Klasifikasi Tingkat Kematangan Tandan Buah Segar Kelapa Sawit Menggunakan Pendekatan Deep Learning

Authors

  • Jefri Zulkarnain Universitas Amikom Yogyakarta, Yogyakarta, Indonesia
  • Kusrini Universitas Amikom Yogyakarta, Yogyakarta, Indonesia
  • Tonny Hidayat Universitas Amikom Yogyakarta, Yogyakarta, Indonesia

DOI:

https://doi.org/10.23887/jstundiksha.v12i3.59140

Keywords:

Klasifikasi, Deep Learning, Tingkat Kematangan, Tandan Buah Segar Kelapa Sawit, Parameter

Abstract

Menilai kematangan Tandan Buah Segar (TBS) kelapa sawit sangat kompleks, kematangan TBS dilihat berdasarkan jumlah atau persentase dari buah yang terlepas dari TBS serta berdasarkan perubahan warna kulit luar TBS, dalam melakukan klasifikasi tingkat kematangan rentan terjadi kesalahan penilaian oleh manusia, kesalahan klasifikasi dapat terjadi oleh berbagai faktor. Untuk membantu kesalahan dalam klasifikasi, Deep learning diusulkan dalam melakukan mengklasifikasi tingkat kematangan. Tujuan dalam penelitian ini adalah menganalisis klasifikasi menggunakan Deep learning untuk memprediksi tingkat kematangan TBS kelapa sawit. Dalam penelitian ini diusulkan Deep learning dengan model ResNet50 untuk melakukan klasifikasi pada empat tingkat kematangan TBS: mentah, kurang matang, matang, dan terlalu matang. Penelitian ini akan melakukan eksperimen berdasarkan empat alokasi data, dua optimizer, dan enam learning rate serta melakukan augmentasi data. Penelitian menunjukan experimen model yang diusulkan menghasilkan kondisi terbaik alokasi data 90/10, optimizer adam, dan learning rate 0.0001 dengan precision 96%, recall 98%, F1 score 97%, dan accuracy 97%. Kesimpulan dari hasil penelitian model yang diusulkan berhasil mencapai akurasi 97%, namun demikian dalam melakukan klasifikasi tingkat kematangan membutuh data latih dengan ukuran besar untuk mendapatkan hasil kalsifikasi yang baik serta memperhatikan dataset dan metode yang digunakan.

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Published

2024-01-22

How to Cite

Zulkarnain, J., Kusrini, & Hidayat, T. (2024). Klasifikasi Tingkat Kematangan Tandan Buah Segar Kelapa Sawit Menggunakan Pendekatan Deep Learning. JST (Jurnal Sains Dan Teknologi), 12(3), 748–758. https://doi.org/10.23887/jstundiksha.v12i3.59140

Issue

Vol. 12 No. 3 (2023): Oktober

Section

Articles

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Copyright (c) 2023 Kusrini Kusrini

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