This study aims to describe language errors at the semantic level and the use of code mixing contained in Tomohiro Yamashita's Instagram account @tomoyama32. This study uses a qualitative approach to descriptive data analysis. The source of the data in this study was obtained from Tomohiro Yamashita's Instagram social media account in several posts uploaded since March 3, 2020. The data collection of this research was using the listening and recording technique and documenting it in the form of screenshots. Researchers use content analysis to simplify the process of data analysis. The most common semantic language errors found were symptoms of diction selection, namely 50 error symptoms with an error percentage of 37.9%. Hypercorrection symptoms were found to be 49 error symptoms with a percentage of 37.1%. The semantic error of pleonasm symptoms found 30 error symptoms with a percentage of 22.8%. The semantic error of ambiguity symptoms contained in the caption of Tomohiro Yamashita @tomoyama32 is only 3 error symptoms with a percentage of 2.2%. The use of code mixing found with the most common word forms was found in 32 forms with a percentage of 44.4%, phrase elements in 31 forms with a percentage of 43.1%, baster elements in 8 forms with a percentage of 11.1%, clause elements in 1 form with percentage of 1.4%. The form of mixed code elements of reduplication and idioms is not found in the 40 caption data uploaded by Tomohiro so the percentage is 0%.
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