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All Journal Nuansa Informatika JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Informatika Terpadu Digital Transformation Technology (Digitech) Jurnal Ilmiah Ilmu Terapan Universitas Jambi
Dedek Julian
Universitas Bina Darma
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Library & Information Science

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Perencanaan SOP Manajemen Insiden DPMPTSP Kabupaten OKI Menggunakan Framework ITILv3 Dedek Julian; Tata Sutabri
NUANSA INFORMATIKA Vol 17, No 1 (2023)
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/fkom uniku.v17i1.7203

Abstract

Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu (DPMPTSP) telah menerapkan pelayanan berbasis TI dengan pengadaan aplikasi berbasis website yang mendukung jalannya proses pelayanan kepada masyarakat. Dengan kondisi tersebut, diperlukan manajemen insiden karena rentannya perangkat TI serta data dan informasinya, salah satu panduan manajemen insiden yang berstandar internasional adalah ITIL V3 yang merupakan kumpulan praktik terbaik dari ITSM. Penelitian ini berfokus kepada domain service operation dengan sub-domain incident management dari ITIL. Pada tahapan metode penelitian, dilakukan analisa gap, sehingga dapat dilihat kesenjangan kondisi saat ini dengan kondisi ideal berdasarkan ITILv3. Hasil akhir penelitian mengusulkan beberapa SOP yang lebih jelas dan terstruktur, yaitu SOP penanganan insiden, eskalasi insiden, dan penutupan insiden.
Perancangan UI/UX Aplikasi Forum Diskusi Mahasiswa Universitas Bina Darma Dengan Menerapkan Metode Design Thinking Dedek Julian; Tata Sutabri; Edi Surya Negara
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 6 No. 1 (2023): Jutikomp Volume 6 Nomor 1 April 2023
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v6i1.3579

Abstract

Information on academic activities at Bina Darma University can be obtained via WhatsApp messages to PPM, however, these contacts can only be contacted according to working hours, while students need a medium to exchange information quickly. Student discussion forum applications can meet these needs, where fellow students can exchange information without being limited by time, principal, or semester. The UI/UX design of the student discussion forum application was carried out by applying the Design Thinking method by going through the stages of empathize, define, ideate, prototype, and test. In the design process, gestalt principles are also applied to increase user convenience in using the application. The usability testing results show that 60% of respondents stated that the application was easy to use, while 30% said it was straightforward, and the remaining 10% said it was quite easy to use.
Perbandingan Kinerja Aplikasi Pengembalian Data Untuk Digital Forensik Dengan Metode National Institute of Standards and Technology Dedek Julian; Adi Wijaya; Tata Sutabri
Digital Transformation Technology Vol. 3 No. 1 (2023): Artikel Periode Maret Tahun 2023
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v3i1.2727

Abstract

Kejahatan digital seperti pencurian data perusahaan dapat diantisipasi dengan meningkatkan keamanan sistem, sementara untuk kasus yang sudah terjadi, harus dilakukan analisis dan investigasi dalam mengungkapkan bukti-bukti kejahatan digital atau yang disebut sebagai digital forensik. Penelitian ini menguji coba 5 aplikasi pengembalian data untuk mendapatkan kembali bukti digital dari skenario kasus kejahatan pencurian data melalui flashdisk yang telah diformat, 5 aplikasi tersebut adalah autopsy, recuva, stellar, puran dan easus. Metode yang digunakan adalah metode National Institute of Standards and Technology (NIST), dengan tahapan dimulai dari collection, examination, analysis dan reporting. Tahapan tersebut dilaksanakan dengan barang bukti berupa flashdisk yang telah di isi 6 file sebagai bukti digital yang perlu dicari. Hasil akhir penelitian menunjukkan bahwa tools autopsy berhasil mengembalikan sebanyak 83% dari file yang di uji coba, sementara aplikasi recuva, puran dan easus sebanyak 66%, dan aplikasi stellar sebanyak 33%.
Analisa Kinerja Aplikasi Digital Forensik Autopsy untuk Pengembalian Data menggunakan Metode NIST SP 800-86 Dedek Julian; Tata Sutabri
Jurnal Informatika Terpadu Vol 9 No 2 (2023): September, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v9i2.984

Abstract

One example of digital crime that often occurs is data theft, such as transaction information, and important company data. The thief will delete files to remove traces so that it is necessary to search for and restore data that has been deleted to be used as digital evidence. This activity is usually called digital. forensics. Paid digital forensic applications are sold at quite expensive prices, so one alternative is Autopsy, which is an open source based investigation application that can restore data. This research aims to analyze the performance of the autopsy application in returning 70 files including documents, videos and images as digital evidence based on the crime case scenario of data theft with formatted flash disks. NIST SP 800-86 was chosen as the research method because it has simple stages and is in accordance with the research theme. The stages in this method start from collecting evidence, analyzing the contents of the flash disk with the autopsy application, searching for and returning the found files, to validating the files with hash compare. The analysis report shows that the autopsy application succeeded in returning 81.42% of the data that had been deleted and could be used as evidence based on the crime case scenario that had been created. The files that were successfully returned were 10 DOCX, 10 XLSX, 10 PDF, 6 TXT, 1 MP3, 10 MP4, and 10 PNG.
COMPARING DEEP LEARNING AND MACHINE LEARNING FOR DETECTING FAKE NEWS ON SOCIAL MEDIA Ria Andryani; Dedek Julian; Rezki Syaputra; Ahmad Syazili; Ahmad Rusli; Rahmat Ramadan; Edi Surya Negara
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 3 (2025): Volume 9, Nomor 3, September 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i3.46370

Abstract

One of the critical issues resulting from the increasing penetration of social media is the spread of fake news. This can damage public information and influence mass opinion, leading to conflict. To overcome this problem, machine learning and deep learning-based approaches have been continuously developed to detect fake news on various social media platforms automatically. This article aims to compare the effectiveness of these two approaches in detecting fake news. The methods used include the implementation of traditional machine learning algorithms, such as Support Vector Machines (SVM) and Random Forest, as well as deep learning-based approaches, including Long Short-Term Memory and Self-Organizing Maps. Datasets containing real and fake news from various social media sources are used to train and evaluate these models. Model performance is measured based on accuracy, precision, recall, and F1-score. This study aims to determine which approach is more effective and identify challenges in implementing these algorithms in a dynamic social media environment. The results obtained show that the Random Forest algorithm achieves an accuracy level of 100%, surpassing other algorithms, including Long Short-Term Memory with an F-1 Score of 97%, Self-Organizing Map with an F-1 Score of 96%, and Support Vector Machine with an F-1 Score of 92%.
Co-Authors Adi Wijaya Ahmad Rusli Ahmad Syazili Andryani, Ria Edi Surya Negara Rahmat Ramadan Rezki Syaputra Tata Sutabri