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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Multidisciplinary Sustainability Asean
Fakhri, La Jupriadi
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Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Physics Public Health Other

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Investigasi File Carving pada Media Penyimpanan Menggunakan Framework Computer Forensic Investigative Process Fakhri, La Jupriadi; Riadi, Imam; Yudhana, Anton
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6125

Abstract

One of the uses of digital storage media in the digital era that is still popular today is the use of flash drives as a means of transferring data between computer devices. Flash disks are often used as evidence in digital investigation cases. The risk of losing data is one of the main problems that society often faces. Data loss occurs for various reasons, such as user error, device failure, malware attack, or criminal acts such as hacking. The file carving technique is used to recover lost or deleted files from digital storage media with Foremost software. However, with so many file types, it is sometimes difficult to choose which file types to recover and how to ensure the authenticity of the files. This study uses the Computer Forensic Investigative Process (CFIP) Framework on a flash drive, which is used as evidence in a criminal case. Foremost software is used to perform file carving techniques on flash drives. The results showed that the data acquisition process using DC3DD succeeded in producing digital evidence with a hash value that is identical to the original file. Foremost software successfully recovered various file types, such as 9 image files with jpg file type, 5 audio files with mp3 file type, and 5 document files with pdf file type. Foremost shows a high success rate, with file carving accuracy of 90% for image files, and 62.5% for audio files and documents. The average success rate of Foremost software in returning evidence is 73.08%.
PENGENALAN ARTIFICIAL INTELLIGENCE KEPADA SISWA DI SMA NEGERI 9 SAMARINDA Fawait, Aldi Bastiatul; Rahmah, Sitti; Sugiarto, Sugiarto; Fakhri, La Jupriadi; Jamil, Muh; Saputra, Yudhi Fajar; Arifin, Merlina Lidiana; Saputri, Nadia Keril
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 6 (2024): Vol. 5 No. 6 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i6.38605

Abstract

Kegiatan pengabdian pada masyarakat yang melibatkan sosialisasi mengenai Pengenalan Artificial Intelligence (AI) kepada siswa di lingkungan Sekolah Menengah Atas ini bertujuan untuk memberikan informasi kepada siswa-siswi SMA Negeri 9 Samarinda mengenai perkembangan teknologi terkait AI. Dalam proses sosialisasi ini, tujuannya adalah memberikan pemahaman mengenai kecerdasan buatan yang dirancang khusus untuk menangani permasalahan kognitif yang umumnya terkait dengan kecerdasan manusia, seperti proses pembelajaran, pemecahan masalah, dan pengenalan pola. Manfaat dari kegiatan pengabdian pada masyarakat ini adalah agar siswa-siswi dapat lebih memahami kemajuan teknologi kecerdasan buatan di Indonesia dan memanfaatkan Sumber Daya Manusia (SDM) lokal yang berkualitas, seiring dengan pemahaman bahwa SDM dalam negeri tidak kalah dengan SDM luar negeri. Selain itu, diharapkan bahwa keberadaan Artificial Intelligence dapat berkontribusi dalam pengembangan SDM di negara Indonesia. Hasil Pengabdian Pengenalan Artificial Intelligence Kepada Siswa di Lingkungan Sekolah Menengah Atas pada SMA 9 Negeri Samarinda dilakukan selama satu hari yang dihadiri oleh 34 peserta, 2 orang dosen, dan dibantu oleh mahasiswa program studi Ilmu Komputer Universitas Widyagama Samarinda hasil angket dari peyelenggaraan pengabdian ini didapatkan 7 pertanyaan yang hasilnya diatas 80% peserta yang artinya peserta setuju telah mendapat pengetahuan Pengenalan Artificial Intelligence dengan baik atau penyelenggaraan ini sudah dilaksanakan dengan sangat baik sekali.
The ANFIS Model Approach in Classifying the Characteristics of Children with Special Needs at SLB in Southwest Papua Ermin; Fakhri, La Jupriadi; Aliama, Fisal
Jurnal Penelitian Pendidikan IPA Vol 11 No 10 (2025): October
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i10.12978

Abstract

Special Elementary Education (SDLB) has a strategic role in providing equal access to education for Children with Special Needs (ABK). Observations at one of the Special Needs schools (SLB) in Southwest Papua show that the initial assessment process of ABK characteristics based on age, IQ, and motor skills has not been effective. This study aims to develop a system based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) model to assist the initial classification process of ABK characteristics and support initial assessments at school. The ANFIS model is used to study the nonlinear relationship between input variables and classification results. Testing is carried out using validated data to assess the level of accuracy and consistency of the model. The results show that the ANFIS model-based system has an accuracy level of 85.7% with stable predictive capabilities on most of the test data. These findings show that the integration of ANFIS into a web-based system can be an effective tool for teachers in conducting initial assessments, so that the process of identifying ABK characteristics can be carried out more quickly, objectively, and efficiently.
Implementation of Artificial Intelligence in Cybersecurity Crisis Management Bastiatul Fawait, Aldi; Fakhri, La Jupriadi; Muslimah, Virasanty
Journal of Multidisciplinary Sustainability Asean Vol. 1 No. 6 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v1i6.1776

Abstract

Background. The growing complexity of cybersecurity threats has led to an increasing demand for faster and more efficient solutions. As cyber threats evolve in sophistication, the implementation of Artificial Intelligence (AI) in cybersecurity crisis management has become highly relevant. AI’s ability to process vast amounts of data quickly and detect patterns that may be undetectable to human operators offers significant potential in combating cybercrime and cyberattacks. Purpose. This study aims to evaluate how AI can enhance the effectiveness of cybersecurity by improving the detection and response to cyber threats. Specifically, the research focuses on understanding AI's role in identifying potential threats more quickly and responding with greater efficiency compared to traditional methods. Method. The research employs a mixed-method approach, combining quantitative data analysis and qualitative interviews. Quantitative data were gathered from cyberattack simulations to measure AI’s effectiveness in detecting and responding to various types of cyber threats. Additionally, qualitative interviews were conducted with cybersecurity experts to gather insights into AI’s practical applications and limitations in real-world scenarios. Results. The findings show that AI significantly accelerates threat detection, improving the overall response efficiency with a success rate of up to 85%. AI is also capable of analyzing large datasets in a short period, enabling faster identification of vulnerabilities and potential threats. However, AI still faces limitations in handling unexpected and novel types of cyberattacks, indicating that it cannot entirely replace human expertise. Conclusion. While AI offers numerous advantages in the field of cybersecurity, it must be integrated with human expertise to address its limitations effectively. AI technology should be continuously updated to adapt to emerging threats. This study contributes to the understanding of AI’s strategic role in cybersecurity and provides valuable direction for further research aimed at overcoming the technology’s weaknesses in threat management.
Co-Authors Aldi Bastiatul Fawait Fawait Aliama, Fisal Anton Yudhana Arifin, Merlina Lidiana Bastiatul Fawait, Aldi Ermin Ermin Imam Riadi Jamil, Muh Saputra, Yudhi Fajar Saputri, Nadia Keril Sitti Rahmah Sugiarto S Virasanty Muslimah