MobileNetV3-based Handwritten Chinese Recognition Towards the Effectiveness of Learning Hanzi

MobileNetV3-based Handwritten Chinese Recognition Towards the Effectiveness of Learning Hanzi

mandarin character writing; machine learning; digital learning tool; MobileNetV2; MobileNetV3; system usability scale

Writing Mandarin characters is considered the most challenging component for beginners due to the rules and character
formations. This paper explores the potential of a machine learning-based digital learning tool for writing Mandarin
characters. It also conducts a comparative study between MobileNetV2 and MobileNetV3, exploring different configurations.
The research follows the Multimedia Development Life Cycle (MDLC) method to create both the application and machine
learning models. Participants from higher education institutions that offer Mandarin courses in Batam, Indonesia, were
involved in a User Acceptance Test (UAT). Data was gathered through questionnaires and analyzed using the System Usability
Scale (SUS) methods. The results show positive user acceptance, with an SUS score of 77.92%, indicating a high level of
acceptability. MobileNetV3Small was also preferred for recognizing the user’s handwriting, due to comparable accuracy size,
rapid inference time, and smallest model size. While the application was well-received, several participants provided constructive feedback, suggesting potential improvements

Suwarno, Tony Tan, Jonathan

http://jurnal.iaii.or.id

Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association

December 2023

Sri Wahyuni

ISSN Media Electronic: 2580-0760

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