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Inggris Sayyidah Jasinda Amalia; Sandhy Fernandez
Governance IT Adoption and Technology Advance Vol. 1 No. 1 (2026)
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/govita.v1i1.10603

Abstract

PT XYZ focuses on supplying, distributing and managing clean water sources for the people. The problem faced is that PT XYZ does not yet have a security management system to carry out mitigation actions other than the data backup process which is carried out every day. Having data backup alone is not enough to protect the security of a company's information system. The research method used in this research is a qualitative method where the data obtained comes from observations and interviews. This research was carried out with the results recommended at identifying improvements to significantly increase security for the Company. The choice of ISO 27001:2013 as the framework for carrying out this research evaluation is because ISO itself is a good standard for solving problems that occur at PT XYZ, this standard is very flexible to develop and really depends on the needs of the organization.
Hybrid Model of Isolation Forest and Long Short-Term Memory Autoencoder for Digital Forensic Anomaly Detection in Manufacturing IoT Networks Muammar; Sandhy Fernandez; Arif Riyandi; Sena Wijayanto
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5732

Abstract

The development of Internet of Things (IoT) technology in the manufacturing sector creates opportunities for efficiency while also increasing vulnerability to sabotage threats that are difficult to detect manually. This study aims to design and evaluate an artificial intelligence-based hybrid model that combines Isolation Forest and Long Short-Term Memory Autoencoder to detect anomalies in the context of digital forensics in manufacturing industrial IoT networks. The research design uses an experimental approach with a simulated dataset representing 35 working days of smart factory operations, covering 127 sabotage scenarios distributed across six types of logs. The methodology applied is a two-layer cascade architecture, where Isolation Forest serves as a statistical anomaly detector in the first layer, followed by Long Short-Term Memory Autoencoder as a time-series pattern validator in the second layer. The evaluation results show that Isolation Forest independently achieved an F1-score of 0.84, Long Short-Term Memory Autoencoder achieved 0.87, while the hybrid model produced an F1-score of 0.93 with a precision of 0.91 and a recall of 0.95. These findings confirm that the hybrid cascade approach significantly outperforms each individual method. This study concludes that the integration of both methods provides a more accurate and efficient digital forensic solution for detecting sabotage incidents in industrial IoT environments.
Digitalisasi Pengelolaan Lahan dan Pemasaran Hasil Pertanian Melalui Penguatan Kapasitas Kelompok Tani Sandhy Fernandez; Muammar Muammar; Arif Riyandi; Sisilia Thya Safitri; Muhamad Awiet Wiedanto Prasetyo
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 1 (2026): Februari
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/6mp47h76

Abstract

Kegiatan pengabdian kepada masyarakat ini dilaksanakan untuk menjawab permasalahan pengelolaan lahan dan pemasaran hasil pertanian yang masih dilakukan secara konvensional oleh kelompok tani di Desa Cingebul, Kabupaten Banyumas. Pencatatan data lahan yang belum terstruktur serta keterbatasan pemanfaatan media digital menyebabkan kesulitan dalam perencanaan, evaluasi, dan pengambilan keputusan, serta membatasi jangkauan pemasaran hasil pertanian. Program ini bertujuan untuk mendukung transformasi digital pertanian melalui penguatan kapasitas kelompok tani dalam pengelolaan data lahan dan pemasaran hasil pertanian berbasis teknologi digital. Metode pelaksanaan meliputi analisis kebutuhan melalui observasi dan wawancara, pelatihan pengelolaan data lahan digital, pelatihan pemasaran digital, serta pendampingan implementasi secara langsung di lapangan. Hasil kegiatan menunjukkan peningkatan pemahaman peserta yang ditunjukkan oleh kenaikan skor evaluasi kuantitatif dari rentang 52–60 pada pre-test menjadi 80–86 pada post-test, dengan peningkatan tertinggi pada kemampuan input data lahan. Evaluasi kepuasan peserta juga menunjukkan nilai rata-rata tinggi pada kategori baik hingga sangat baik dengan skor antara 4,55–4,81. Secara keseluruhan, kegiatan ini meningkatkan efisiensi pengelolaan lahan, transparansi data pertanian, dan kesiapan kelompok tani dalam memanfaatkan teknologi digital secara berkelanjutan.
Biometric Authentication Improving Robustness Attendance System with MobileNet Muhammad Imanullah; Sandhy Fernandez; Ardi Wijaya; M. Yoka Fathoni
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 4 (2026): JUTIF Volume 7, Number 4, August 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.4.5381

Abstract

Our research is focused on developing an effective attendance system that matches the conditions of pandemic or other specific pandemic situations. We have built a legacy system using Randomized QR-Code and MAC-Address as the authentication method. Based on the analysis, it is known that users need around 25.8877 seconds to authenticate their presence in the system. Therefore, we are trying to improve the authentication time and robustness of the system by using user facial biometrics. Facial biometrics was chosen because it is the most appropriate way to authenticate one's identity during pandemic, where physical contact is unnecessary or even expected to be avoided. According to several test scenarios, it is known that our new system takes time simultaneously to recognize the user and record their presence data once they show their face to the recognition camera. This new system can also run more powerfully with a percentage of 1.26% processor time, 16.9059% faster than the previous system, because it is deployed in a web browser using the latest web app framework technology, which can run on various devices. Based on these findings, our new approach successfully improves its predecessor systems. To produce a robust attendance system, we must implement a Biometric Authentication method, which is enhanced with other secure authentication methods such as Random QR-Code scanning. With a combination of these methods, an attendance system will run safely and efficiently.