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All Journal Scientific Journal of Informatics Jurnal Penelitian Pendidikan IPA (JPPIPA) ILKOM Jurnal Ilmiah Antivirus : Jurnal Ilmiah Teknik Informatika bit-Tech Community Development Journal: Jurnal Pengabdian Masyarakat TRANSFORMASI : JURNAL PENGABDIAN PADA MASYARAKAT Journal of Multidisciplinary Sustainability Asean
La Jupriadi Fakhri
Universitas Muhammadiyah Sorong
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Physics Public Health Social Sciences Other

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Forensic Tools Comparison on File Carving using Digital Forensics Research Workshop Framework La Jupriadi Fakhri; Imam Riadi; Anton Yudhana
Scientific Journal of Informatics Vol 10, No 4 (2023): November 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i4.46901

Abstract

Purpose: Cybercrime is the misuse of technology as a tool or medium in committing crimes such as hacking, stealing, deleting, hiding, and destroying information. Cybercriminals tend to delete, hide, and format all the data collected to eliminate traces of digital evidence. In digital forensics, file carving techniques can overcome data loss from storage media. This study aims to determine the results of the file carving process in uncovering digital evidence and evaluating the performance of digital forensic software, including Foremost and Scalpel, based on 3 assessment parameters.Methods: In this investigation, the Digital Forensics Research Workshop (DFRWS) research method is used with the following stages: Identification, Preservation, Collection, Examination, Analysis, and Presentation. Results: Comparison results of the data obtained from Foremost and Scalpel forensic tools are based on three primary parameters including the speed of the recovery process, the number of successfully recovered files, and the identical hash value. The Foremost tool managed to recover the carving files in 1 minute and 3 seconds, showing a success rate of 85% with a hash value similarity rate of 70.59%. On the other hand, Scalpel recovered the carving file in 2 minutes 17 seconds, achieving a success rate of 65% with a hash value similarity rate of 7.69%.Novelty: This data results from the performance of both forensic tool applications in collecting digital evidence from Flash disk storage media.
Digital Leadership Transformation in the Modern Era: Empowering Aisyiyah Mothers through Social Media Faroek, Dewi Astria; Ermin, Ermin; Rezki, Rezki; Muslimah, Virasanty; Fakhri, La Jupriadi; Miswar, Nur
TRANSFORMASI : JURNAL PENGABDIAN PADA MASYARAKAT Vol 4, No 3 (2024): Desember
Publisher : UNIVERSITAS MUHAMMADIYAH MATARAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/transformasi.v4i3.28119

Abstract

The community service program is an activity carried out to contribute to the community directly with the main objective of increasing understanding to the participants about digital leadership and providing direct training in the use of social media as a medium for da'wah. This activity was held at Nawa Flat, Sorong City, on September 16, 2024, attended by 30 Aisyiyah women participants. This activity was carried out offline in one meeting session using material delivery using the lecture method, question and answer sessions and direct training on the use of social media as a preaching medium using the Tiktok and Canva applications. The results obtained show an increase in participants' understanding and skills in utilizing digital technology for da'wah purposes. This program has an important meaning in empowering Aisyiyah women to be able to use social media effectively, so that it is expected to expand the reach of da'wah messages in the digital era. 
Comparison of Accuracy Level of Certainty Factor Method and Bayes Theorem on Cattle Disease Setyawan, Muhammad Rizki; Bahari Putra, Fajar Rahardika; Fakhri, La Jupriadi
ILKOM Jurnal Ilmiah Vol 16, No 3 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i3.1943.343-355

Abstract

This study aims to address the challenges of livestock disease diagnosis in Okaba district, Meraoke, Papua. A total of 2 paramedics or veterinarians and 1 assistant is not sufficient because of the long distances that the medics have to travel, traveling from all areas of Okaba District to its interior. Keepers can only utilize their basic skills for temporary care. The researcher's process included interviews with experts covering the disease, its symptoms and prevention, then analyzed with the provision of utilizing certainty factors and Bayes' theorem to increase the accuracy and veracity of the findings. In this scenario, the data is used as a reference point for analysis in the web-based expert system. The results obtained when processing the problem estimation are disease information, symptom information, and treatment. The reference in the application and analysis shows that the Certainty Factor method is superior in providing consistent accuracy, with a percentage reaching 98.79% in the case of worms, while the Bayes Theorem method shows lower accuracy, around 73%. The comparison indicates that Certainty Factor is more suitable in high uncertainty environments, while Bayes' Theorem is more effective when sufficient probabilistic data is available. Future suggestions can expand the scope by testing other methods such as Machine Learning or Artificial Neural Networks to increase the accuracy of the diagnosis percentage. In addition, more extensive trials on different types of livestock and different environmental conditions will help in developing a more flexible and robust system.
ANALISIS KEPUASAN PELANGGAN TRANSPORTASI ONLINE DENGAN PENERAPAN KLASIFIKASI TEKS MENGGUNAKAN METODE KNN Ermin, Ermin; Soekarta, Rendra; Jupriadi Fakhri, La; Jundullah, Muhammad; Retno Irianto, Dwi
Antivirus : Jurnal Ilmiah Teknik Informatika Vol 18 No 2 (2024): November 2024
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/antivirus.v18i2.3994

Abstract

Gojek merupakan transportasi online yang memanfaatkan aplikasi untuk melayani Pengguna (masyarakat). Layanan aplikasi Gojek memiliki layanan yang terbatas pada ojek online. Perkembangan pada jasa layanan didukung dengan pembayaran transaksi non tunai (GoPay), untuk mempermudah trasaksi para pelanggan. Untuk mengklasifikasikan kepuasan pelanggan digunakan metode K-Nearest Neighbor (KNN). Dalam penelitian ini, penggunaan metode KNN dipilih karena sederhana dan intuitif, cocok untuk data teks, dapat menangani data tidak seimbang, dan memiliki kemampuan untuk mengatasi data baru. Selain itu, KNN juga dapat digunakan sebagai baseline yang cukup baik dalam membandingkan performa dengan metode-metode lain dalam klasifikasi kepuasan pelanggan transportasi online berdasarkan ulasan atau komentar. Web yang dibangun menggunakan library dari python yaitu streamlit. Dataset yang digunakan dari penelitian ini adalah data hasil scraping ulasan gojek dari google play store sebanyak 4000 ulasan. Pengujian dilakukan mengambil salah satu ulasan terbaru bintang 1 dan salah satu ulasan bintang 5 yang relevan, Hasil yang didapatkan menunjukan bahwa ulasan tersebut dapat di klasifikasi sebagai puas dan tidak puas dengan nilai akurasi 84,08%.
The ANFIS Model Approach in Classifying the Characteristics of Children with Special Needs at SLB in Southwest Papua Ermin; La Jupriadi Fakhri; Fisal Aliama
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.
PENGENALAN ARTIFICIAL INTELLIGENCE KEPADA SISWA DI SMA NEGERI 9 SAMARINDA Aldi Bastiatul Fawait; Sitti Rahmah; Sugiarto Sugiarto; La Jupriadi Fakhri; Muh Jamil; Yudhi Fajar Saputra; Merlina Lidiana Arifin; Nadia Keril Saputri
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.
Implementation of Artificial Intelligence in Cybersecurity Crisis Management Aldi Bastiatul Fawait; La Jupriadi Fakhri; Virasanty Muslimah
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.
NLP Based Tourism Service Optimization on Multilingual Voice Chatbot Muhammad Jundullah; Ermin Ermin; Muhammad Surahmanto; La Jupriadi Fakhri; Hatari Muslim
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3473

Abstract

The rapid advancement of artificial intelligence has created significant opportunities to enhance tourism services, a vital sector of Indonesia’s economy, particularly in Raja Ampat as a leading ecotourism destination. (R1-1 Background) A persistent challenge in this region is effective communication for homestay management, where limited human resources and linguistic diversity constrain service quality. (R1-1 Methodology) This study evaluates a multilingual voice chatbot integrating Natural Language Processing, Large Language Models, and a Retrieval-Augmented Generation architecture, supporting Indonesian, English, and a virtual local language. System performance is quantitatively assessed using Speech-to-Text accuracy measured by Word Error Rate, intent classification metrics, semantic retrieval effectiveness, and end-to-end evaluation. The proposed pipeline includes speech data collection, text normalization, multilingual embedding, vector storage, semantic retrieval, and response generation. (R1-2 Results) Results show that STT quality strongly determines downstream performance. Indonesian achieves the lowest WER (0.14) and the highest intent F1-score (0.89), while the virtual language records the highest WER (0.25) and the lowest intent F1-score (0.65). The semantic retriever attains a Mean Average Precision of 0.55, indicating moderate document ranking quality. The integrated end-to-end system achieves an F1-score of 0.857 with a user satisfaction score of 4.4. (A-1 Contribution) Compared with existing tourism chatbots, the proposed system uniquely combines multilingual voice interaction with RAG-based grounding to improve response reliability in low-resource settings. (A-2 Conclusion and applicability) These findings demonstrate practical effectiveness for homestay services and highlight scalability to other multilingual tourism regions in Indonesia and beyond.
Co-Authors Aldi Bastiatul Fawait Fawait Anton Yudhana Bahari Putra, Fajar Rahardika Dewi Astria Faroek Ermin Ermin Fisal Aliama Hatari Muslim Imam Riadi Merlina Lidiana Arifin Muh. Jamil Muhammad Jundullah Muhammad Rizki Setyawan Muhammad Surahmanto Nadia Keril Saputri Nur Miswar Retno Irianto, Dwi REZKI, REZKI Sitti Rahmah Soekarta, Rendra Sugiarto Virasanty Muslimah Yudhi Fajar Saputra