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All Journal Briliant: Jurnal Riset dan Konseptual Journal of Chinese Language and Culture Studies
Ting, Hie Ling
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Arts Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Languange, Linguistic, Communication & Media Other

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Exploring multilingual Code-Switching in Malaysia through We-Media Perspectives Chong, Pei Qi; Ting, Hie Ling; Chan, Jie Yan; Lee, Sek Yui; Tay, Stephanie Cin Wun
Journal of Chinese Language and Culture Studies Vol. 2 No. 2 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um073v2i22023p39-45

Abstract

With the continuous development of globalization, the close contact of multiple languages has promoted the emergence of a large number of code-switching phenomena. Malaysia has the characteristics of multi-ethnic, multi-cultural and multi religious integration, which determines the phenomenon of multilingual culture in Malaysia. Malaysians use many languages to communicate. Therefore, multilingual code switching has become a unique language communication mode in Malaysia. Starting from the actual situation in Malaysia, this paper uses the video "the way Chinese speak Chinese in Malaysia" from YouTube We-Media as the research object. This paper analyzes the phenomenon of multilingual code switching in the video, analyzes and interprets its causes, so as to make a comprehensive summary of the social language phenomenon in Malaysia.
Assessment of Students in Online Industrial Practice Activities Using Machine Learning Based on Mobile Application Sunarti, Sunarti; Ting, Hie Ling; Widyatmoko, Tiksno; Bukhori, Herri Akhmad
BRILIANT: Jurnal Riset dan Konseptual Vol 7 No 2 (2022): Volume 7 Nomor 2, Mei 2022
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (211.892 KB) | DOI: 10.28926/briliant.v7i2.926

Abstract

All of the learning in the pandemic era uses online learning including practical in the industry that should do all of the students to apply their knowledge.  The practical industry online is very difficult to assement students that the assessment is given from both company and the university. Companies have many parameters to assessment and each company has different parameters. This study uses 14 parameters that are generally used in assessment for practical students and the university side using 10 parameters. The problem is that every parameter has a different weight than it makes it confusing to give marks with manual assessment. This research uses machine learning to fix this problem based on mobile applications for the user interfaces. The result of testing this application had an average accuracy for assessment students based on parameters of companies and universities that is 83,3%.
Co-Authors Chan, Jie Yan Chong, Pei Qi Herri Akhmad Bukhori Lee, Sek Yui Sunarti Tay, Stephanie Cin Wun Widyatmoko, Tiksno