Peningkatan Keselamatan Berkendara dengan Fitur Deteksi Helm pada Sistem Transportasi Cerdas

Authors

  • Rizki Elisa Nalawati Politeknik Negeri Jakarta
  • Dewi Yanti Liliana Politeknik Negeri Jakarta
  • Bambang Warsuta Politeknik Negeri Jakarta

Keywords:

CNN, Deteksi, Help, Sepeda Motor, YOLO (You Only Look Once)

Abstract

Peningkatan jumlah pengendara sepeda motor setiap tahun kian bertambah. Sehingga memunculkan masalah baru berupa kepatuhan masyarakat terkait keselamatan berkendara. Salah satu upaya keselamatan berkendara adalah menggunakan helm saat berkendara. Namun tidak semua masyarakat patuh terhadap aturan yang telah ditetapkan oleh pemerintah. Untuk mendukung upaya peningkatan keselamatan berkendara khususnya roda dua atau motor, Sistem transportasi cerdas dapat diimplementasikan guna mensolusikan masalah ini. Manfaat dari sistem transportasi cerdas ini adalah kemampuan dalam melakukan deteksi pengguna sepeda motor yang tidak menggunakan helm. Menggunakan helm sepeda motor dapat menurunkan kemungkinan cedera fatal pengendara sepeda motor dalam kecelakaan lalu lintas jalan sebesar 42%. Sehingga peranan sistem transportasi cerdas ini memanfaatkan teknik image recognition dalam mendeteksi pemakaian helm. Teknik deteksi pemakaian helm ini mampu diimplementasikan dengan keberadaan algoritma YOLO yang mampu merekognisi sebuah obyek. Sistem ini akan mengadopsi kemampuan algoritma You Only Look Once (YOLO) dalam mengenali objek. Selain itu, sistem ini akan mengadopsi jaringan Convolutional Neural Network (CNN) tunggal dalam klasifikasi serta lokalisasi objek dengan kotak pembatas. Identifikasi citra dilakukan dengan pemanfataan CNN. Sehingga didapatkan skurasi pendeteksian helm adalah 94%, yang cocok untuk ditempatkan di lokasi jalan raya.

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Published

2023-08-05

How to Cite

Nalawati, R. E., Dewi Yanti Liliana, & Bambang Warsuta. (2023). Peningkatan Keselamatan Berkendara dengan Fitur Deteksi Helm pada Sistem Transportasi Cerdas. Seminar Nasional Inovasi Vokasi, 2, 136–146. Retrieved from https://prosiding.pnj.ac.id/sniv/article/view/402