MODEL DEEP LEARNING UNTUK PEMANTAUAN KEPATUHAN PAKAIAN MAHASISWA SEBAGAI PENDUKUNG TATA TERTIB AKADEMIK DI CYBER UNIVERSITY

• YULITA AYU WARDANI
• 14230021

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ABSTRAK

ABSTRAK

• Nama              : Yulita Ayu Wardani
• NIM                 : 14230021
• Program Studi : Ilmu Komputer
• Fakultas           : Teknologi Informasi
• Jenjang            : Strata Dua (S2)

Peminatan : Artificial Intelligence and Blockchain Judul : Model Deep Learning Untuk Pemantauan Kepatuhan Pakaian Mahasiswa Sebagai Pendukung Tata Tertib Akademik Di Cyber University Universitas Siber Indonesia (Cyber University) adalah salah satu perguruan tinggi yang sangat memperhatikan kode etik cara berpakaian mahasiswa. Penelitian ini bertujuan untuk mengembangkan model deep learning berbasis YOLO v8 untuk memantau kepatuhan berpakaian mahasiswa sebagai bentuk dukungan terhadap tata tertib akademik di perguruan tinggi. Dataset terdiri dari foto mahasiswa Cyber University yang diproses dengan teknik augmentasi seperti pemotongan, rotasi, dan pencahayaan guna meningkatkan kinerja model. Hasil penelitian menunjukkan bahwa dalam pengujian terbaik dengan dataset 70:30 (20 epochs, batch size 16, learning rate 0.001), model YOLO v8 mencapai precision 0.78, recall 0.62, F1-score 0.68, box loss sebesar 1.47, dan mAP@0.5 sebesar 0.62. Tantangan yang dihadapi dalam penelitian ini meliputi variasi pencahayaan, perbedaan pose mahasiswa, latar belakang yang kompleks, serta kemiripan warna pakaian dengan lingkungan sekitar. Meskipun dalam beberapa kondisi akurasi mencapai 33.4%-100%, diperlukan dataset lebih besar dan perbandingan model lain untuk meningkatkan akurasi Sistem ini berpotensi dapat mendukung sistem pemantauan kepatuhan berpakaian secara otomatis, efisien, dan objektif di lingkungan perguruan tinggi, sekaligus menjadi langkah awal penerapan smart campus berbasis teknologi visi komputer.

KATA KUNCI

METODE DEEP LEARNING

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DAFTAR PUSTAKA

DAFTAR PUSTAKA

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