Klasifikasi Sampah Otomatis Berbasis Yolov8 dan Raspberry Pi 5 pada Smartbin
DOI:
https://doi.org/10.59395/53bb4f09Keywords:
klasifikasi sampah, YOLOv8, Raspberry Pi 5, computer vision, smartbin, deep learningAbstract
Penelitian ini bertujuan merancang dan menguji prototipe tempat sampah cerdas untuk mengklasifikasikan limbah secara otomatis ke dalam empat kategori, yaitu mudah terurai, residu, bahan berbahaya dan beracun (B3), serta daur ulang. Metode yang digunakan adalah penerapan algoritma pembelajaran mendalam You Only Look Once versi delapan varian nano (YOLOv8n) yang diimplementasikan pada komputer papan tunggal Raspberry Pi 5, modul kamera penangkap citra, serta motor servo ganda sebagai penggerak mekanik pemilah. Data penelitian menggunakan 300 citra limbah primer dengan pembagian data latih dan data uji sebesar 80:20 serta pemanfaatan teknik transfer learning. Teknik analisis data dilakukan melalui pengujian konvergensi iterasi pelatihan, evaluasi akurasi deteksi visual langsung, uji keandalan integrasi mekanik aktuator, serta pengukuran latensi waktu komputasi. Hasil penelitian menunjukkan pelatihan model mencapai performa optimal pada putaran ke-300 dengan capaian mean Average Precision (mAP@0.5) sebesar 84,22%. Pengujian prototipe secara langsung menghasilkan rata-rata akurasi deteksi sebesar 80,75%, keberhasilan integrasi mekanik sebesar 92,0%, dan waktu komputasi rata-rata sebesar 0,1126 detik per objek. Sistem terbukti mampu memilah sampah secara cepat dan andal pada komputasi tepi (edge computing).
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