Abstract:Abstract: This community service activity focuses on increasing digital literacy as an effort to support digital transformation in the Industry 5.0 era. This program is designed to provide training and seminars to employees…
ees of PT Flextronics Technology Indonesia Batam to improve their understanding and skills in utilizing digital technology effectively in the world of work. Through this activity, participants are given insight into the use of digital technology in business operations, cybersecurity, personal data protection, and the application of artificial intelligence (AI) in industry. This training also includes practical skills such as data analysis, use of digital business software, and e-commerce optimization. So this activity aims to support digital transformation in the Industry 5.0 era by increasing people's understanding and skills in utilizing digital technology. The target of this program is for company employees to be able to optimize technology in business activities, increase productivity, and innovate in the digital era. With this approach, it is hoped that participants can improve work efficiency, competitiveness, and the ability to adapt to technological developments.
Keywords: digital literacy; digital economy; artificial intelligence (AI)
Abstrak: Kegiatan pengabdian kepada masyarakat ini berfokus pada peningkatan literasi digital sebagai upaya mendukung transformasi digital di era Industri 5.0. Program ini dirancang untuk memberikan pelatihan dan seminar kepada karyawan PT Flextronics Technology Indonesia Batam guna meningkatkan pemahaman dan keterampilan mereka dalam memanfaatkan teknologi digital secara efektif dalam dunia kerja. Melalui kegiatan ini, peserta diberikan wawasan mengenai pemanfaatan teknologi digital dalam operasional bisnis, keamanan siber, perlindungan data pribadi, serta penerapan kecerdasan buatan (AI) dalam industri. Pelatihan ini juga mencakup keterampilan praktis seperti analisis data, penggunaan perangkat lunak bisnis digital, dan optimalisasi e-commerce. Sehingga kegiatan ini bertujuan untuk mendukung transformasi digital di era Industri 5.0 dengan meningkatkan pemahaman dan keterampilan masyarakat dalam memanfaatkan teknologi digital. Metode yang digunakan dalam kegiatan Pengabdian masyarakat adalah metode edukasi berupa penyuluhan dengan ceramah dan diskusi. Sasaran program ini adalah para karyawan perusahaan agar dapat mengoptimalkan teknologi dalam aktivitas bisnis, meningkatkan produktivitas, serta berinovasi di era digital. Dengan pendekatan ini, diharapkan peserta dapat meningkatkan efisiensi kerja, daya saing, serta kemampuan beradaptasi dengan perkembangan teknologi.
Kata kunci: literasi digital; ekonomi digital; artificial intelligence (AI)
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:This community service aims to improve digital literacy of students at SMK Negeri 1 Setia Janji through training in safe and effective internet use. Digital literacy is an essential skill in today's digital era, especially…
ly for Vocational High School (SMK) students who will enter the workforce directly. However, the low understanding of wise internet use, as well as the rampant misuse of digital media, are serious challenges that need to be overcome. The method used in this activity is a hands-on training approach that includes materials on digital ethics, cybersecurity, online information management, and the use of the internet for learning and self-development. The results of the activity showed a significant increase in students' understanding and skills related to safe and effective internet use. Thus, this training has proven effective in improving students' digital literacy and can be used as a model for developing digital competencies in other school environments.
Keywords: digital literacy; safe internet; training; vocational high school students
Abstrak: Pengabdian ini bertujuan untuk meningkatkan literasi digital siswa SMK Negeri 1 Setia Janji melalui pelatihan penggunaan internet secara aman dan efektif. Literasi digital merupakan keterampilan esensial dalam era digital saat ini, terutama bagi siswa Sekolah Menengah Kejuruan (SMK) yang akan terjun langsung ke dunia kerja. Namun, rendahnya pemahaman tentang penggunaan internet secara bijak, serta maraknya penyalahgunaan media digital, menjadi tantangan serius yang perlu diatasi. Metode yang digunakan dalam kegiatan ini adalah pendekatan pelatihan berbasis praktik langsung (hands-on training) yang mencakup materi tentang etika digital, keamanan siber, manajemen informasi online, serta pemanfaatan internet untuk pembelajaran dan pengembangan diri. Hasil kegiatan menunjukkan adanya peningkatan signifikan dalam pemahaman dan keterampilan siswa terkait penggunaan internet yang aman dan efektif. Dengan demikian, pelatihan ini terbukti efektif dalam meningkatkan literasi digital siswa dan dapat dijadikan model pengembangan kompetensi digital di lingkungan sekolah lainnya.
Kata kunci: Internet aman; literasi digital; Pelatihan; Siswa SMK
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 sensitive health data and frequent cyberattacks, securing electronic medical records (EMR) has become a critical challenge. This study proposes a hybrid encryption framework combining Affine and AES…
ES algorithms with an AI-based key management module to enhance EMR security while maintaining efficiency. A dataset of 1,000 simulated records was evaluated using five cryptographic configurations: Affine-only, AES-only, RSA-only, Affine–AES, and Affine–AES with AI. Performance was measured through encryption/decryption latency and ciphertext size, while security was assessed under brute-force, SQL injection, and phishing simulations. The AI decision tree for key generation was evaluated using accuracy, precision, recall, F1-score, and entropy metrics. Results show that the AI-enhanced hybrid method eliminates brute-force success, introduces only minor latency overhead, and generates high-entropy keys with reliability above 98%. These findings indicate that integrating AI-based dynamic key regeneration into hybrid encryption can improve EMR security while remaining practical for clinical and cloud-based healthcare systems. Future work should involve real clinical datasets and explore post-quantum cryptographic extensions.
Keywords: AI key management; attack resistance; encryption performance; electronic medical records; hybrid encryption
Abstrak: Di era meningkatnya sensitivitas data kesehatan dan maraknya serangan siber, perlindungan Rekam Medis Elektronik (RME) menjadi tantangan penting. Penelitian ini mengusulkan kerangka enkripsi hibrida yang menggabungkan algoritma Affine dan AES dengan modul manajemen kunci berbasis AI untuk meningkatkan keamanan RME tanpa mengorbankan efisiensi. Dataset simulasi berisi 1.000 entri diuji menggunakan lima konfigurasi kriptografi: Affine-only, AES-only, RSA-only, Affine–AES, serta Affine–AES dengan AI. Performa diukur melalui latensi enkripsi/dekripsi dan ukuran ciphertext, sedangkan keamanan dievaluasi melalui simulasi serangan brute force, SQL injection, dan phishing. Model decision tree untuk manajemen kunci dinilai menggunakan metrik akurasi, presisi, recall, F1-score, dan entropi. Hasil menunjukkan bahwa metode hibrida dengan AI menghilangkan keberhasilan brute force, menambah overhead latensi yang minimal, serta menghasilkan kunci berentropi tinggi dengan reliabilitas di atas 98%. Temuan ini menunjukkan bahwa regenerasi kunci dinamis berbasis AI dalam skema enkripsi hibrida dapat meningkatkan keamanan RME sekaligus tetap praktis untuk sistem klinis dan layanan kesehatan berbasis cloud. Penelitian selanjutnya disarankan menggunakan dataset klinis nyata dan mengeksplorasi kriptografi pascakuantum.
Kata kunci: enkripsi hibrida; ketahanan serangan; kinerja enkripsi; manajemen kunci berbasis AI; rekam medis elektronik
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:Cybercrime has become a serious challenge in the digital age, requiring a dynamic legal approach to respond to this threat. This study aims to investigate legal developments in the application of criminal sanctions against…
st cybercrimes. Through a critical analysis of various cases and regulatory developments, this study will explore the effectiveness of criminal sanctions applied in tackling cybercrime.
This research method includes comparative law analysis, case studies, and interviews with criminal law experts. Research findings will include the evolution of the concept of cybercrime, the legal challenges faced in enforcing criminal sanctions, and the impact of the application of criminal law on cybersecurity levels
The results of this study are expected to provide in-depth insight into the progress of criminal law in responding to cybercrime, as well as provide a basis for further improvement and development in the relevant legal framework. The practical implications of this research are expected to help authorities, legal professionals, and academics in understanding the dynamics of criminal law related to cybercrime, so as to formulate policies that are more effective and responsive to evolving cybersecurity threats.