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      "abstract": "Kopi merupakan komoditas unggulan Indonesia yang memiliki nilai ekonomi tinggi\r\nsehingga pengendalian kualitasnya sangat penting, terutama pada tahap\r\npascapanen. Proses penyortiran biji kopi masih dilakukan secara manual yang\r\nmenyebabkan kelambatan, ketidakefisienan, dan hasil yang tidak konsisten. Studi\r\nini bertujuan untuk mengembangkan sistem klasifikasi biji kopi secara real-time\r\nmenggunakan pendekatan deep learning berbasis transfer learning melalui CNN\r\nDenseNet201. Dengan memanfaatkan teknologi visi komputer, sistem ini\r\ndiharapkan mampu mengidentifikasi biji kopi berkualitas dan cacat secara otomatis\r\ntanpa perlu perangkat keras khusus atau proses tambahan yang kompleks.\r\nPenelitian ini berkontribusi dalam penyediaan sistem klasifikasi yang cepat, akurat,\r\ndan dapat diinterpretasikan dalam mendukung otomasi industri kopi, khususnya\r\ndalam penilaian kualitas biji kopi. Hasil yang diperoleh diharapkan dapat\r\nmeningkatkan efisiensi serta menstandardisasi proses sortir kopi di Indonesia.",
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      "institution": "Universitas AMIKOM Yogyakarta",
      "subjects": [
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