Segementasi Gambar pada Dataset MNIST dengan Optimasi Mini Batch dan K-means++ pada Algoritma K-means
DOI:
https://doi.org/10.26418/justin.v11i2.55503Keywords:
Segmentasi Gambar, Clustering, k-means, mini batch, k-means , MNISTAbstract
Proses segmentasi gambar tulisan tangan berupa gambar dengan menggunakan k-means perlu diawali dengan clusterisasi. Akibat dari proses clusterisasi ini membuat proses secara keseluruhan menjadi lambat. Penelitian ini memanfaatkan mini batch k-means untuk mempercepat proses pengenalan tulisan tangan berupa gambar. Data yang digunakan pada penelitian ini adalah dataset MNIST. Normalisasi terhadap dataset akan dilakukan terlebih dahulu sebelum clusterisasi menggunakan teknik minibatch k-means diterapkan. Selanjutnya inisiasi centroid dilakukan menggunakan k-means++. Hasil penelitian menyatakan bahwa optimasi minibatch dan k-means++ pada algoritma k-means mampu mempercepat waktu komputasi lebih singkat 28 menit 13 detik yaitu 29 menit 39 detik menjadi 1 menit 26 detik, dengan akurasi sebesar 90,13%.
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