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All Journal JOIN (Jurnal Online Informatika) International Journal of Artificial Intelligence Research InComTech: Jurnal Telekomunikasi dan Komputer JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer Networks, Architecture and High Performance Computing Journal Zetroem ICTEE (Engineering Journals of Information, control, telecommunication and electrical) Perwira Journal of Science and Engineering (PJSE) International Journal of Engineering Continuity International Journal of Science Education and Cultural Studies International Journal of Management Science and Application Jurnal Komputer dan Elektro Sains Jurnal Pengabdian Masyarakat Sultan Indonesia BACA: Jurnal Dokumentasi dan Informasi
Taufik Hidayat
Universitas Wiralodra
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Unveiling the Cybercrime Ecosystem: Impact of Ransomware-as-a-Service (RaaS) in Indonesia Budi wibowo; Luqman Hafiz; Taufik Hidayat
International Journal of Science Education and Cultural Studies Vol. 4 No. 1 (2025): IJSECS
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijsecs.v4i1.320

Abstract

This study explores the rise of Ransomware-as-a-Service (RaaS) in Indonesia’s cybercrime ecosystem, highlighting its role as a significant digital security threat. RaaS lowers the technical barriers to executing ransomware attacks, enabling individuals with minimal expertise to launch sophisticated cyberattacks. Analyzing data from 2020 to 2024, this study identified Indonesia as a hotspot for RaaS-driven cybercrime in Southeast Asia due to low cybersecurity awareness and weak regulatory frameworks. Key findings reveal that government administration, healthcare, and finance are the most frequently targeted sectors due to their sensitive data and inadequate defense capabilities. Ransomware variants such as Luna Moth and WannaCry, dominate the malware landscape by employing tactics like phishing and exploiting outdated systems. These attacks result in severe socioeconomic consequences, including financial losses, operational disruptions, and reputational damage. This study contributes to our understanding of RaaS by examining its operational, economic, and regulatory dimensions in the Indonesian context. This underscores the urgent need for strengthened cybersecurity policies, public-private sector collaboration, and international cooperation to address transnational cybercrime. By providing actionable insights into attack patterns and mitigation strategies, this study aims to guide efforts to combat ransomware threats and enhance Indonesia’s digital resilience.
Cybersecurity Education Strategies Based on Open-Source Intelligence (OSINT) to Enhance Public Awareness Taufik Hidayat; Budi Wibowo; Andrie Yuswanto; Annisa Fathul Jannah
International Journal of Science Education and Cultural Studies Vol. 4 No. 2 (2025): ijsecs
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijsecs.v4i2.422

Abstract

In today’s rapidly evolving digital landscape, cybersecurity threats are escalating in both frequency and complexity, which points to the urgent need for effective educational approaches to enhance public awareness. Open-Source Intelligence (OSINT), which leverages publicly available information, offers a practical framework for identifying and understanding cyber risks. This study proposes the design, implementation, and evaluation of an OSINT-based cybersecurity education strategy aimed at non-technical audiences. Employing a mixed-methods approach including literature review, module development, and surveys, this research measures the strategy’s effectiveness in improving cybersecurity comprehension. The results indicate that the OSINT-based educational approach significantly enhances participants’ understanding of cyber risks, yielding an average increase of 35% in comprehension scores. Furthermore, the integration of real-world OSINT demonstrations makes cybersecurity threats more tangible and personally relevant, thereby motivating proactive preventive behavior. In conclusion, incorporating OSINT into cybersecurity education provides an effective and scalable strategy for improving public awareness and resilience against modern digital threats.
Digital Signal Feature Extraction for Graph-Based Host Classification in VM Placement Taufik Hidayat; Lukman Medriavin Silalahi; Abdul Hamid
ZETROEM Vol 8 No 1 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i1.7559

Abstract

This study proposes a host classification methodology based on signal analysis and graph representation as a pre-placement stage for virtual machines (VM) in a cloud computing environment. The Bitbrains dataset is utilized as a source of time-series data representing CPU, memory, disk, and network utilization. Each parameter is modeled as a discrete signal and analyzed in both time and frequency domains. The analysis is conducted using a fixed observation window and frequency-domain transformation to capture workload characteristics across multiple resources. The Fourier transform results indicate the dominance of low-frequency components, suggesting gradual workload variations. Spectral energy is calculated and normalized to identify quantitative differences between host conditions. The results show that the overloaded class contributes 98.9% of the total spectral energy, while the underloaded and balanced classes contribute only 0.7% and 0.4%, respectively. The extracted features are then integrated using a four-node graph model that connects all resource dimensions into a single structure. The aggregated graph score is employed for dynamic percentile-based classification. From a total of 1,239 analyzed hosts, the proposed method classifies 421 hosts as overloaded, 409 as underloaded, and 409 as balanced. These findings demonstrate that spectral characteristics combined with graph integration provide a quantitatively structured and adaptive host segmentation mechanism, where the resulting classification can support VM placement decisions by identifying underloaded, balanced, and overloaded host conditions.
Co-Authors Abdul Hamid Adrial Adrial Affan Nawly Tanjung Affy Khoiriyah Ahmad Gani Aji Nurrohman Ali Miftakhu Rosyad Ali Miftakhu Rosyad Alissa Eka Rahmawati Andrie Yuswanto Andrie Yuswanto Andrie Yuswanto Angel Imannuel Annisa Fathul Jannah Azzery, Yasep Baiti Jannati Budi wibowo Cyntiya Laxmi Haura Dandi, Muhamad Dewi Yunita Sari Dewi Yunita Sari Diana Rusjayanti Diana Rusjayanti Dwi Mulyanto, Nur Fachri Alfianza Febriano Anggawa Rizky Fernando, Kinky He Xi Kang Hufrizatul Parida Ica Reisyya Y. P Imroatul Karimah Indra Surya Permana Ismail Ismail Ismail Ismail Jannatul Firdaus Nawang Wulan Julpri Andika Kalamullah Ramli Kinky Fernando Lukman Medriavin Silalahi Luqman Hafiz Luthfia Sodikin M Ihsan M. Kenanta Dhafin Mahardiko, Rahutomo Marwiyah Marwiyah Moh Mardiyana Mohamad Adnan Fauzi Mudrik Alaydrus Muhamad Baedowi Muhamad Dandi Muhammad Hamsah Nadim Ibrahim Nadim Ibrahim Najeem Olawale Adelakun Nida Pristyan Ramadhani Nur Afandi Nur Dwi Mulyanto Nurchamidah Nurchamidah Pao P. Ruaya Parastoo Alaei Roozbahani Pipit Puji Arti R. Deiny Mardian Rahmat Hidayat Rahutomo Mahardiko Rahutomo Mahardiko Rahutomo Mahardiko Ricky Martin, Mohamad Safera, Agna Shofa Lutfiah Fitri Sianturi Tigor Franky Devano Sigit Wibawa Sodikin, Luthfia Stephen Reader Suwoyo, Heru Syahril Sidiq Tineke Fatma Putri Tio Dwi Ananpasha tion sutiyono Tion Sutiyono Wahyu Pratama SJ Wiji Prayitno, Seno Yasep Azzery Zaenudin Zaenudin Zeyn Saleh Ali