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All Journal PENDIPA Journal of Science Education KOMPUTA : Jurnal Ilmiah Komputer dan Informatika
Wahyudi, Bisyron
Unknown Affiliation
Chemistry Computer Science & IT Education Mathematics

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Studi Pustaka: Optimalisasi Deteksi Malware melalui Integrasi Pembelajaran Mesin Heuristik dan Big Data untuk Keamanan Siber Supriyadi, Devi; Wahyudi, Bisyron; Rimbawa, Danang
Komputa : Jurnal Ilmiah Komputer dan Informatika Vol 14 No 1 (2025): Komputa : Jurnal Ilmiah Komputer dan Informatika
Publisher : Program Studi Teknik Informatika - Universitas Komputer Indonesia (UNIKOM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputa.v14i1.15595

Abstract

The increasingly complex and dynamic threat of malware drives the need for a more adaptive detection strategy than conventional signature-based methods. This study aims to evaluate the effectiveness of machine learning, heuristics, and big data approaches in detecting modern malware. The main problem raised is the limitation of traditional methods in identifying new malware variants, especially those that use obfuscation techniques such as polymorphism and metamorphism. Using a systematic literature study approach to the 2016-2024 literature from various reputable sources, this study compares the performance of each approach based on accuracy, efficiency, and resistance to adversarial attacks. The results of the analysis show that deep learning models such as the Convolutional Neural Network (CNN) have the highest detection accuracy, while heuristic methods excel in initial detection efficiency, and big data provides advantages in the scalability of real-time detection systems. This study concludes that the hybrid integration of these three approaches has the potential to create a malware detection system that is more adaptive and resilient to cyberattacks, although further empirical validation is still needed for real-world implementation.
Penguatan Literasi Sains sebagai Instrumen Pertahanan Negara: Tinjauan Literatur Melawan Disinformasi Lingkungan dan Bencana Triason, Herwan; Wahyudi, Bisyron; Sibarani, Frado
PendIPA Journal of Science Education Vol 10 No 1 (2026): January - March
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pendipa.10.1.145-152

Abstract

Environmental and disaster disinformation has evolved into a serious hybrid threat to national defense, targeting social stability and public trust during crises. This study aims to analyze the strategic role of science literacy as a non-military defense modality in countering false narratives and pseudoscience. Employing a Systematic Literature Review (SLR) method with the PRISMA protocol, this study reviewed selected articles published between 2020 and 2025 from Scopus, Google Scholar, and Garuda Portal databases. The analysis reveals that disaster disinformation operates as a form of cognitive warfare that undermines national mitigation responses. Key findings confirm that science literacy functions effectively as a "cognitive shield" that enhances public resistance to hoaxes, while simultaneously repositioning critical thinking skills as a modern manifestation of the State Defense (Bela Negara) concept within the Universal People's Defense and Security System (Sishankamrata). This study concludes that integrating science curriculum with defense doctrine is imperative to build adaptive national resilience. Synergy between the education and defense sectors is recommended to create a resilient information ecosystem.
Co-Authors Rimbawa, Danang Sibarani, Frado Supriyadi, Devi Triason, Herwan