Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 2, 2025Jurnal Pertahanan Media Informasi tentang Kajian dan Strategi Pertahanan yang Mengedepankan Identity Nasionalism dan IntegrityOpen Access

National Cyber Defense: Analysis of Incident Severity Factors Using a Decision Tree

View Full Paper
Ask AI
Bookmark
Share

Authors

RFReyhan FakhrejaKUKhaerul UmamKZKamila Zahra

Discussion

Loading...

Member takes

Overview

Descriptive quantitative analysis identifies major severity predictors in cyber incidents, suggesting data-driven policy improvements.

Key Points

  • Incident Type is the strongest predictor of cyber incident severity, highlighting its critical role.
  • Attacks with response times over 48 hours often lead to critical outcomes, emphasizing the importance of timely responses.
  • The decision tree model achieved 93.75 percent accuracy, showcasing its effectiveness in predicting incident severity.
  • Recommendations aim to strengthen Indonesia’s cybersecurity by enhancing infrastructure and incident response frameworks.

Cite This Study

Fakhreja et al. (2025) studied this question.

synapsesocial.com/papers/68de6f3f83cbc991d0a22d12https://doi.org/10.33172/jp.v11i1.19798
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Digital Risks in Emerging Economies: Cyber Threat Escalation in Indonesia (2020–2023)2024 · 1 citations
  2. 2CYBER RISK MANAGEMENT IN THE DIGITAL ERA: AN ANALYSIS OF MITIGATION STRATEGIES AND PREVENTIVE INNOVATIONS AGAINST CYBERCRIME IN INDONESIA2025 · 1 citations
  3. 3Bridging the Gap Between Policy and Practice: Evaluating Indonesia’s Cybersecurity Regulatory Framework (2020–2023)2024
  4. 4Analysis of Knowledge Management Strategies for Handling Cyber Attacks with the Computer Security Incident Response Team (CSIRT) in the Indonesian Aviation Sector2024
  5. 5Cybersecurity Challenges and Investment in Indonesia2024