Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Sriwijaya Journal of Informatics and Applications
Muhammad Rasuandi
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Sign Language A-Z Alphabet Introduction American Sign Language using Support Vector Machine Muhammad Rasuandi; Muhammad Fachrurrozi; Anggina primanita
Sriwijaya Journal of Informatics and Applications Vol 4, No 2 (2023)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v4i2.74

Abstract

Deafness is a condition where a person's hearing cannot functionnormally. As a result, these conditions affect ongoing interactions,making it difficult to understand and convey information.Communication problems for the deaf are handled through theintroduction of various forms of sign language, one of which isAmerican Sign Language. Computer Vision-based sign languagerecognition often takes a long time to develop, is less accurate, andcannot be done directly or in real-time. As a result, a solution isneeded to overcome this problem. In the system training process,using the Support Vector Machine method to classify data and testingis carried out using the RBF kernel function with C parameters,namely 10, 50, and 100. The results show that the Support VectorMachine method with a C parameter value of 100 has betterperformance. This is evidenced by the increased accuracy of the RBFC=100 kernel, which is 99%.
Co-Authors M. Fachrurrozi . Primanita, Anggina