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<http://digilib.unila.ac.id/id/eprint/56218> <http://purl.org/dc/terms/title> "STUDI PENGGUNAAN METODE JARINGAN SYARAF TIRUANBACKPROPAGATION UNTUK MENENTUKAN KEMATANGAN BUAH KOPI"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://digilib.unila.ac.id/id/eprint/56218> <http://purl.org/ontology/bibo/abstract> "Identifikasi kopi merupakan proses dalam menentukan kematangan kopi. Saat\r\nmengolahan kopi, pemilihan kopi dilakukan secara manual oleh petani dalam\r\npenentuannya. Hal itu membuat proses menjadi lebih lambat dan tidak membuat\r\nkepastian untuk kualitas kopi yang bermutu baik, untuk itu perlu mengembangkan\r\nsistem untuk mengidentifikasi kualitas kopi yang baik. Dalam penelitian ini,\r\ndilakukan studi awal untuk mengembangkan sistem untuk mengidentifikasi\r\nkematangan kopi menggunakan metode JST backpropagation. Tahapan awal\r\nmerancang sistem yaitu preprocessing dalam pemprosesan gambar sebelum\r\nmemasuki langkah JST backpropagation. Proses preprocessing berguna untuk\r\nmeningkatkan kontras, menghapus background dalam gambar dan membaca nilai\r\nRGB untuk input pada tahap berikutnya. Pada tahap selanjutnya adalah sistem\r\nJST backpropagation, melakukan training setelah sistem membaca polanya\r\ndengan benar, selanjutnya sistem melakukan testing menggunakan data yang\r\nberbeda dengan pelatihan. Hasil akhir dalam penelitian ini adalah sistem dapat\r\nmenentukan target yang diharapkan dan dapat membaca pola pelatihan dengan\r\nbenar pada saat melakukan testing. Tingkat akurasi sistem yang di informasikan\r\nketika sistem pada proses testing, sistem memiliki 4 kondisi output yaitu (matang,\r\ntidak matang, terlalu matang dan tidak diketahui) menampilkan hasil presentase\r\nberhasil 96,66% dari 60 sample gambar testing. Penelitian ini diharapkan dapat\r\nmembantu dalam mengembangkan sistem identifikasi kematanng kopi dengan\r\nmenggunakan JST backpropagation.\r\nKata kunci : kopi, JST, backpropagation.\r\n\r\n\r\nIdentification of coffee is a process in determining for maturity of coffee. When\r\nprocessing coffee, selection of coffee were done in manually by farmer on its\r\ndetermination. This makes the process slower and it makes no certain results for\r\nbetter quality of coffee, that’s why need to develop a system to identify better\r\nquality of coffee. In this research, doing first study to develop system to identify\r\nmaturity of coffee using Artificial Neural Network backpropagation method. The\r\nfirst step of designing system is preprocessing in picture processing before\r\nentering Artificial Neural Network backpropagation step. Preprocessing process is\r\nuseful to increase contrast, to remove background in picture and read RGB’s score\r\nfor input in the next step. The next step is Artificial Neural Network\r\nbackpropagation system, it doing the training after the system read the pattern\r\ncorrectly, after that, the system doing test using different data with training. The\r\nfinal result in this research is the system could determine the expected target and\r\ncould read the training pattern correctly when doing testing. The level of system\r\naccuracy informed when the system succeeded testing the process, The 4th output\r\nconditions system are (mature, immature, over mature, and unknown) display the\r\npercentage results of succeed 96,66% from 60 samples of testing pictures. This\r\nresearch is expected to help in developing identification system of maturity coffee\r\nby using Artificial Neural Network backpropagation.\r\nKeywords: coffee, Artificial Neural Network, backpropagation\r\n"^^<http://www.w3.org/2001/XMLSchema#string> .
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