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      "title": "KLASIFIKASI PENYAKIT DAUN TERONG MENGGUNAKAN\r\nDATASET TERAUGMENTASI DENGAN OPTIMASI FINETUNING\r\nDENGAN\r\nALGORITMA\r\nMOBILENETV2",
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          "nim": "22.11.4945",
          "name": {
            "given": "Muhammad",
            "lineage": null,
            "honourific": null,
            "family": "Ramadianto"
          }
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      "contributors": [
        {
          "name": {
            "given": "Afrig",
            "family": "Aminuddin",
            "honourific": null,
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      "corp_creators": [
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      "keywords": "MobileNetV2, Fine-Tuning, Transfer Learning, Penyakit Daun\r\nTerong, Klasifikasi Citra, Eggplant Leaf Disease,\r\nImage Classification.",
      "date": "2026-02-27",
      "abstract": "Terong (Solanum melongena L.) merupakan salah satu komoditas\r\nhortikultura yang banyak dibudidayakan di Indonesia, namun produktivitasnya\r\nsering menurun akibat serangan penyakit daun. Identifikasi penyakit daun secara\r\nkonvensional masih dilakukan melalui pengamatan visual sehingga rentan terhadap\r\nkesalahan diagnosis, membutuhkan waktu, dan tidak efisien pada lahan berskala\r\nbesar. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan sistem\r\nklasifikasi penyakit daun terong berbasis citra digital menggunakan metode Deep\r\nLearning dengan arsitektur MobileNetV2. Dataset yang digunakan berasal dari\r\nMendeley Data dan telah melalui proses augmentasi, sehingga penelitian ini\r\nberfokus pada optimalisasi pelatihan model menggunakan transfer learning dan\r\nfine-tuning. Tahapan penelitian meliputi preprocessing citra, pembagian data\r\nmenjadi data training, validation, dan testing, pelatihan model MobileNetV2\r\npretrained ImageNet, serta evaluasi performa menggunakan confusion matrix dan\r\nmetrik akurasi. Hasil eksperimen menunjukkan bahwa model mencapai validation\r\naccuracy terbaik sebesar 95.52% pada epoch ke-34. Selain itu, evaluasi pada data\r\ntesting menghasilkan akurasi sebesar 93.92%. Hasil tersebut membuktikan bahwa\r\nMobileNetV2 dengan strategi fine-tuning mampu memberikan performa klasifikasi\r\nyang baik dengan efisiensi komputasi yang tinggi. Sistem ini diharapkan dapat\r\nmembantu petani dalam mendeteksi penyakit daun terong secara cepat dan akurat\r\nsebagai bagian dari penerapan smart agriculture.",
      "dir": "disk0\/00\/03\/31\/12",
      "date_type": "published"
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