PENDEKATAN MLP DALAM KLASIFIKASI BAHASA ISYARAT: ANALISIS JARAK EUCLIDEAN LANDMARK TANGAN
DOI:
https://doi.org/10.31000/jika.v9i2.13368Abstract
Perkembangan teknologi Computer Vision dalam Kecerdasan Buatan (AI) mendorong inovasi teknologi yang inklusif dalam komunikasi bagi penyandang disabilitas, seperti tunarungu dan tunawicara. Penelitian ini mengembangkan model klasifikasi bahasa isyarat angka SIBI, khususnya angka 0-9 yang menggunakan jarak Euclidean antar landmark tangan sebagai fitur. Proses penelitian mencakup pengumpulan data, ekstraksi landmark tangan dengan Mediapipe, ekstraksi fitur jarak Euclidean, pelatihan model dengan Multi Layer Perceptron, evaluasi, dan implementasi real-time. Hasil penelitian menunjukkan model berhasil mengklasifikasikan pose angka 0-9 dan non-pose, dengan akurasi 87.17% dan penerapan threshold pada tahap evaluasi serta implementasi real-time untuk memastikan semua input data terklasifikasi dengan tingkat kepercayaan tinggi. Hasil penelitian ini dapat menunjang proses pembelajaran bahasa isyarat SIBI bagi penyandang disabilitas.References
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