusses the basic concepts of bioinformatics, the use of bioinformatics software, and its application in learning to improve teacher competence and create interactive and relevant biology learning.
Cyber Science Education within STEM Spencer, Angela
Cybersecurity and Innovative Technology Journal Vol 2, No 2 (2024)
Publisher : Gemilang Maju Publikasi Ilmiah (GMPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53889/citj.v2i2.330

Abstract

Cyber science education is an essential component within the larger realm of STEM, which encompasses science, technology, engineering, and mathematics. In order to effectively educate and prepare students for future careers in the rapidly-evolving field of technology and digital communication, it is necessary to utilize both quantitative and qualitative research methods. The theoretical framework of constructivism allows educators to actively engage students in hands-on learning experiences that foster critical thinking skills and problem-solving abilities. The importance of cyber science education is evident in the 21 individuals who were interviewed and partcipated for this research study. These participants included educators, administrators, researchers, and industry professionals who all emphasized the need for a strong foundation in cyber science education in order to remain competitive in today's global job market. It is clear that cyber science education is crucial for preparing students for the future workforce and promoting innovation and advancement in various industries.
Ontology Development for SysML-Based Energy Harvester Design Green, Christopher W.
Cybersecurity and Innovative Technology Journal Vol 2, No 2 (2024)
Publisher : Gemilang Maju Publikasi Ilmiah (GMPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53889/citj.v2i2.540

Abstract

This study presented the development of an ontology for energy harvesting systems, leveraging the Systems Modeling Language (SysML) within a Model-Based Systems Engineering (MBSE). Energy harvesting, which transforms ambient energy into usable electrical power, has gained traction as a sustainable solution for powering low-power devices in applications such as wireless sensors and autonomous systems. This paper explored the diverse sources and components involved in energy harvesting, including transduction mechanisms, power management, and storage, to address the complexity inherent in multi-source energy systems. Using SysML profiles, this study constructs an ontology that formalizes the concepts, relationships, and constraints within the energy harvesting domain, providing a common vocabulary and promoting semantic interoperability among stakeholders. The ontology is developed systematically and structured to facilitate designing and reusing energy harvesting components, supporting increased efficiency and scalability. The results demonstrate how ontology-based design aids in reducing complexity, improving consistency, and fostering collaboration across interdisciplinary teams, offering significant implications for sustainable technology development in energy harvesting applications.
Artificial Intelligence and Cybersecurity in Preventing Sentinel Events Triplett, William J.
Cybersecurity and Innovative Technology Journal Vol 2, No 2 (2024)
Publisher : Gemilang Maju Publikasi Ilmiah (GMPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53889/citj.v2i2.555

Abstract

The study mainly focused on the impact of artificial intelligence (AI) in addressing sentinel occurrences in healthcare, particularly the unanticipated events that cause intensive patient harm. Through initiatives such as leveraging predictive analytics, machine learning algorithms, and processing of natural language, AI could help promote safety and prevent risks. This article evaluates the uses of AI, drawbacks, and the ethical implications while developing an understanding of how this innovation would boost patient care and cultural safety. Moreover, the paper examines the security issues related to AI-based healthcare to highlight the advantages of enforcing critical information safeguards while enhancing organizational dependability.
Artificial Intelligence, Cybersecurity, and Human Trafficking Networks Triplett, William J.
Cybersecurity and Innovative Technology Journal Vol 2, No 2 (2024)
Publisher : Gemilang Maju Publikasi Ilmiah (GMPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53889/citj.v2i2.556

Abstract

This study aimed to examine the role of artificial intelligence (AI) in dealing with human trafficking by analyzing social networks. Human trafficking is a global concern that exists in the anonymity of social connections and online platforms. There are important transformative tools that facilitate the identification and disruption of trafficking networks, including AI techniques like natural language processing, social network analysis, and machine learning.  The study tests AI applications, ethical considerations, and cybersecurity measures that importantly safeguards data integrity and promotes the efficacy of AI-driven systems. The outcomes of the study show the potential of AI in pattern recognition, network mapping, and predictive analytics to support law enforcement and advocacy groups.

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