DOI: https://doi.org/10.14710/transmisi.27.4.240-248

SISTEM DETEKSI KEBAKARAN BERBASIS VISI KOMPUTER DENGAN YOLOv11 TERINTEGRASI DENGAN TELEGRAM

*Nico Demeus Hasoloan Manurung orcid publons  -  Fakultas Teknik dan Informatika, Universitas 17 Agustus 1945 Jakarta, Indonesia
Rajes Khana  -  Program Studi Informatika, Universitas 17 Agustus 1945, Indonesia
Jemie Muliadi  -  Program Studi Teknik Elektro, Universitas 17 Agustus 1945, Indonesia
Muhammad Sobirin  -  Program Studi Teknik Elektro, Universitas 17 Agustus 1945, Indonesia
Dikirim: 31 Mei 2025; Diterbitkan: 6 Okt 2025.
Akses Terbuka Copyright (c) 2025 Transmisi: Jurnal Ilmiah Teknik Elektro under http://creativecommons.org/licenses/by-sa/4.0.

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Deteksi dini api menjadi penting dalam upaya mitigasi risiko kebakaran. Sistem deteksi tersebut dikembangkan dalam penelitian ini dengan menggunakan kamera dan algoritma YOLOv11, serta notifikasi real-time terintegrasi dengan Telegram. Pelatihan model melibatkan dataset citra nyata dan hasil augmentasi, serta dievaluasi menggunakan metrik precision, recall, dan mAP. Hasil pelatihan menunjukkan bahwa model mencapai precision, recall, dan mAP@0.5 serta mAP@0.5:0.95 lebih tinggi dari YOLO versi lainnya dengan peningkatan precision sebesar 7,06%, recall 4,02%, mAP@0.5 sebesar 1,42%, dan mAP@0.5:0.95 mencapai peningkatan tertinggi sebesar 25,77%. Tingkat confidence rata-rata dari sistem adalah 0,63 pada indoor dan 0,576 pada outdoor yang menunjukkan kehandalannya. Sistem juga mengirimkan notifikasi otomatis ke Telegram saat deteksi api terjadi, sehingga mempercepat respons user terhadap insiden kebakaran. Dapat disimpulkan bahwa sistem yang dirancang cocok untuk diterapkan sebagai sistem peringatan dini kebakaran berbasis visi komputer yang dapat diterapkan pada PC dan mudah diintegrasikan ke smartphone.

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