Klasifikasi Decision Making Pelanggaran dalam Sepak Bola Berbasis 3D Convolutional Neural Network dengan Arsitektur Res-Net 50

Sanjaya, Ramadhan Djibran (2025) Klasifikasi Decision Making Pelanggaran dalam Sepak Bola Berbasis 3D Convolutional Neural Network dengan Arsitektur Res-Net 50. Bachelor thesis, Institut Teknologi Kalimantan.

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Abstract

Penelitian ini menunjukkan fluktuasi yang signifikan dalam pelatihan model dengan konfigurasi untuk mengurangi overfitting. Dalam beberapa percobaan, penggunaan konfigurasi dropout menghasilkan fluktuasi tajam, dengan performa terbaik dicapai pada epoch ke-69 dengan nilai macro average 0.7399. Teknik regularisasi menunjukkan fluktuasi yang lebih ekstrim, dengan performa tertinggi pada epoch ke-52, yaitu macro average 0.86. Ketika kedua teknik, dropout dan regularisasi, diterapkan secara bersamaan, fluktuasi yang lebih ringan terjadi, namun titik performa tertinggi tercapai pada epoch ke-89 dengan nilai macro average 0.88. Meskipun model ini menunjukkan hasil yang baik untuk klasifikasi, tantangan utama yang dihadapi adalah jumlah parameter yang terlalu besar dibandingkan dengan dataset yang ada, yang menyebabkan overfitting meskipun telah dilakukan langkah-langkah pencegahan dalam proses pra-pemrosesan dan pelatihan.

Item Type: Thesis (Bachelor)
Subjects: T Technology > T Technology (General)
Divisions: Jurusan Matematika dan Teknologi Informasi > Informatika
Depositing User: Ramadhan Djibran Sanjaya
Date Deposited: 15 Jul 2025 02:12
Last Modified: 15 Jul 2025 02:12
URI: http://repository.itk.ac.id/id/eprint/24616

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