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All Journal Scientific Journal of Informatics EMITTER International Journal of Engineering Technology JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Ilmu Komputer dan Desain Komunikasi Visual Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Green Intelligent Systems and Applications Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Submit : Jurnal Ilmiah Teknologi Informasi dan Sains Nusantara Computer and Design Review
Neny Kurniati
Universitas Nahdlatul Ulama Sidoarjo
Arts Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics

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Forensic Analysis of Drones Attacker Detection Using Deep Learning Editya, Arda Surya; Kurniati, Neny; Alamin, Mochammad Machlul; Pramana, Anggay Luri; Lisdiyanto, Angga
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.48183

Abstract

Purpose: This research proposes deep learning techniques to assist forensic analysis in drone accident cases. This process is focused on detecting attacking drones. In this research, we also compare several deep learning and make some comparisons of the best methods for detecting drone attackers.Methods: The methods applied in this research are YOLO, SSD, and Fast R-CNN. Additionally, to validate the effectiveness of the results, extensive experiments were conducted on the dataset. The dataset we use contains videos taken from drones, especially drone collisions. Evaluation metrics such as Precision, Recall, F1-Score, and mAP are used to assess the system's performance in detecting and classifying drone attackers.Results: This research show performance results in detecting and attributing drone-based threats accurately. In this experiment, it was found that YOLOV5 had superior results compared to YOLOV3 YOLOV4, SSD300, and Fast R-CNN. In this experiment we also detected ten types of objects with an average accuracy value of more than 0.5.Novelty: The proposed system contributes to improving security measures against drone-related incidents, serving as a valuable tool for law enforcement agencies, critical infrastructure protection and public safety. Furthermore, this underscores the growing importance of deep learning in addressing security challenges arising from the widespread use of drones in both civil and commercial contexts. 
Studi Quality of Service (QoS) Jaringan Internet Berbasis Wireshark di Lingkungan Ruang Terbuka Publik Ardiansyah, Fitto; Alamin, Mochammad Machlul; Muchibbin, Moch Rafli; Farros, M Faizal Zhafran; Hidayat, Rakmat; M, Baqik Al Zalzala; Kurniati, Neny
Nusantara Computer and Design Review Vol. 3 No. 2 (2025): Nusantara Computer and Design Review
Publisher : LPPM UNUSIDA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/tewbgs61

Abstract

Tujuan dari penelitian ini adalah untuk mengevaluasi kualitas layanan (QoS) jaringan internet di Alun-Alun Sidoarjo dengan menggunakan wireshark. Internet publik semakin dibutuhkan untuk berbagai keperluan, seperti komunikasi, hiburan, dan pekerjaan. Namun, kualitas jaringan di area publik seperti Alun-Alun Sidoarjo masih sering mengalami masalah, seperti koneksi lambat, keterlambatan pengiriman data (latensi), perubahan waktu pengiriman yang tidak stabil (jitter), dan kehilangan data (packet loss). Pada penelitian ini, dilakukan pengukuran langsung terhadap beberapa parameter utama, yaitu throughput, latensi, jitter, dan packet loss pada tiga waktu yang berbeda yakni pagi, siang, dan sore. Hasil analisis menunjukkan bahwa koneksi internet pada siang hari memiliki kecepatan transfer data (throughput) tertinggi sebesar 72 kbps dengan latensi paling rendah (22,8 ms). Sementara itu, pada pagi hari ditemukan jitter negatif (-0,599 ms), yang bisa memengaruhi layanan yang membutuhkan koneksi stabil secara real-time. Pada sore hari, tingkat kehilangan data (packet loss) paling rendah sebesar 0,109%, menunjukkan jaringan yang lebih stabil dibandingkan waktu lainnya. Berdasarkan hasil penelitian ini, kualitas layanan internet di Alun-Alun Sidoarjo masih tergolong cukup baik menurut standar TIPHON, meskipun ada perubahan kualitas pada waktu-waktu tertentu. Oleh karena itu, diperlukan peningkatan infrastruktur jaringan agar koneksi lebih stabil, terutama dalam mengatasi jitter negatif dan menjaga kestabilan kecepatan transfer data di semua waktu. The purpose of this study is to evaluate the quality of service (QoS) of the internet network in Sidoarjo's town square using Wireshark. Public internet is increasingly needed for various purposes, such as communication, entertainment, and work. However, network quality in public areas such as Sidoarjo's town square still often experiences problems, such as slow connections, delayed data transmission (latency), unstable transmission time changes (jitter), and data loss (packet loss). In this study, direct measurements were made of several key parameters, namely throughput, latency, jitter, and packet loss at three different times: morning, afternoon, and evening. The analysis results show that the internet connection during the day has the highest data transfer rate (throughput) of 72 kbps with the lowest latency (22.8 ms). Meanwhile, in the morning, negative jitter was found (-0.599 ms), which can affect services that require a stable connection in real-time. In the afternoon, the data loss rate (packet loss) was lowest at 0.109%, indicating a more stable network compared to other times. Based on the results of this study, the quality of internet service in Sidoarjo's town square is still considered quite good according to TIPHON standards, although there are occasional changes in quality. Therefore, network infrastructure improvements are needed to ensure more stable connections, particularly in addressing negative jitters and always maintaining stable data transfer speeds.
Co-Authors Achmad Basuki Achmad Basuki Anggay Luri Pramana Arda Surya Editya Ardiansyah, Fitto Athika Dwi Wiji Utami Dadet Pramadihanto Farros, M Faizal Zhafran Hidayat, Rakmat Lisdiyanto , Angga Lisdiyanto, Angga M, Baqik Al Zalzala Mochammad Machlul Alamin Muchibbin, Moch Rafli Orizky, Moch. Fahrul Pangarso, Aditya Wisnu Pramana, Anggay Lury Rofiq, M. Ainun Syahri Mu’min Widanarko, Bayu