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            "given": "Zaky Fauzan"
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      "date": "2026-02-24",
      "keywords": "Deteksi penyakit, Daun pisang, YOLOv11n, Augmentasi Data,\r\nmAP, F1-Confidence, Disease detection, Banana Leaf, Data Augmentation.",
      "department": "Fakultas Ilmu Komputer",
      "metadata_visibility": "show",
      "thesis_type": "bachelor",
      "title": "ANALISIS YOLOv11n UNTUK DETEKSI PENYAKIT DAUN\r\nPISANG DENGAN KETIDAKSEIMBANGAN KELAS",
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      "abstract": "Penyakit daun pisang merupakan salah satu ancaman utama bagi produksi\r\npisang di Indonesia, yang dapat menurunkan kualitas dan kuantitas hasil pertanian.\r\nOleh karena itu, deteksi dini terhadap penyakit daun pisang sangat penting untuk\r\nmeminimalkan kerugian ekonomi yang ditimbulkan. Penelitian ini bertujuan untuk\r\nmengembangkan sistem deteksi penyakit daun pisang secara otomatis\r\nmenggunakan model deteksi objek YOLOv11n. Metode yang digunakan mencakup\r\npengumpulan dataset daun pisang yang terinfeksi berbagai jenis penyakit dari\r\nplatform Roboflow, yang kemudian dilakukan proses pra-pemrosesan dan\r\naugmentasi data untuk mengatasi ketidakseimbangan kelas dalam dataset. Model\r\nYOLOv11n dilatih dengan menggunakan teknik augmentasi data seperti flip\r\nhorizontal, flip vertikal, grayscale, Gaussian blur, dan Gaussian noise untuk\r\nmeningkatkan keberagaman data pelatihan. Hasil penelitian menunjukkan bahwa\r\nmodel YOLOv1n berhasil mencapai kinerja yang baik dalam mendeteksi penyakit\r\ndaun pisang dengan skor mAP@50 sebesar 87.8% pada epoch ke 10, yang\r\nkemudian stabil pada 87.1% setelah 40 epoch. Evaluasi menggunakan metrik F1Confidence\r\n\r\ndan Recall-Confidence menunjukkan bahwa model ini memiliki\r\nkeseimbangan yang baik antara presisi dan recall, dengan nilai F1-Confidence ratarata\r\n0.82\r\ndan\r\nRecall-Confidence\r\n0.96\r\npada\r\nepoch\r\nke-10.\r\nDengan\r\ndemikian,\r\nmodel\r\n\r\nYOLOv11n\r\nini\r\ndapat\r\ndiandalkan\r\nuntuk\r\ndeteksi\r\npenyakit\r\ndaun\r\npisang\r\nsecara\r\nrealtime\r\ndan\r\nmemberikan\r\nkontribusi\r\nsignifikan\r\nterhadap\r\npengelolaan\r\ntanaman\r\npisang\r\n\r\nyang\r\nlebih\r\nefisien.\r\nPenelitian\r\nini\r\njuga\r\nmemberikan\r\nsolusi\r\npraktis\r\nbagi\r\npetani\r\nuntuk\r\n\r\nmemantau\r\nkesehatan\r\ntanaman\r\ndengan\r\nteknologi\r\nyang\r\nmudah diakses.",
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            "given": "Rina",
            "lineage": null,
            "honourific": null,
            "family": "Pramitasari"
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