Sistem Pendeteksi Kendaraan Roda Dua Berbasis Internet of Things Menggunakan ESP32-Cam dan YOLOv3
Internet of Things-Based Two-Wheeled Vehicle Detection System Using ESP32-CAM and YOLOV3 for Smart Parking Access Control
DOI:
https://doi.org/10.57152/malcom.v6i3.2826Keywords:
Basis Data MySQL, Deteksi Motor, ESP32-CAM, Internet of Things, Portal Otomatis, YOLOv3Abstract
Pengelolaan parkir secara konvensional masih memiliki keterbatasan dalam pemantauan kendaraan, pengendalian akses, dan pencatatan data secara terstruktur. Sistem dirancang untuk menangkap citra objek melalui ESP32-CAM, memproses deteksi motor menggunakan YOLOv3 pada Python, mengendalikan portal melalui motor servo, menyalakan lampu kilat pada kondisi tertentu, serta menyimpan data hasil deteksi ke basis data MySQL. Pengujian sistem dilakukan pada area parkir Lapangan Borasi, Manokwari, Papua Barat. Kontribusi penelitian ini terletak pada integrasi deteksi kendaraan roda dua berbasis YOLOv3 dengan sistem kontrol portal otomatis, pencahayaan adaptif menggunakan flash ESP32-CAM, serta penyimpanan data deteksi secara real-time ke basis data MySQL dalam satu sistem IoT yang terintegrasi. Pengujian dilakukan menggunakan 19 data uji yang terdiri atas 15 motor dan 4 objek bukan motor. Hasil pengujian menunjukkan bahwa 13 motor berhasil terdeteksi, sedangkan 2 motor tidak terdeteksi pada malam hari akibat rendahnya pencahayaan. Pada objek bukan motor, 2 mobil dan 1 orang berhasil dikenali sebagai bukan motor, sedangkan 1 sepeda salah terdeteksi sebagai motor. Berdasarkan confusion matrix, sistem memperoleh akurasi sebesar 84,21%, presisi motor sebesar 92,86%, dan recall sebesar 86,67%. Hasil ini menunjukkan bahwa sistem mampu melakukan deteksi motor dan pengendalian portal secara otomatis, meskipun masih dipengaruhi oleh kondisi pencahayaan dan kemiripan bentuk objek.
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Copyright (c) 2026 Selvi Leoni Woof, Ir. Abdul Zaid Patiran, Andreas Leonardo Sumendap

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