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All Journal Dedikasi: Jurnal Pengabdian Kepada Masyarakat Journal of Informatics and Vocational Education
Syandhu Dea Fermanda
Universitas Muhammadiyah Bangka Belitung
Religion Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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PENGEMBANGAN SPOT FOTO KREATIF MELALUI PEMBUATAN FRAME FOTO DI WISATA LPHD BATU MENTAS Eko Pratama; Astrid Juliyanti; Dwi Fajaria; Putrianti; Ratri Kusumadita; Gea Cantika; Syandhu Dea Fermanda; Ayu Nuratika; Febrianus Jerabun; Rakha Piadika
Bestari: Jurnal Pengabdian Kepada Masyarakat Vol 5 No 3 (2025)
Publisher : Sekolah Tinggi Keguruan dan Ilmu Pendidikan (STKIP) Melawi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46368/dpkm.v5i3.4465

Abstract

The UNMUH BABEL Community Service Program (KKN) at the Batu Mentas Village Community Service Center (LPHD) is located in Badau Village, Belitung Regency, which boasts beautiful tropical forests, clear streams, large rock formations, and a camping area. However, visual facilities, such as photo spots, are still limited. This community service activity aimed to create a creative, triangular photo spot made from bamboo and wood that blends seamlessly with the surrounding environment. The method used was a participatory approach, involving tourism managers in every stage, from site identification and design planning to material processing, to installation and evaluation. The results of the activity showed that the photo spot received a positive response from tourism managers and has the potential to become an effective promotional tool through social media posts. This innovation is expected to increase tourist visits, strengthen the destination's image as a sustainable ecotourism destination, and provide economic benefits to the local community.
Early Fire Detection Using IoT and Deep Learning Syandhu Dea Fermanda; Zikri Wahyuzi; Arvi Pramudyantoro
Journal of Informatics and Vocational Education Vol. 9 No. 3 (2026): November 2026
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i3.3515

Abstract

Fire incidents in strategic facilities such as weapon storage rooms can cause severe damage, threaten personnel safety, and disrupt operational readiness. Conventional fire detection systems generally rely on smoke or temperature sensors, which often respond only after hazardous conditions reach a certain threshold. Therefore, this study proposes an early fire prevention system based on Internet of Things (IoT) and deep learning using CCTV cameras. The system was developed using the System Development Life Cycle (SDLC) with the Waterfall model. The object detection model employed YOLOv8 and was trained on a laptop before being deployed to a Raspberry Pi 5 as the real-time processing unit. The implemented hardware consisted of a Raspberry Pi 5, a Logitech webcam, monitor, keyboard, and mouse. Testing was conducted in a room measuring 6 m × 4 m × 3.5 m. The developed system successfully detected four object classes, namely fire, smoke, cigarette, and person. The implemented logic mechanism classified fire detection as a fire incident, while simultaneous cigarette and smoke detection was categorised as smoking activity with potential fire risk. In addition, the system successfully sent automatic warning notifications through Telegram, enabling faster response without continuous manual monitoring. The results indicate that combining YOLOv8, Raspberry Pi 5, and IoT communication can provide an effective, practical, and low-cost intelligent fire prevention solution for indoor strategic facilities.
Co-Authors Arvi Pramudyantoro Astrid Juliyanti Ayu Nuratika Dwi Fajaria Eko Pratama Febrianus Jerabun Gea Cantika Putrianti Rakha Piadika Ratri Kusumadita Zikri Wahyuzi