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) |
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| 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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