Abstract:Abstract: The development of digital technology in Indonesia has penetrated even rural areas, but it is not accompanied by an adequate understanding of personal data security. Rural communities tend to be vulnerable to cyber…
yber threats due to limited digital literacy. The purpose of this Community Service (PkM) activity is to increase awareness and knowledge of the community of Silo Lama Village, Silau Laut District, about the importance of personal data security in the digital era. The implementation method includes outreach, education, and practical training for the community using a participatory approach. The material presented includes the definition of personal data, types of cyber threats, how to protect personal information, and an introduction to the Personal Data Protection Law. The activity was attended by 30 participants consisting of village officials, community leaders, and the general public. The results of the activity showed a significant increase in participants' understanding of personal data security, from an average pre-test score of 45% to 82% in the post-test. Participants were also able to identify various forms of online fraud and implement data protection measures. This program has made a positive contribution to improving the digital literacy of rural communities and is expected to prevent losses due to cybercrime in the future.
Keywords: cyber; data; digital; security; village
Abstrak: Perkembangan teknologi digital di Indonesia telah merambah hingga ke wilayah pedesaan, namun tidak diimbangi dengan pemahaman yang memadai tentang keamanan data pribadi. Masyarakat desa cenderung rentan terhadap ancaman siber karena keterbatasan literasi digital. Tujuan dari kegiatan Pengabdian kepada Masyarakat (PkM) ini adalah untuk meningkatkan kesadaran dan pengetahuan masyarakat Desa Silo Lama, Kecamatan Silau Laut tentang pentingnya menjaga keamanan data privat. Metode kegiatan meliputi sosialisasi, edukasi, dan pelatihan praktis kepada masyarakat dengan pendekatan partisipatif. Materi yang disampaikan mencakup pengertian data pribadi, jenis-jenis ancaman siber, cara melindungi informasi pribadi, serta pengenalan UU Perlindungan Data Pribadi. Kegiatan dihadiri dengan 30 orang meliputi unsur pejabat desa, tokoh warga, dan warga umum. Hasil kegiatan memaparkan peningkatan pemahaman warga terkait keamanan data pribadi, dari rerata skor pre-test 45% menjadi 82% pada post-test. Peserta juga mampu mengidentifikasi berbagai bentuk penipuan online dan menerapkan langkah-langkah perlindungan data. Program ini memberikan kontribusi positif dalam upaya meningkatkan literasi digital masyarakat desa dan diharapkan dapat mencegah kerugian akibat kejahatan siber di masa mendatang
Kata kunci: data; digital; desa; keamanan; siber
Abstract:Abstract: The rapid development of digital technology in education presents significant benefits, but it also introduces serious challenges in the form of increasing threats of Cybercrime. Teachers at SD Negeri 132408 Kota…
ta Tanjungbalai, as the frontline of education, often lack an adequate understanding of digital literacy and how to handle cybercrimes, such as the spread of false information, data theft, and violations of digital ethics. This community service activity aims to enhance the digital literacy capacity of teachers in preventing and addressing Cybercrime within the school environment. The methods used include intensive training, group discussions, case studies, and practical simulations, implemented in three stages: preparation, implementation, and evaluation. The solutions offered encompass providing digital literacy materials, Cybercrime prevention training, and developing practical guidelines. Evaluation results show that teacher understanding increased significantly, with the average score rising from 45 to 78 (p<0.05). The targeted outputs of this activity are the publication of a scientific article in a Sinta 5 accredited national journal as a mandatory output, and a popular article in mass media as an additional output. This activity is expected to increase teachers' awareness and skills in creating a safe and healthy digital education environment.
Keywords: cybercrime; digital literacy; education; elementary school teachers; training
Abstrak: Pesatnya perkembangan teknologi digital di dunia pendidikan menghadirkan manfaat besar, namun juga memunculkan tantangan serius berupa meningkatnya ancaman Cybercrime. Guru di SD Negeri 132408 Kota Tanjungbalai, sebagai garda terdepan pendidikan, seringkali belum memiliki pemahaman yang memadai tentang literasi digital dan cara menghadapi kejahatan siber, seperti penyebaran informasi palsu, pencurian data, dan pelanggaran etika digital. Kegiatan pengabdian ini bertujuan untuk meningkatkan kapasitas literasi digital guru dalam mencegah dan mengatasi Cybercrime di lingkungan sekolah. Metode yang digunakan berupa pelatihan intensif, diskusi kelompok, studi kasus, dan simulasi praktik, yang dilaksanakan dalam tiga tahap: persiapan, pelaksanaan, dan evaluasi. Solusi yang ditawarkan mencakup pemberian materi literasi digital, pelatihan pencegahan Cybercrime, dan penyusunan panduan praktis. Hasil evaluasi menunjukkan pemahaman guru meningkat signifikan dari skor rata-rata 45 menjadi 78 (p<0.05). Target luaran dari kegiatan ini adalah publikasi artikel ilmiah pada jurnal nasional terakreditasi Sinta 5 sebagai luaran wajib, dan artikel di media massa sebagai luaran tambahan. Diharapkan kegiatan ini mampu meningkatkan kesadaran dan keterampilan guru dalam menciptakan lingkungan pendidikan digital yang aman dan sehat.
Kata kunci: cybercrime; guru sd; literasi digital; pelatihan; pendidikan
Abstract:Abstract: The rapid development of digital technology brings various benefits as well as challenges, one of which is the increasing risk of cyber threats and personal data breaches. The digital community, particularly participants…
rticipants at LKP Mutiara Informatika in Asahan Regency, requires a fundamental understanding and skills in protecting personal data and recognizing cyber threats. This community service program aims to provide educational and practical training on personal data protection and cybersecurity. The implementation methods include material delivery, interactive discussions, and practical simulations using real case studies. This program enhanced participants’ understanding of digital privacy, online fraud, and the use of basic security tools. Participants were also able to identify preventive measures to protect their digital accounts. Through this training, the community is better prepared to face the challenges of the technological era and to serve as agents of cybersecurity literacy, while also emphasizing the importance of synergy between education and technology in building safe and responsible digital awareness.
Keywords: personal data; cybersecurity; digital community
Abstrak: Perkembangan teknologi digital yang pesat membawa berbagai manfaat sekaligus tantangan, salah satunya adalah meningkatnya risiko terhadap keamanan siber dan kebocoran data pribadi. Masyarakat digital, khususnya peserta di LKP Mutiara Informatika Kabupaten Asahan, membutuhkan pemahaman dan keterampilan dasar dalam melindungi data pribadi serta mengenali ancaman siber. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memberikan pelatihan yang bersifat edukatif dan aplikatif mengenai perlindungan data pribadi dan keamanan siber. Metode pelaksanaan meliputi penyampaian materi, diskusi interaktif, dan simulasi praktik menggunakan studi kasus nyata. Kegiatan ini meningkatkan pemahaman peserta tentang privasi digital, penipuan online, serta penggunaan perangkat pengaman dasar. Peserta juga mampu mengenali langkah pencegahan untuk melindungi akun digital. Dengan pelatihan ini, masyarakat lebih siap menghadapi tantangan era teknologi dan berperan sebagai agen literasi keamanan siber, sekaligus menegaskan pentingnya sinergi edukasi dan teknologi dalam membangun kesadaran digital yang aman.
Kata kunci: data pribadi; keamanan siber; masyarakat digital
Abstract:In the ever-evolving digital era, technological advancements have affected various aspects of life, including data security. Personal data protection has been crucial, especially for students who actively use the internet…
net and they are vulnerable to cyber threats. However, many students at MA Al Washliyah Kisaran are not fully aware of the digital security risks and the importance of their personal information protection. Therefore, an educational activity was conducted to enhance students’ understanding and skills in maintaining digital security. The methods used in this program were socializing and educating about digital threats such as phishing, data breaches, and social media security. This avticity aims to raise awareness and encourage responsible internet usage among students. Through this activity, students are expected to have better understanding of digital threats and the preventive measures needed to protect their personal data.
Keywords: digital security; personal data protection; MA Al washliyah kisaran
Abstrak: Di era digital yang terus berkembang, kemajuan teknologi telah memengaruhi berbagai aspek kehidupan, termasuk keamanan data. Perlindungan data pribadi menjadi sangat penting, terutama bagi siswa yang aktif menggunakan internet dan mudah terkena ancaman siber. Namun, banyak siswa di MA Al Washliyah Kisaran yang belum sepenuhnya menyadari risiko keamanan digital serta pentingnya melindungi informasi pribadi mereka. Oleh karena itu, kegiatan edukasi ini dilakukan untuk meningkatkan pemahaman dan keterampilan siswa dalam menjaga keamanan digital. Metode yang digunakan dalam kegiatan ini meliputi sosialisasi dan edukasi mengenai berbagai ancaman digital seperi phishing, kebocoran data, dan keamanan media sosial. Kegiatan ini bertujuan untuk meningkatkan kesadaran serta mendorong penggunaan internet secara bijak di kalangan siswa. Dengan adanya kegiatan ini, siswa diharapkan dapat lebih memahami potensi ancaman digital serta menerapkan langkah-langkah pencegahan yang diperlukan untuk melindungi data pribadi mereka.
Kata kunci: keamanan digital; perlindungan data pribadi; MA Al washliyah kisaran
Abstract:Awareness of social media security is very important today, especially due to the increasing number of online security threats that can affect user privacy and data security. Moreover, the condition of rural communities…
is in dire need of knowledge to be wiser in using social media. This community service was carried out in Cempaka Village, Cempaka District, OKU Timur Regency, with the aim of increasing public understanding of cyber security. The methods used were education and socialization about cyber threats, the importance of maintaining password confidentiality, and personal data privacy. This activity involved the active participation of various levels of the Cempaka Village community. The results of this service showed a significant increase understanding of social media secutty awareness. People became more aware of the risks of crime on social media and had better knowledge of how to protect themselves.
Keywords: cempaka village; security awareness; social media; socialization
Abstrak: Kesadaran akan keamanan media sosial sangat penting saat ini, terutama karena meningkatnya ancaman keamanan daring yang dapat memengaruhi privasi dan keamanan data pengguna. Apalagi kondisi masyarakat desa yang sangat membutuhkan pengetahuan agar lebih bijaksana dalam menggunakan media sosial. Pengabdian masyarakat ini dilaksanakan di Desa Cempaka, Kecamatan Cempaka, Kabupaten OKU Timur, dengan tujuan meningkatkan pemahaman masyarakat mengenai keamanan siber. Metode yang digunakan adalah edukasi dan sosialisasi tentang ancaman siber, pentingnya menjaga kerahasiaan kata sandi, dan privasi data pribadi. Kegiatan ini melibatkan partisipasi aktif dari berbagai lapisan masyarakat Desa Cempaka. Hasil dari pengabdian ini menunjukkan peningkatan yang signifikan dalam pemahaman masyarakat mengenai keamanan media sosial. Masyarakat menjadi lebih sadar akan risiko kejahatan di media sosial dan memiliki pengetahuan yang lebih baik tentang cara melindungi diri mereka.
Kata kunci: desa cempaka; security awareness; sosial media; sosialisasi
Abstract:Abstract: The growing intensity of cyber attacks, marked by rapid, large-scale, automated, and adaptive execution, requires analytical methods that represent the diversity of network environments, including variations in…
target platforms such as IoT, traditional networks, and hybrid infrastructures. This study compares machine learning models for cyber attack classification under heterogeneous environmental conditions and formulates a conceptual optimization framework based on model performance. Four publicly available benchmark datasets were used, namely UNB CIC IoT 2023, UNB CIC IDS-2018, UNSW-NB15, and a Kaggle cyber security attacks dataset, comprising approximately 40,000 to over 3.6 million records and 25 to 80 features across IoT, conventional, and mixed network environments. Random Forest, XGBoost, Multilayer Perceptron, and Transformer were implemented within a unified pipeline involving preprocessing, feature selection, and Bayesian Optimization-based hyperparameter tuning. All models achieved F1-score and Cohen's Kappa above 96%, with XGBoost performing best (97.80%, 97.26%), followed by Random Forest (97.78%, 96.96%) and Transformer (97.44%, 96.82%), while MLP scored lowest (96.74%, 96.00%), a gap below one percentage point. Confusion matrix analysis revealed persistent misclassification in minority and overlapping attack classes, informing a proposed adaptive cyber attack simulation optimization framework.
Keywords: cyber attacks; optimization; machine learning; environmental variability.
Abstrak: Meningkatnya intensitas serangan siber yang berlangsung cepat, masif, otomatis, dan adaptif menuntut pendekatan analitis yang merepresentasikan keragaman lingkungan jaringan, termasuk perbedaan karakteristik platform sasaran seperti Internet of Things (IoT), jaringan konvensional, dan infrastruktur hibrida. Penelitian ini membandingkan model machine learning untuk klasifikasi serangan siber pada kondisi lingkungan heterogen, sekaligus menyusun kerangka optimasi konseptual berdasarkan performa model. Empat dataset benchmark publik digunakan, yaitu UNB CIC IoT 2023, UNB CIC IDS-2018, UNSW-NB15, serta dataset Kaggle cyber security attacks, dengan jumlah data berkisar 40.000 hingga lebih dari 3,6 juta rekaman dan 25 sampai 80 fitur, mewakili lingkungan IoT, konvensional, dan campuran. Random Forest, XGBoost, Multilayer Perceptron, dan Transformer diimplementasikan melalui pipeline terpadu mencakup pra-pemrosesan, seleksi fitur, dan optimasi hyperparameter berbasis Bayesian Optimization. Seluruh model mencapai F1-score dan Cohen's Kappa di atas 96%, dengan XGBoost menunjukkan performa terbaik (97,80%, 97,26%), diikuti Random Forest (97,78%, 96,96%) dan Transformer (97,44%, 96,82%), sementara MLP mencatat skor terendah (96,74%, 96,00%), dengan selisih kurang dari satu poin persentase. Analisis confusion matrix mengungkap misklasifikasi yang konsisten pada kelas minoritas dan serangan dengan karakteristik serupa, yang menjadi dasar kerangka optimasi simulasi serangan siber adaptif yang diusulkan.
Kata kunci: serangan siber; optimasi; machine learning; variabilitas lingkungan
Abstract:Abstract: In the era of the Internet of Things (IoT), cyber threats are increasingly complex and dynamic, thus demanding an adaptive and intelligent network security system. This study proposes a Convolutional Neural Network…
work (CNN)-based Intrusion Detection System (IDS) implemented through a Federated Learning (FL) approach in a Non-Independent and Identically Distributed (Non-IID) data environment. This approach allows the model to be trained in a distributed manner across multiple IoT devices without having to collect sensitive data to a central server, thereby maintaining data privacy while increasing the efficiency of the training process. The experiment used the CIC IoT 2023 dataset, which represents various modern IoT network traffic patterns. The results show that the proposed CNN–FL model achieves an overall accuracy of 0.99, with excellent performance in detecting various types of network traffic. The model obtains a perfect recall value (1.00) for normal traffic (Benign), as well as a very high F1-score for DDoS (0.99) and DoS (0.99) attacks. Stable and consistent performance across all five federation rounds demonstrates that this approach is a reliable, efficient, and accurate solution for detecting threats in distributed and privacy-preserving IoT networks.
Keywords: cnn; federated_learning; ids; non-iid; ciciot2023
Abstrak: Dalam era Internet of Things (IoT), ancaman siber semakin kompleks dan dinamis, sehingga menuntut sistem keamanan jaringan yang adaptif dan cerdas. Penelitian ini mengusulkan Intrusion Detection System (IDS) berbasis Convolutional Neural Network (CNN) yang diterapkan melalui pendekatan Federated Learning (FL) pada lingkungan data yang bersifat Non-Independent and Identically Distributed (Non-IID). Pendekatan ini memungkinkan model dilatih secara terdistribusi di berbagai perangkat IoT tanpa harus mengumpulkan data sensitif ke server pusat, sehingga mampu menjaga privasi data sekaligus meningkatkan efisiensi proses pelatihan. Eksperimen menggunakan dataset CIC IoT 2023, yang merepresentasikan berbagai pola lalu lintas jaringan IoT modern. Hasil penelitian menunjukkan bahwa model CNN–FL yang diusulkan mencapai akurasi keseluruhan sebesar 0.99, dengan performa yang sangat baik dalam mendeteksi berbagai jenis lalu lintas jaringan. Model memperoleh nilai recall sempurna (1.00) untuk lalu lintas normal (Benign), serta nilai F1-score yang sangat tinggi untuk serangan DDoS (0.99) dan DoS (0.99). Kinerja yang stabil dan konsisten di seluruh lima putaran federasi membuktikan bahwa pendekatan ini merupakan solusi yang andal, efisien, dan akurat untuk mendeteksi ancaman pada jaringan IoT yang bersifat terdistribusi dan menjaga privasi (privacy-preserving).
Kata kunci: cnn; federated_learning; ids; non-iid; ciciot2023
Abstract:Abstract: The advancement of network security faces growing challenges as cyberattacks become more sophisticated. Traditional rule-based systems struggle with zero-day attacks and obfuscation techniques. This study examines…
nes the development trends of AI-based algo-rithms, particularly machine learning and deep learning, in threat detection. A literature review evaluates AI-driven approaches, including support vector machines, random for-est, deep neural networks, convolutional neural networks, and reinforcement learning. Findings show that AI enhances detection accuracy, adaptability, and reduces false posi-tives. Machine learning efficiently classifies known attacks, while deep learning excels in identifying complex patterns such as distributed denial-of-service and advanced persis-tent threats. Unsupervised learning improves anomaly detection without labeled data. However, AI models require high-quality data, substantial computational resources, and remain vulnerable to adversarial attacks. Despite these challenges, AI provides a dynam-ic and adaptive security solution, surpassing traditional systems. Future research should enhance AI scalability and resilience for evolving cybersecurity threats.
Keywords: anomaly detection; artificial intelligence; deep learning; machine learning; network security
Abstrak: Perkembangan keamanan jaringan menghadapi tantangan yang semakin besar seiring meningkatnya kompleksitas serangan siber. Sistem berbasis aturan tradisional kesulitan mendeteksi zero-day attack dan teknik penyamaran. Penelitian ini mengkaji tren pengembangan algoritma berbasis AI, khususnya machine learning dan deep learning, dalam deteksi ancaman. Literature review mengevaluasi pendekatan berbasis AI, termasuk support vector machines, random forest, deep neural networks, convolutional neural networks, dan reinforcement learning. Hasil penelitian menunjukkan bahwa AI meningkatkan akurasi deteksi, adaptabilitas terhadap ancaman baru, serta mengurangi false positive. Machine learning efektif mengklasifikasikan serangan yang telah diketahui, sementara deep learning unggul dalam mengenali pola kompleks seperti distributed denial-of-service dan advanced persistent threats. Unsupervised learning meningkatkan deteksi anomali tanpa memerlukan data berlabel. Namun, AI masih bergantung pada data berkualitas tinggi, sumber daya komputasi besar, dan rentan terhadap adversarial attack. Meskipun demikian, AI menawarkan solusi keamanan yang lebih dinamis dan adaptif dibandingkan sistem tradisional. Penelitian selanjutnya perlu difokuskan pada peningkatan skalabilitas dan ketahanan AI dalam menghadapi ancaman siber yang terus berkembang.
Kata kunci: deteksi anomali; jaringan keamanan; kecerdasan buatan; pembelajaran dalam; pembelajaran mesin
Abstract:Abstract: The background of this research is that some of the risks of using technology that are classified as dangerous are often ignored by users of the monitoring system for learning activities at private universities…
so that there are several obstacles such as not being able to open the system because the system is hacked by irresponsible parties, the computer network used is often disrupted so that hampers the operational process, and the level of computer security is still relatively weak. This study aims to measure the likelihood of threats and risk impacts on the teaching and learning activity monitoring system and to provide recommendations for risk control of security problems that could become a threat that causes losses to universities. The framework used as a tool to measure the level of threat and risk impact is to use the NIST Special Publication 800-30r-1 framework. The framework of the NIST Special Publication 800-30r-1 has nine phases in carrying out risk assessments, namely introduction of system characteristics, recognition of threats, recognition of vulnerabilities, analysis of handling systems, determining likelihood, determining impact, risk determination, recommending control and determination of results. There are six risk assessment systems for monitoring learning activities at private universities, two of which are high so they are classified as very dangerous and the rest are moderate. The results of this study are used as a reference in making risk control standard documents as a form of improving the quality of a private university.
Keywords: Monitoring System; NIST Spesial Publication 800-30r1; Risk Assessment.
Abstrak: Latarbelakang penelitian ini adalah resiko penggunaan teknologi yang tergolong berbahaya sering tidak dihiraukan oleh pengguna sistem monitoring kegiatan belajar pada perguruan tinggi swasta sehingga terjadi beberapa kendala seperti tidak bisa membuka sistem karena sistem diretas oleh pihak yang tidak bertanggung jawab, jaringan komputer yang digunakan sering terganggu sehingga menghambat proses operasional, serta tingkat keamanan komputer yang masih tergolong lemah. Penelitian ini mempunyai tujuan yaitu mengukur seberapa besar kemungkinan terjadi ancaman dan dampak resiko terhadap sistem monitoring kegiatan belajar mengajar serta memberikan rekomendasi pengendalian resiko dari permasalahan keamanan yang bisa menjadi suatu ancaman yang menimbulkan kerugian pada perguruan tinggi. Framework yang digunakan sebagai alat untuk mengukur tingkat ancaman dan dampak resiko adalah menggunakan kerangka kerja NIST Special Publication 800-30r-1. Kerangka kerja NIST Special Publication 800-30r-1 ini mempunyai sembilan fase dalam melakukan penilaian resiko yaitu pengenalan karakteristik sistem, pengenalan ancaman, pengenalan kerentanan, analisis penanganan sistem, menentukan kemungkinan terjadi (likelihood), menentukan dampak (impact), risk determination, merekomendasikan pengendalian dan penetapan hasil. Penilaian resiko sistem monitoring kegiatan belajar pada perguruan tinggi swasta ada enam resiko yang dua diantaranya termasuk tinggi sehingga digolongkan sangat berbahaya dan selebihnya termasuk sedang. Hasil dari penelitian ini digunakan sebagai acuan dalam pembuatan dokumen standar pengendalian resiko sebagai bentuk peningkatan mutu suatu perguruan tinggi swasta.
Kata kunci: NIST Spesial Publication 800-30r; Penilaian Resiko; Sistem Monitoring
Abstract:The teaching profession plays a strategic role in advancing national education, as mandated by the 1945 Constitution of the Republic of Indonesia. However, teachers frequently face challenges, including threats of physical…
al violence from students’ parents, which undermine their dignity and safety in the educational environment. This study addresses the problem of how legal frameworks provide protection for teachers and whether existing regulations adequately ensure their rights and security. The research aims to analyze the effectiveness of legal protection for teachers under the Criminal Code, Law No. 14 of 2005 on Teachers and Lecturers, Law No. 35 of 2014 on Child Protection, and Ministerial Regulations concerning teacher protection. The study employs a normative juridical method with a statute, conceptual, and case approach, relying on primary, secondary, and tertiary legal materials, analyzed through qualitative interpretation and juridical argumentation. The results indicate that although legal instruments exist, their implementation remains weak due to the absence of technical regulations, limited institutional coordination, and insufficient support systems for teachers at the school level. The study concludes that derivative regulations and integrated mechanisms are essential for ensuring effective protection. It recommends strengthening inter-agency coordination, establishing school-level protection units, and enhancing teachers’ legal literacy.