GETARI: Dataset untuk Klasifikasi Gerakan Dasar Tari Bali Perempuan

Authors

  • I Putu Putra Budha Lantara Sistem Informasi, Institut Teknologi dan Bisnis STIKOM Bali
  • I Putu Dwi Payana Sistem Informasi, Institut Teknologi dan Bisnis STIKOM Bali
  • Gede Ariel Septian Pratama Sistem Informasi, Institut Teknologi dan Bisnis STIKOM Bali
  • Wayan Evan Ada Munayana Sistem Informasi, Institut Teknologi dan Bisnis STIKOM Bali
  • Kadek Sri Nopiani Sistem Informasi, Institut Teknologi dan Bisnis STIKOM Bali
  • I Nyoman Rudy Hendrawan Institut Teknologi dan Bisnis STIKOM Bali

DOI:

https://doi.org/10.23887/janapati.v11i3.52598

Keywords:

Tari Bali, klasifikasi, GETARI, VGG-LSTM, I3D

Abstract

Tari Bali adalah salah satu daya tarik kultural yang selalu dilestarikan oleh masyarakat Bali dari dulu hingga sekarang. Hingga saat ini banyak upaya telah dilakukan oleh masyarakat untuk mengabadikan karya seni Tari Bali ke dalam media digital. Salah satu pendekatan yang dapat digunakan dalam rangka preservasi karya seni Tari Bali yaitu dengan pendekatan teknologi machine learning. Pada penelitian ini dilakukan pembuatan dataset gerakan dasar Tari Bali yang merupakan kelanjutan dari penelitian sebelumnya yaitu, enam gerakan dasar Tari Bali yakni, ngelung, ngeseh, tapak sirangpada, ngeed, ngelo, dan ngumbang, yang dinamakan GETARI. GETARI kemudian diklasifikasikan dengan menggunakan model pre-trained VGG-LSTM dan I3D. Berdasarkan hasil training pada model VGG-LSTM didapatkan nilai validation loss sebesar 1,01 dan akurasi sebesar 0,57, sedangkan I3D memperoleh nilai validation loss sebesar 0,03 dan akurasi sebesar 0,97. Perubahan strategi training menurunkan validation loss VGG-LSTM menjadi sebesar 0,18 dengan akurasi mencapai 0,94. Selain itu dilakukan juga pengukuran terhadap metrik klasifikasi lainnya seperti precision, recall, dan F1. Secara keseluruhan, kinerja pada data test memperlihatkan bahwa model I3D tetap menjadi yang terbaik diantara keduanya, dengan nilai akurasi sebesar 0,97, precision sebesar 0,98, recall sebesar 0,98, dan F1 juga sebesar 0,98. Penelitian ini merupakan salah tahap awal dari pengembangan dataset gerakan dasar Tari bali dan juga pengembangan model machine learning untuk mengklasifikasikan gerakan dasar Tari Bali. Model yang dikembangan dapat dijadikan sebagai acuan dalam pengembangan model machine learning lainnya.

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Published

2022-12-27

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