Klasifikasi Kualitas Fisik Kopi Beras Arabika menggunakan Pengolahan citra dengan Metode K-Nearest Neighbor (K-NN)
نویسندگان
چکیده
Abstrak. Proses sortasi pada biji kopi beras arabika umumnya masih dilakukan secara manual sehingga peran teknologi sangat dibutuhkan proses otomatis dengan menggunakan pengolahan citra digital metode K-Nearest Neighbor (KNN). Penelitian ini bertujuan untuk mengetahui tingkat akurasi klasifikasi kualitas fisik berdasarkan normal, pecah, coklat, dan hitam sebagian K- Nearest (K-NN). Perlakuan pengambilan penelitian ada dua yaitu telungkup (Down) terbalik (Up). Rancangan (KNN) Linear Discriminant Analysis (LDA) parameter yang memengaruhi arabika. Hasil menunjukkan bahwa nilai K=5 rata-rata 78,625% sedangkan K=3 58,000%. terbaik posisi 80,25%. Berdasarkan hasil paling berpengaruh dalam adalah area, perimeter, b, kontras, B, R, L, a, energi, korelasi, G.The Classification Of The Physical Quality Arabica Coffee Bean Uses Image Processing Using (K-NN) MethodAbstract. sorting process for coffee beans is generally still done manually so the role of technology needed in automatic using image processing with method. This study aims to determine level accuracy physical quality classification based on images normal beans, broken cocoa and partially black There are two treatments taking this study, namely face down (down) upside (up). research design uses method parameters that affect beans. results showed by value K = 5 average was 78.625%, while 3 best treatment position an 80.25%. Based (LDA), most influential contrast, energy, correlation, G parameters.
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ژورنال
عنوان ژورنال: Jurnal Ilmiah Mahasiswa Pertanian
سال: 2022
ISSN: ['2614-6053', '2615-2878']
DOI: https://doi.org/10.17969/jimfp.v7i2.19896