Kombinasi Metode Fitur Ekstraksi untuk Indentifikasi Penyakit pada Daun Teh
DOI:
https://doi.org/10.26418/justin.v11i3.65172Keywords:
Penyakit Daun Teh, Haralick, Color Histogram, Hu Moment, Augmentasi DataAbstract
Teh merupakan salah satu minuman yang paling banyak dikonsumsi di dunia, namun produksi teh seringkali terhambat dan mengalami penurunan oleh berbagai penyakit yang mempengaruhi pertumbuhan dan kualitas daun teh. Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi penyakit daun teh dengan memanfaatkan teknologi Image Classification dan menerapkan metode kombinasi analisis tekstur Haralick, Color Histogram, Hu Moment dan pengklasifikasian objek menggunakan Random Forest classifier. Dataset yang digunakan dalam penelitian ini dikumpulkan dari perkebunan teh Johnstone Boiyon di Koiwa, Kabupaten Bomet, Kenya dengan jumlah 1510 citra yang terbagi menjadi 8 kelas. Pra pemrosesan pada penelitian ini dilakukan dengan menambahkan tahapan augmentasi data untuk memperoleh jumlah citra yang lebih besar sehingga algoritma dapat mempejalari pola lebih banyak. Hasil penelitian menunjukkan bahwa kombinasi dari metode yang diusulkan mencapai akurasi 99% dengan nilai standard deviasi yang rendah sebesar 0.001055% yang menunjukkan keefektifan kombinasi analisis tekstur Haralick, Color Histogram, dan Hu Moment serta Random Forest Classifier dalam mengklasifikasikan penyakit daun teh.
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