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All Journal Jurnal Telkommil
Robianto Herdana Sukirno
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Computer Science & IT Control & Systems Engineering Engineering

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Intelligent System for Real-Time Weapon and Combat Equipment Detection Based on Computer Vision for Military Base Security: Rekayasa Keamanan Siber Yudhi Darmawan; Ilyas Hasmi; Robianto Herdana Sukirno
Jurnal Telkommil Vol 6 No 2 (2025): Jurnal Telkommil
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/kom.v6i2.599

Abstract

This research proposes an intelligent security system based on computer vision for real-time detection of weapons and military equipment in guard posts and military bases. The primary objective is to strengthen early warning capabilities by automatically identifying objects resembling firearms, knives, or combat gear through surveillance cameras. The system employs convolutional neural networks (CNN) for object classification and detection, integrated with a real-time alert mechanism to notify security personnel when suspicious items are detected. The method includes dataset collection of various weapon and combat equipment images, preprocessing, model training using YOLOv8, and evaluation with precision, recall, and F1-score metrics. Experimental results demonstrate that the system can accurately recognize specific military-related objects with high detection speed, ensuring reliable performance in real-time monitoring scenarios. The findings highlight the potential application of artificial intelligence in enhancing situational awareness and proactive security measures in military environments. This study concludes that the implementation of computer vision-based intelligent detection systems can significantly improve the effectiveness of base and post security operations, providing timely alerts to prevent potential threats
Analisa Anomali Traffic Log Honeypot di Web Server: Rekayasa Keamanan Siber Yuef Okky Pradana; Jeki Saputra; Robianto Herdana Sukirno
Jurnal Telkommil Vol 6 No 2 (2025): Jurnal Telkommil
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/kom.v6i2.606

Abstract

Dalam era digital yang semakin terhubung, ancaman serangan siber terhadap web server semakin canggih dan sering kali sulit dideteksi dengan sistem keamanan konvensional. Honeypot berbasis AI menawarkan solusi efektif dalam menganalisis serangan dengan memanfaatkan traffic log yang dihasilkan oleh aktivitas penyerang. Penelitian ini bertujuan untuk menganalisis anomali traffic log yang dihasilkan oleh honeypot pada web server, dengan tujuan mendeteksi serangan yang tidak teridentifikasi sebelumnya. Sistem honeypot berbasis AI digunakan untuk mendeteksi serangan, seperti XSS, SQL Injection, dan DDoS, serta menganalisis pola anomali yang terjadi. Hasil penelitian menunjukkan bahwa honeypot berbasis AI dapat mendeteksi serangan lebih cepat dan lebih akurat dibandingkan dengan sistem berbasis signature. Penelitian ini juga mengidentifikasi tantangan dalam analisis log dan pemeliharaan data pada skala besar, serta pentingnya penggunaan cloud computing untuk menangani volume data yang besar.
Browser Extension Endpoint Security Anti Spyware dan Data Exfiltration Berbasis Rule based Java Script : Rekayasa Keamanan Siber ricki2114; Bambang Purwanto; Robianto Herdana Sukirno
Jurnal Telkommil Vol 7 No 1 (2026): Jurnal Telkommil
Publisher : Pustaka Poltekad

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

Abstract

The expansion of web based applications has increased browser side security risks, particularly through malicious Java Script exploitation leading to data exfiltration. Conventional endpoint security mechanisms primarily emphasize network-layer monitoring, leaving client side browser activities less protected. This study proposes a browser extension-based endpoint security solution employing a rule based Java Script monitoring approach to detect spyware behavior and prevent unauthorized data transmission. Using the Research and Development (R&D) methodology, the system was designed, implemented and evaluated through controlled attack simulations. The extension monitors DOM access, local storage usage and outbound HTTP/HTTPS requests based on predefined detection rules. Experimental results across ten simulated scenarios demonstrate an 80% detection rate. The findings indicate that rule based client side monitoring offers a lightweight and practical approach to strengthening browser-level endpoint security.
Co-Authors Bambang Purwanto Ilyas Hasmi Jeki Saputra ricki2114 Yudhi Darmawan Yuef Okky Pradana