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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Techno.Com: Jurnal Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Seminar Nasional Teknologi Informasi Komunikasi dan Industri INOVTEK Polbeng - Seri Informatika Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Infotekmesin Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Industri Terintegrasi (JUTIN) Jurnal Sistem Informasi dan Sains Teknologi Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Journal of Accounting Law Communication and Technology Repeater: Publikasi Teknik Informatika dan Jaringan INOVTEK Polbeng - Seri Informatika
Agus Tedyyana, Agus
Politeknik Negeri Bengkalis
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering

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Journal : INOVTEK Polbeng - Seri Informatika

 1 
Implementation of AES-128 Encryption for Fingerprint Template Protection in ESP32-Based Biometric Ticketing System Subandri, Muhammad Asep; Tedyyana, Agus; Putu Mahendra, I Gusti Agung
INOVTEK Polbeng - Seri Informatika Vol. 11 No. 1 (2026): February
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/mkks1830

Abstract

Biometric ticketing systems utilizing fingerprint recognition provide enhanced security and convenience for passenger identification in public transportation. However, the transmission of fingerprint templates over wireless networks without adequate cryptographic protection exposes the system to interception attacks and privacy breaches. This research implements AES-128 encryption in Cipher Block Chaining (CBC) mode to protect fingerprint templates transmitted within an ESP32-based biometric ticketing system. The implementation leverages the ESP32’s integrated mbedTLS library with hardware acceleration to achieve efficient cryptographic operations. Experimental evaluation using 10 fingerprint template samples demonstrates a 100% success rate for encryption-decryption operations. Performance measurements indicate an average encryption latency of 2.30 ms and decryption latency of 2.10 ms, with a data size overhead of 32 bytes (6.25%) due to Initialization Vector (IV) and PKCS7 padding. The results confirm that the proposed encryption scheme effectively secures biometric data transmission while maintaining system responsiveness suitable for real-time applications.
Design of an Intelligent Vehicle Manifest Recording System at the Bengkalis-Sungai Pakning Ro-Ro Ferry Crossing Based on Deep Learning and Optical Character Recognition Jaroji; Danuri; Tedyyana, Agus
INOVTEK Polbeng - Seri Informatika Vol. 11 No. 1 (2026): February
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/894v9b70

Abstract

Vehicle manifest recording in Ro-Ro ferry services is still predominantly conducted manually, which may lead to operational inefficiencies and data inconsistencies. This study presents an automated vehicle manifest recording system for the Bengkalis–Sungai Pakning Ro-Ro ferry crossing by leveraging deep learning and Optical Character Recognition (OCR) technologies. The proposed system utilizes CCTV or IP cameras to capture vehicle images, performs frame extraction from video streams, and applies YOLOv11 for real-time vehicle and license plate detection. The detected license plate regions are subsequently processed using an OCR module to extract textual vehicle identification information. The detection model was trained using a publicly available vehicle and license plate dataset. Experimental evaluation on the vehicle and license plate dataset shows that the YOLOv11 model achieves a precision of 85.9%, recall of 84.0%, and mAP@0.5 of 87.8% for vehicle and plate detection. OCR evaluation conducted on real operational test images indicates a recognition success rate of 57.5%, with an average confidence score of 0.63 for successfully recognized plates. Further analysis reveals that illumination level and plate scale (distance proxy) are the dominant factors affecting OCR performance, while tilt angle exhibits moderate influence. These results indicate that the proposed framework provides reliable visual detection performance and identifies critical environmental constraints that must be addressed for robust automated manifest deployment in Ro-Ro ferry environments.
Co-Authors Abda Abda Afis Julianto Apri Siswanto Danuri Danuri Danuri Danuri Danuri Danuri Danuri, Danuri Depandi Enda Deski Ari Sandi Effendy, Akmar Elgamar Syam Fajar Ratnawati Fajar Ratnawati Fajri Profesio Putra Febriansyah, Muhammad Zuhri Ghazali, Osman Jaroji Jaroji, - Kasmawi Lidya Wati Lumban, Andre Pardamean Muhamad Azren Muhammad Asep Subandri Muhammad Luthfi Nur Ilham. A Nurmi Hidayasari Onno W. Purbo Osman Ghazali Pretti Ristra Putu Mahendra, I Gusti Agung Ratnawati, Fajar Rezki Kurniati, Rezki Rima Anggraini Rima Anggraini, Rima Rosyidah Rosyidah, Rosyidah Sobirin, M Suci Sekar Sari Suharyadi, Thoriq Nadaghoist Sunaryo Sunaryo Supria Supria W. Purbo, Onno Yudi Yudi