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This study examines the phenomenon of code-mixing among Generation Z in Banjarmasin, particularly in The comments section of TikTok content, which has become a primary digital expression space for young People. The aim of this study was to identify the forms, patterns, and social and cultural factors underlying This linguistic practice. Using descriptive qualitative methods with listening and note-taking techniques, Information was collected from comments on two TikTok posts on the accounts @BudRab and @Fazarbungaz. The findings indicate that the code-mixing that occurred was dominated by the insertion Of Banjarese elements into Indonesian (Banjar-Indonesian code-mixing), as well as a mixture of Banjarese, Indonesian, and English (Outer Code-mixing and Mixed Code-mixing). The forms of code-mixing found Included the insertion of Banjarese words, phrases, and lexical items such as kd (kada), makai, and mun. An analysis of the functions of code-mixing shows that this practice has a dual role: referential (for specific Local contexts), directive (to guide conversations), emotive/expressive (to indicate emotional closeness, for Example, longitude), and most importantly, as a marker of digital identity and cultural solidarity among Banjar speakers in the digital realm. This phenomenon confirms that social media serves as a new, flexible and essential space for the Banjar language to survive and negotiate with global and national languages. This study contributes to sociolinguistics by mapping the dynamics of language evolution among Gen Z in A digital context, highlighting the creative and social aspects of code-mixing.

This study aims to describe strategies for Indonesian language development through the use of Instagram, particularly the Story feature, as a medium for introducing Indonesian lexical equivalents. The study is grounded in the increasing use of foreign terms and code-mixing on social media, highlighting the need for language cultivation efforts that align with digital communication habits. A descriptive qualitative method was employed, with data collected from polls, question box responses, and user interaction metrics from the Instagram account @katasetara_. The findings indicate that respondents’ understanding of Indonesian lexical equivalents remains relatively low, as shown by the high percentage of incorrect answers for terms such as caption (57%), typo (56%), and headset (52%). By providing explanations in feed posts, the @katasetara_ account serves as an informative and engaging medium for language cultivation. This study concludes that Instagram holds strong potential as an effective platform for linguistic education when combined with interactive strategies and adherence to standard Indonesian language norms.

The research entitled Use of Language in advertisements and broadcasts on TV. The formulation of the problem is (1) How is the use of the variety of spoken language? (2) How is the use of languageseen from the accuracy of the choice of words (diction)? (3) How is the code mixing that occurs in the use of the language, the method used is a qualitative descriptive method. The source of the data used in this research is the oral utterances delivered in broadcast news. Source of data used as research data is news that is broadcast starting from the morning and at night. Technique data collection in this study used the recording method with listening and listening techniques note technique. The results of the research show that (1) the use of speech variety is variety official (2) the use of diction, then 10 of the ten news used is obtained. Of the ten types of accuracy of diction analyzed, the results of the accuracy of the use of diction were obtained, as follows: use of special general words 6, use of words that are almost synonymous 5, use of denotative and connotative words 4, use of words that are similar in spelling 1, use of idioms 1, use of foreign endings 1, and use of continuity word choice 4 found inaccurate word choice. (3) the use of mixing Indonesian code into the language Region is code mixing into (inner code-mixing) due to code mixing carried out between local languages ​​and Indonesian. based on the results obtained the researcher's observation in depth, from the use of the language used is sufficient light what else is the local language and most of the errors found are correct used. Then mix the code that is widely used in broadcast news and advertisements should be avoided because it is news for the area and speak the local language.