Perancangan Sistem Deteksi Objek Menggunakan Deep Learning Untuk Mengetahui Ketersediaan Parkir Berbasis Web

Anggun Fergina(1*), S Somantri(2), Radita Ayulianti(3),

(1) Universitas Nusa Putra, Sukabumi, Indonesia
(2) Universitas Nusa Putra, Sukabumi, Indonesia
(3) Universitas Nusa Putra, Sukabumi, Indonesia
(*) Corresponding Author

Abstract


Parking systems often use visual monitoring by parking guards via CCTV, who sometimes experience problems in finding available empty parking spaces. This can cause inaccuracies in directing parking users to available spaces, increasing traffic congestion around the parking area. Therefore, this research aims to design an object detection system using deep learning technology to ensure the availability of parking spaces through a web-based application using the Yolo v8 and prototype methods. Testing the essence of the system shows that object detection is carried out effectively, with box boundaries that correspond to the presence of vehicles in the parking lot. Web test results show consistency between the number of vehicles detected and the numbers displayed on empty and occupied parking slots. Usability testing involving 60 respondents showed a high level of satisfaction, with an average percentage of 91.20%, indicating the level of suitability of the system to user needs.


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DOI: https://doi.org/10.30645/kesatria.v5i3.418

DOI (PDF): https://doi.org/10.30645/kesatria.v5i3.418.g414

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