Studi Metode Klasifikasi Machine Learning dengan Gray Level Co-occurrence Matrix Pada Sistem Pengenalan Bunga
DOI:
https://doi.org/10.22441/incomtech.v15i2.16007Kata Kunci:
GLCM, klasifikasi, machine learning, pengenalan bungaAbstrak
Bunga adalah produsen terpenting di bumi yang dapat tumbuh di berbagai iklim dan habitat. Tidak seperti klasifikasi objek sederhana pengenalan bunga dan klasifikasi bunga adalah tugas yang menantang karena beberapa kelas bunga dapat memiliki fitur yang serupa: beberapa bunga dari jenis yang berbeda memiliki warna, bentuk dan penampilan yang serupa. Studi penelitian ini membandingkan dan melakukan optimasi parameter pada beberapa metode klasifikasi pada machine learning dan kombinasinya dengan metode ekstraksi fitur gray level co-occurrence matrix berbasis pengolahan citra digital. Sistem pengenalan klasifikasi bunga dibagi menjadi dua bagian besar, yaitu metode ekstraksi ciri dan metode klasifikasi. Kemudian proses pengenalan menghasilkan akurasi sistem. Database bunga yang digunakan menggunakan 10 kelas bunga dan setiap kelas bunga berisi 80 citra bunga digital. Total citra dalam database yang digunakan dalam penelitian ini adalah 800 citra.
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Referensi
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