SEGMENTASI SAMPAH ORGANIK, NON-ORGANIK, DAN B3 MENGGUNAKAN YOLOV11 DENGAN PEMBANDING CNN

Putra, R. Much Ardiansyah (2026) SEGMENTASI SAMPAH ORGANIK, NON-ORGANIK, DAN B3 MENGGUNAKAN YOLOV11 DENGAN PEMBANDING CNN. Undergraduate thesis, Universitas Nusantara PGRI Kediri.

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Abstract

Penelitian ini bertujuan merancang sistem segmentasi sampah menggunakan YOLOv11n-Seg serta membandingkan hasil klasifikasinya dengan CNN EfficientNetB0. Dataset yang digunakan berformat YOLO segmentation dengan 5.489 citra dan 6.542 objek anotasi pada kelas organik, non-organik, dan B3. Tahapan penelitian meliputi analisis dataset, anotasi instance segmentation, pelatihan model, evaluasi, dan implementasi prototipe Streamlit. Hasil pengukuran evaluasi metrik YOLO dirancang menggunakan Precision sebesar 90,43%, Recall sebesar 79,36%, F1-score sebesar 84,54%, mAP-50 sebesar 84,96%, dan mAP 50-95 sebesar 76,68%. Sedangkan untuk pengukuran hasil metrik CNN menggunakan nilai akurasi sebesar 98,95%, Precision sebesar 99,2%, Recall sebesar 99,3%, F1-score sebesar 99,2%. Hasil analisis dataset menunjukkan kelas non-organik dominan dengan 3.805 objek, diikuti organik 2.093 objek dan B3 635 objek. Sistem ini diharapkan membantu identifikasi sampah rumah tangga secara cepat dan interaktif.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Segmentasi, Sampah, Machine Learning, YOLO, CNN
Subjects: 410 Engineering science > 457 Computer engineering
410 Engineering science > 459 Computer science
410 Engineering science > 461 Information systems
Divisions: Fakultas Teknik dan Ilmu Komputer > S1-Teknik Informatika
Depositing User: R. Much Ardiansyah Putra
Last Modified: 04 Aug 2026 15:59
URI: http://repository.unpkediri.ac.id/id/eprint/26304

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