CD Skripsi

Klasifikasi Huruf Dan Angka Dalam Bisindo Menggunakan Metode Convolutional Neural Network

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ABSTRACT
BISINDO (Indonesian Sign Language) is one of the sign languages used by the deaf community in Indonesia. In its usage, communication barriers are often encountered by individuals with hearing impairments because BISINDO is still not widely known and understood. This study employs the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. The research develops a Convolutional Neural Network (CNN) model to recognize letters and numbers in Indonesian Sign Language (BISINDO). The best model was achieved in the 32nd trial with 25 epochs, a batch size of 64, and an image size of 100x100 pixels, reaching an accuracy of 93%. The trained model is capable of accurately classifying each letter and number in BISINDO.

Keywords : BISINDO, Deaf, Deep Learning, CRISP-DM, CNN, Classification

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

2007110658

Penerbit

Pekanbaru : Universitas Riau - F. Teknik - Teknik Informatika., 2024

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

2007110658

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

INFORMATIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

Rahmat Hidayat Syahputra

Versi lain/terkait

Lampiran Berkas

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