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Digital Transformation and Strengthening of Mosque Security Systems at Al-Quddus G-Land Arcadia Bojongsoang Towards a Smart Worship Environment (Smart Mosque) Reza Rendian Septiawan; Ardiansyah Ramadhan; Iga Narendra Pramawijaya; Ridho Ramadani Saputra; Kirei Kirani Jayusman; Deo Prima Listiono
JARDIRA – Jurnal Pengabdian Digital dan Rekayasa Informatika Vol. 2 No. 2 (2026): Vol. 2, No. 2, July 2026
Publisher : CogniSpectra Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65917/jardira.v2i2.73

Abstract

Background: Al-Quddus Mosque in the G-Land Arcadia residential complex, Bojongsoang, functions as an important religious and social center for the local community. However, increasing activity levels and conventional security practices have exposed the mosque to risks such as theft, vandalism, and limited monitoring capabilities. Contribution: This community service program aimed to support the digital transformation of the mosque through the deployment of a smart security system as an initial step toward developing a Smart Mosque environment. Method: The program was implemented through four stages: situational analysis, system design, deployment of a high-definition CCTV surveillance network integrated with a Network Video Recorder (NVR), and operational training for mosque administrators. The surveillance system utilized Ezviz H3C Color 2MP cameras strategically installed in indoor and outdoor areas. A post-installation survey was conducted to evaluate community responses. Results: The digital security system was successfully installed and formally handed over to mosque administrators for future operation and maintenance. Training activities improved administrators’ readiness to operate the system independently. Survey results showed a highly positive response, with 99.35% of respondents agreeing or strongly agreeing that the project met community needs and should be continued in the future. Conclusion: The implementation transformed mosque security management from a conventional approach toward a proactive digital system. The initiative strengthened security infrastructure, enhanced community preparedness in managing digital assets, and provided a replicable model for technology-based religious facility management in the Society 5.0 era.
An HHO-Optimized LSTM Framework for Predicting Adverse Effects Associated with Reproductive and Breast Disorders ANGEL METANOSA AFINDA; IGA NARENDRA PRAMAWIJAYA; FAUZAN FIRDAUS
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 14, No 3: Published July 2026
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v14i3.358

Abstract

Reproductive toxicity prediction is a major challenge in drug development as side effects are often difficult to detect early. SMILES representations provide a compact sequential format suitable for deep learning. This study proposes an HHO-optimized LSTM model to predict reproductive and breast-related side effects. Four architectural schemes were evaluated including L (LSTM only), CL (Convolution + LSTM), LD (LSTM + Dense), and CLD (Convolution + LSTM + Dense). Results show that the tuned L scheme achieved the best performance with accuracy increasing from 0.6304 to 0.6739 and F1-score from 0.6792 to 0.7097. These findings highlight the effectiveness of metaheuristic optimization in computational toxicology modeling.