Quantitative Analysis of the Key Factors Driving Cybersecurity Awareness Among Information Systems Users

Cybersecurity threats are increasingly complex and widespread, posing significant risks to individuals and organizations. However, many studies tend to address the technological or behavioral aspects separately. The study uses a survey-based quantitative approach using PLS-SEM to analyze key factors that influence cybersecurity awareness, including demographics, training, psychological bias, and organizational culture. The findings suggest that several constructs-such as threat awareness, perceived risk, and education-significantly predict cybersecurity awareness and behaviour. Notably, the model yields an R² value of up to 0.703 with a strong path significance (p < 0.05), which underscores the robustness of the relationship. This study offers an integrated perspective on cybersecurity by bridging the psychological, educational, and organizational dimensions. It highlights cybersecurity awareness as a mediating construct that links upstream factors to secure user behavior-a relational structure that has not been explored in previous research.

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Publication Details

Journal
Jurnal Teknik Informatika (Jutif)
Published
2025-08-18
DOI
https://doi.org/10.52436/1.jutif.2025.6.4.4861
Primary Topic
Advanced Graph Theory Research
Type
article
Field-Weighted Citation Impact
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article

Quantitative Analysis of the Key Factors Driving Cybersecurity Awareness Among Information Systems Users

Jurnal Teknik Informatika (Jutif)
Advanced Graph Theory Research
article

Quantitative Analysis of the Key Factors Driving Cybersecurity Awareness Among Information Systems Users

article en

Abstract

Cybersecurity threats are increasingly complex and widespread, posing significant risks to individuals and organizations. However, many studies tend to address the technological or behavioral aspects separately. The study uses a survey-based quantitative approach using PLS-SEM to analyze key factors that influence cybersecurity awareness, including demographics, training, psychological bias, and organizational culture. The findings suggest that several constructs-such as threat awareness, perceived risk, and education-significantly predict cybersecurity awareness and behaviour. Notably, the model yields an R² value of up to 0.703 with a strong path significance (p < 0.05), which underscores the robustness of the relationship. This study offers an integrated perspective on cybersecurity by bridging the psychological, educational, and organizational dimensions. It highlights cybersecurity awareness as a mediating construct that links upstream factors to secure user behavior-a relational structure that has not been explored in previous research.

Jurnal Teknik Informatika (Jutif)Vol. 6(4)
Sebelas Maret University (ID), Syarif Hidayatullah State Islamic University Jakarta (ID), Asia e University (MY)
Openalex Percentile: Top 45%
Advanced Graph Theory Research
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