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All Journal Adimas : Jurnal Pengabdian Kepada Masyarakat Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Bayu Prasetiyo Utomo
Politeknik Negeri Madiun
Computer Science & IT Social Sciences

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IMPLEMENTASI CLOSED CIRCUIT TELEVISION UNTUK PENINGKATAN KEAMANAN PERUMAHAN GRIYA SALAK MADIUN Nisaul Hafidhoh; Susilo Veri Yulianto; Muhammad Syaeful Fajar; Gus Nanang Syaifuddiin; Hendrik Kusbandono; Bayu Prasetiyo Utomo; Zidni Zidan Mahestra Setyawan; Nabila Carrissa Dewi
ADIMAS Jurnal Pengabdian Kepada Masyarakat Vol 10 No 1 (2026): Maret 2026
Publisher : Universitas Muhammadiyah Ponorogo

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Abstract

Neighborhood security is a key factor in creating a good quality of life in residential areas. Cases of theft, vandalism, and even inconvenience caused by unknown visitors frequently pose a threat to the community. This situation demands a more effective and responsive surveillance system in residential areas. Traditional surveillance methods, such as patrols or manual security, often experience various limitations, both in terms of human resources, operational time, and coverage area. This activity aims to improve neighborhood security through the implementation of a Closed Circuit Television (CCTV) system in the Griya Salak Housing Complex, Madiun City. The implementation method includes a needs analysis, CCTV network design with a hybrid topology, device installation including IP cameras and Network Video Recorders (NVRs), and system usage training for residents. The results of the activity show an increase in surveillance effectiveness and a sense of security for residents, as well as increased community participation in the management of the technology-based security system. The implementation of this CCTV system is expected to become a model for digital security that can be replicated in other residential areas.
Ekstraksi Blind Data Tersemat LSB dari Citra PNG melalui Force Decode Multi-Arah Ikhwan Baidlowi Sumafta; Ahmad Hamdani; Tri Lestariningsih; Ghali Marzani; Bayu Prasetiyo Utomo; Dionesyus Divo Crista Marvino
SABER : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Vol. 4 No. 4 (2026): Oktober: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/saber.v4i4.3891

Abstract

Digital images are widely utilized as carriers for covert communications through steganography. However, this technique is increasingly exploited to conceal malicious payloads, such as malware, without altering visual appearances. While the Least Significant Bit (LSB) method remains popular due to its high visual imperceptibility, existing steganalysis techniques often fail to recover hidden content when insertion parameters are unknown. This study evaluates the effectiveness of the Force Decode strategy as an exploratory blind steganalysis approach to extract LSB payloads from PNG images without prior knowledge of embedding configurations. Employing a quantitative comparative experimental design, the proposed system was implemented in Python. The method extracts LSBs across the red, green, and blue (RGB) color channels, reconstructs binary sequences through eight pixel-scanning orientations, and converts them into ASCII text. Evaluation was conducted on fifteen stego-image datasets representing five insertion complexity levels, ranging from single-channel alphabetic messages to multi-channel random combinations of letters, numbers, and symbols. The experimental results demonstrate that Force Decode successfully generated textual output across all datasets regardless of insertion complexity. Low-complexity datasets yielded highly legible messages with minimal noise, whereas high-complexity scenarios produced a hybrid of meaningful text fragments and random characters. Despite increased noise in complex configurations, the method consistently revealed latent payload content without prior parameter knowledge. These findings confirm that Force Decode is a viable and effective exploratory steganalysis technique for PNG images, laying a practical foundation for future research on reliable blind LSB extraction and automated interpretation systems.
Co-Authors Ahmad Hamdani Dionesyus Divo Crista Marvino Ghali Marzani Gus Nanang Syaifuddiin Hendrik Kusbandono Ikhwan Baidlowi Sumafta Lestariningsih, Tri Muhammad Syaeful Fajar Nabila Carrissa Dewi Nisaul Hafidhoh Susilo Veri Yulianto Zidni Zidan Mahestra Setyawan