Pembangkitan Dataset Aksara Bali Menggunakan Web Scrapping untuk Pengenalan Aksara Bali Berbasis Optical Character Recognition

Authors

  • I Gede Pradipta Adi Nugraha
  • Ahmad Asroni Universitas Pendidikan Ganesha
  • Luh Joni Erawati Dewi
  • Gede Indrawan

DOI:

https://doi.org/10.31598/jurnalresistor.v6i2.1475

Keywords:

aksara bali, dataset, pengenalan karakter, web scrapping, transliterasi

Abstract

Dataset gambar aksara Bali yang besar dan komprehensif adalah sumber daya penting dalam upaya pemeliharaan warisan budaya Bali serta pengembangan aplikasi terkait. Dataset ini memungkinkan analisis mendalam, pengenalan karakter, pemrosesan bahasa, dan pengujian aplikasi seperti pengenalan tulisan otomatis, pengajaran otomatis, dan pemahaman bahasa, yang semuanya mendukung kemajuan dalam pelestarian warisan budaya Bali. Metode penelitian untuk menghasilkan dataset aksara Bali melibatkan akses ke sumber data, analisis struktur web, dan penerapan teknik web scraping dengan JavaScript untuk pengambilan gambar secara otomatis. Dua tahap utama, yaitu inisiasi dan pengumpulan data, memungkinkan pengumpulan dataset dalam jumlah besar dengan efisiensi tinggi, mempercepat proses pengumpulan data dan meningkatkan akurasi dalam penelitian aksara Bali. Data yang digunakan berasal dari kamus bahasa Bali, bahasa Indonesia, dan bahasa Inggris, dengan total 35.319 kata dalam bahasa Bali, yang kemudian dikonversi menjadi aksara Bali. Hasil dari pembuatan dataset ini mencakup 35.319 pasang data berupa gambar teks aksara Bali dan tesk transliterasinya, memiliki potensi besar untuk pelatihan model pengenalan aksara Bali dan penelitian bahasa Bali. Langkah ini menguatkan ketersediaan dataset yang relevan, berkualitas tinggi, dan memiliki nilai signifikan dalam pengembangan teknologi serta penelitian lebih lanjut di bidang bahasa Bali dan pengenalan aksara Bali.

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Published

2023-08-31

How to Cite

Nugraha, I. G. P. A. ., Asroni, A., Dewi, L. J. E. ., & Indrawan, G. . (2023). Pembangkitan Dataset Aksara Bali Menggunakan Web Scrapping untuk Pengenalan Aksara Bali Berbasis Optical Character Recognition. Jurnal RESISTOR (Rekayasa Sistem Komputer), 6(2), 92-103. https://doi.org/10.31598/jurnalresistor.v6i2.1475

Issue

Vol. 6 No. 2 (2023): Jurnal RESISTOR Edisi Agustus 2023

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Copyright (c) 2023 Ahmad Asroni, I Gede Pradipta Adi Nugraha, Luh Joni Erawati Dewi, Gede Indrawan

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