Article Per Year (5 Year)
p-Index From 2021 - 2026
3.615
P-Index
This Author published in this journals
All Journal Jurnal Cita Hukum JOSIKOM : Jurnal Online Sistem Komputer Jurnal Al-Tadzkiyyah Abjadia, International Journal of Education Al-Daulah : Jurnal Hukum dan Perundangan Islam IJoASER (International Journal on Advanced Science, Education, and Religion) Ta'dib: Jurnal Pendidikan Islam At-Tarbawi : Jurnal Pendidikan, Sosial dan Kebudayaan Jurnal Teknik Industri Terintegrasi (JUTIN) Jurnal Manajemen Pendidikan dan Ilmu Sosial (JMPIS) Khazanah Intelektual Indonesian Journal of International Law Journal of Applied Nursing and Health Jurnal Al-Qiyam Jurnal Tana Mana Journal International of Lingua and Technology Journal International Inspire Education Technology (JIIET) Khaira Ummah: Jurnal Pengabdian Kepada Masyarakat International Journal of Emerging Issues in Islamic Studies Interaction, Community Engagement, and Social Environment Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Asian Journal of Social and Humanities Journal of Moeslim Research Technik
Muhammad Mustofa
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Veterinary Other

Published : 32 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 32 Documents
Search

 1   2   3   4 
Kebijakan Pemerintah Dalam Program Daerah Peduli HAM di Provinsi Jambi martin, joni; Mustofa, Muhammad; Ermasdon, Ermasdon; Arsyad, Arzi; Noviyanti, Noviyanti; Yuli Astuti, Diana; Siregar, Anhar; Arif fadly, Muhammad; Ridho Saputro, Muhammad; Saniati, Saniati; Kurniawan, Ade
Jurnal Khazanah Intelektual Vol. 8 No. 2 (2024): Khazanah Intelektual
Publisher : Brida Provinsi Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Changes in the criteria for Human Rights Care based on Permenkumham number 22 of 2021 have caused many districts/cities to not get the status of Regency/City Caring for Human Rights, the number of regions that care about human rights decreased from 2020 and 2022. This evaluation aims to provide an overview of the implementation of Permenkum HAM Number 22 of 2021 in Jambi Province and what are the obstacles faced in its implementation as well as the relevance, sustainability and effectiveness of MMAF HAM programs/activities, in Jambi Province. Evaluation using an evaluative research approach using the Goal-freeevaluation model, descriptive analysis, evaluation carried out in Jambi Province with samples of Legal Bureaus and Legal Sections of Province/District/City Setda. From the results of the analysis, it is known that the process/mechanism for implementing the fulfillment of the Human Rights KKP Criteria in Jambi Province has run well, and is in accordance with the scheme that has been stipulated in the guidelines for the implementation of the Human Rights MMAF. However, there are several obstacles in its implementation such as a long and costly reporting mechanism; supporting data that is difficult to meet; the officer's lack of understanding of the form and supporting data; still not optimal socialization and technical guidance; and MMAF HAM activities have not become regional priority activities, which have an impact on budget availability in their implementation, from the results of the analysis also obtained several notes on the relevance, sustainability and effectiveness of MMAF HAM programs / activities in Jambi Province in the future, namely on the fulfillment of data supporting the right to legal aid and the right to diversity and pluralism these two aspects are partly difficult to fulfill in Jambi Province because they are hit by the availability of regulations. However, this does not significantly affect the sustainability and effectiveness of KKPHAM activity programs in Jambi province in the future. Keywords: Human Rights, Human Rights Care Criteria, Jambi
Effectiveness of Deep Learning Models in Cybercrime Prediction Mustofa, Muhammad; Akhtar, Shazia; Vandika, Arnes Yuli
Journal of Moeslim Research Technik Vol. 1 No. 5 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v1i5.1561

Abstract

The rise of cybercrime poses significant challenges to security agencies and organizations worldwide. Traditional methods of crime prediction often fall short in accurately identifying potential threats. As a result, there is a growing interest in leveraging advanced technologies, such as deep learning, to enhance predictive capabilities in cybersecurity. This research aims to evaluate the effectiveness of deep learning models in predicting cybercrime incidents. The study investigates how these models can improve accuracy and reliability compared to conventional prediction techniques. A dataset comprising historical cybercrime incidents was collected and preprocessed to extract relevant features. Various deep learning architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), were implemented. The models were trained and validated using a portion of the data, while performance metrics such as accuracy, precision, recall, and F1-score were used to assess their predictive capabilities. The findings indicate that deep learning models significantly outperform traditional methods in predicting cybercrime incidents. The best-performing model achieved an accuracy of 92%, showcasing its ability to identify complex patterns in the data. Additionally, deep learning models demonstrated lower false positive rates, enhancing their reliability in real-world applications. The research concludes that deep learning is a powerful tool for predicting cybercrime, offering enhanced accuracy and efficiency. These findings contribute to the field by highlighting the potential of advanced machine learning techniques in improving cybersecurity measures. Future work should focus on refining these models and exploring their applicability in real-time cyber threat detection.
Co-Authors Addzaky, Khoirul Umam Ade Kurniawan Ady Prabowo, Iwan Agus Susanti Akhtar, Shazia Amrullah Amrullah Angglena, Melly Anjani, Huly Luthfi Selfia Antariksawan, Rudi Anzanni, Aulia Adhitiya Arif fadly, Muhammad Arifin, Andieni Putri Olivia Arifin, Syaadiah Arnes Yuli Vandika Arsyad, Arzi Chairul Anwar Costa, Tiago Desma Ayu Kusuma Wardani, Frisca Dewi Pratiwi Dhumilah, Dewic Sri Ratnaning Dina Amalia Ermasdon, Ermasdon Galuh Kumalasari Hari Alijana, Erma Heru Juabdin Sada Hetiyasari Hijriyyah, Umi I Gede Suardika I Wayan Budi Sentana, I Wayan Istihana Istihana Juliantika, Juliantika Kemal Dermawan, Mohammad Kristiawanto, Kristiawanto Kukuh Dwi Wijanarko Laia, Aturkian Loebis, Iin Almeina Maris Bakara, Stella martin, joni Mas Ahmad Yani Mohammad Irvan Olii Noviyanti Noviyanti, Noviyanti Ridho Saputro, Muhammad Rijal Firdaos Rizka Febriani Sa'idy, Sa'idy Salim, Yeffriansjah Saniati, Saniati Shodiq, Md. Silva, Pedro Siregar, Anhar Siti Zulaikhah Suminah Tandyasraya, Renisa Ulya Fuhaidah, Ulya Umi Hijriyah Wijayanto, Hendro Willie Japaries Yuli Astuti, Diana Yusuf Hasibuan, Fauzie