Klasifikasi Jenis Batik (Tulis, Cap, dan Printing) Menggunakan Ekstraksi Fitur Gray Level Co-occurrence Matrix dan Support Vector Machine
Kata Kunci:
Batik, Computer Vision, GLCM, SVM, Klasifikasi CitraAbstrak
Batik merupakan salah satu warisan budaya Indonesia yang memiliki berbagai teknik pembuatan, antara lain batik tulis, batik cap, dan batik printing. Meskipun memiliki proses produksi yang berbeda, ketiga jenis batik tersebut sering kali menampilkan motif yang serupa sehingga sulit dibedakan oleh masyarakat umum hanya melalui pengamatan visual. Proses identifikasi yang masih mengandalkan pengamatan manual juga membutuhkan pengetahuan dan pengalaman khusus, sehingga berpotensi menimbulkan kesalahan dalam menentukan jenis batik. Oleh karena itu, diperlukan suatu pendekatan berbasis teknologi yang mampu melakukan identifikasi secara lebih objektif dan konsisten. Penelitian ini bertujuan untuk membangun model klasifikasi jenis batik dengan memanfaatkan teknik pengolahan citra digital dan machine learning. Tahapan penelitian meliputi preprocessing citra, ekstraksi fitur tekstur menggunakan Gray Level Co-occurrence Matrix (GLCM), serta proses klasifikasi menggunakan algoritma Support Vector Machine (SVM). Dataset yang digunakan terdiri atas 300 citra batik yang dikelompokkan ke dalam tiga kelas, yaitu batik tulis, batik cap, dan batik printing. Fitur tekstur yang diekstraksi mencakup contrast, correlation, energy, dan homogeneity yang selanjutnya digunakan sebagai atribut masukan pada model klasifikasi. Hasil pengujian menunjukkan bahwa model yang dikembangkan mampu mencapai nilai accuracy sebesar 90,00%, precision sebesar 90,25%, recall sebesar 90,00%, dan F1-score sebesar 90,05%. Temuan tersebut mengindikasikan bahwa kombinasi metode GLCM dan SVM efektif dalam merepresentasikan karakteristik tekstur citra batik serta mampu membedakan jenis batik secara otomatis dengan tingkat ketepatan yang baik. Penelitian ini diharapkan dapat mendukung pemanfaatan teknologi computer vision dalam proses identifikasi batik serta berkontribusi terhadap upaya pelestarian budaya Indonesia melalui penerapan teknologi digital.
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