Indonesian Sign System Introduction Application with Tensorflow Lite and Firebase Authentication
Deaf and mute individuals often face communication barriers with the general public due to limited understanding of sign language. This leads to a gap in social interaction and access to various public services. Government efforts to enhance social inclusion through various policies and programs nee...
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| Format: | Article |
| Language: | English |
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Universitas Kristen Maranatha
2025-04-01
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| Series: | JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) |
| Subjects: | |
| Online Access: | https://journal.maranatha.edu/index.php/jutisi/article/view/9678 |
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| author | Rozali Toyib Anitya Putri Affandi Mussa Ardi Wijaya Anisya Sonita |
| author_facet | Rozali Toyib Anitya Putri Affandi Mussa Ardi Wijaya Anisya Sonita |
| author_sort | Rozali Toyib |
| collection | DOAJ |
| description | Deaf and mute individuals often face communication barriers with the general public due to limited understanding of sign language. This leads to a gap in social interaction and access to various public services. Government efforts to enhance social inclusion through various policies and programs need to be accompanied by practical solutions that can help the deaf and mute interact more easily with society. This study aims to develop a mobile application that can recognize and translate Indonesian Sign Language System (SIBI) into text or speech in real-time, thus helping the deaf and mute communicate more effectively with the general public. The application is designed using TensorFlow Lite for sign language recognition and Firebase Authentication for user authentication. The application was evaluated through questionnaires involving respondents from the general public and mobile experts. The results of the general user questionnaire showed an average satisfaction percentage of 86.65%, with positive ratings for ease of use, benefits, and application interface. Meanwhile, the results of the expert mobile questionnaire showed full satisfaction with an average percentage of 100%, indicating that all application features functioned well. The findings indicate that this application is effective in recognizing and translating sign language and is well-received by the deaf, mute, and the general public. |
| format | Article |
| id | doaj-art-107e23e23f814c7097dcfd221767184e |
| institution | OA Journals |
| issn | 2443-2210 2443-2229 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Universitas Kristen Maranatha |
| record_format | Article |
| series | JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) |
| spelling | doaj-art-107e23e23f814c7097dcfd221767184e2025-08-20T02:12:33ZengUniversitas Kristen MaranathaJuTISI (Jurnal Teknik Informatika dan Sistem Informasi)2443-22102443-22292025-04-01111314810.28932/jutisi.v11i1.96789278Indonesian Sign System Introduction Application with Tensorflow Lite and Firebase AuthenticationRozali Toyib0Anitya Putri Affandi Mussa1Ardi Wijaya2Anisya Sonita3Universitas Muhammadiyah BengkuluUniversitas Muhammadiyah BengkuluUniversitas Muhammadiyah BengkuluUniversitas Muhammadiyah BengkuluDeaf and mute individuals often face communication barriers with the general public due to limited understanding of sign language. This leads to a gap in social interaction and access to various public services. Government efforts to enhance social inclusion through various policies and programs need to be accompanied by practical solutions that can help the deaf and mute interact more easily with society. This study aims to develop a mobile application that can recognize and translate Indonesian Sign Language System (SIBI) into text or speech in real-time, thus helping the deaf and mute communicate more effectively with the general public. The application is designed using TensorFlow Lite for sign language recognition and Firebase Authentication for user authentication. The application was evaluated through questionnaires involving respondents from the general public and mobile experts. The results of the general user questionnaire showed an average satisfaction percentage of 86.65%, with positive ratings for ease of use, benefits, and application interface. Meanwhile, the results of the expert mobile questionnaire showed full satisfaction with an average percentage of 100%, indicating that all application features functioned well. The findings indicate that this application is effective in recognizing and translating sign language and is well-received by the deaf, mute, and the general public.https://journal.maranatha.edu/index.php/jutisi/article/view/9678deaffirebase authenticationhard of hearingsign languagetensorflow lite |
| spellingShingle | Rozali Toyib Anitya Putri Affandi Mussa Ardi Wijaya Anisya Sonita Indonesian Sign System Introduction Application with Tensorflow Lite and Firebase Authentication JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) deaf firebase authentication hard of hearing sign language tensorflow lite |
| title | Indonesian Sign System Introduction Application with Tensorflow Lite and Firebase Authentication |
| title_full | Indonesian Sign System Introduction Application with Tensorflow Lite and Firebase Authentication |
| title_fullStr | Indonesian Sign System Introduction Application with Tensorflow Lite and Firebase Authentication |
| title_full_unstemmed | Indonesian Sign System Introduction Application with Tensorflow Lite and Firebase Authentication |
| title_short | Indonesian Sign System Introduction Application with Tensorflow Lite and Firebase Authentication |
| title_sort | indonesian sign system introduction application with tensorflow lite and firebase authentication |
| topic | deaf firebase authentication hard of hearing sign language tensorflow lite |
| url | https://journal.maranatha.edu/index.php/jutisi/article/view/9678 |
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