Pengembangan Sistem Pembelajaran Berbasis Deep Learning untuk Interpretasi Display Perangkat Medis
DOI:
https://doi.org/10.52436/1.jpti.1651Keywords:
Computer Vision, Deep Learning, Media Pembelajaran, Perangkat Medis, Real-Time, YOLOv8Abstract
Pembacaan manual nilai numerik pada display perangkat medis masih berpotensi menimbulkan kesalahan yang dapat berdampak pada keselamatan pasien dan kualitas layanan kesehatan. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan sistem otomatis berbasis deep learning yang mampu mengenali dan menginterpretasikan digit secara akurat, serta dapat dimanfaatkan sebagai media pembelajaran interaktif. Metode yang digunakan adalah model deteksi objek YOLOv8 yang dilatih pada dataset sebanyak 1.771 citra dengan 13 kelas. Hasil evaluasi menunjukkan bahwa model mencapai precision sebesar 0,881, recall sebesar 0,836, mAP50 sebesar 0,878, dan mAP50–95 sebesar 0,673. Hasil tersebut menunjukkan bahwa model yang diusulkan memiliki kinerja deteksi yang akurat dan andal dalam berbagai kondisi citra. Sistem kemudian diimplementasikan dalam aplikasi berbasis web yang memungkinkan deteksi digit secara real-time. Secara keseluruhan, penelitian ini menegaskan bahwa integrasi deep learning dengan sistem interaktif tidak hanya meningkatkan akurasi interpretasi display perangkat medis, tetapi juga mendukung efektivitas pembelajaran berbasis teknologi secara aplikatif.
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