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Article Details

Vol. 1 No. 1 (2022): November

Articles

Pengenalan Bahasa Isyarat Indonesia menggunakan Mediapipe dengan Model Random Forest dan Multinomial Logistic Regression

I Imam Suyudi S Sudadio Sudadio S Suherman Suherman
23 February 2023 Vol. 1 No. 1 (2022): November https://doi.org/10.35912/jisted.v1i1.1899
Abstract
23 Feb 2023

Purpose: This research aims to create a random forest machine learning model and logistic regression that can perform the sign language recognition of the Indonesian Sign Language System (SIBI) using a regular RGB camera with the MediaPipe framework.

Research methodology: Both variables in this study are measured using Innovative Work Behavior (IWB) Scale from Janssen (2000) and Connor-Davidson Resilience Scale (CD-RISC) from Connor & Davidson (2003) that was distributed through Google Form link. The data analysis is done with the support of the 25th version of SPSS (Statistical Package for Social Science).

Results: Resilience has a significant correlation with innovative work behavior among college students.

Limitations: No strict controls of questionnaire administration, the questionnaire consists of 6 different measurements from the research team, and can't be fully generalized to the college students population.

Contribution: New findings of correlation between two variables among new samples.

Keywords: Sign Language Recognition Indonesian Sign Language SIBI MediaPipe
How to Cite
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Suyudi, I. ., Sudadio, S., & Suherman, S. (2023). Pengenalan Bahasa Isyarat Indonesia menggunakan Mediapipe dengan Model Random Forest dan Multinomial Logistic Regression . Jurnal Ilmu Siber Dan Teknologi Digital, 1(1), 65–80. https://doi.org/10.35912/jisted.v1i1.1899
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