Jurnal Membaca Bahasa dan Sastra Indonesia
Vol 7, No 1 (2022): Jurnal Membaca (Bahasa dan Sastra Indonesia)

STUDI ANALISIS KESALAHAN BERBAHASA DALAM FORUM DISKUSI ONLINE (PLATFORM SPADA) MASA PANDEMI COVID-19 MAHASISWA UNIVERSITAS ISLAM SYEKH-YUSUF TANGERANG

Fajrin, Verawati (Universitas Islam Syekh Yusuf Tangerang)
Pratama, Aditya (Universitas Islam Syekh Yusuf Tangerang)



Article Info

Publish Date
29 Apr 2022

Abstract

This research is motivated by the existence of language related to the delivery of ideas that exist in the human mind. Submission of ideas can be done orally and in writing. In writing, the language can be used in discussion forums. The reality that has been faced since December 2019 has been the outbreak of the Corona Virus so that teaching and learning activities in universities which are usually carried out in the classroom have been switched online using various platforms. The platform used by UNIS Tangerang private university students is called SPADA (Network Learning System) which contains various learning features. The discussion forum on the SPADA Platform uses written language in the form of questions and statements that can be reviewed based on the grammatical elements used by the student seen from errors in saying various written expressions. This study uses a linguistic level by reviewing the language errors used by students in the SPADA discussion forum which can be classified into three types, namely phonologically, morphologically and syntactically. The method used in this study is a descriptive qualitative method using content analysis. The data in this study, namely utterances or speech conversations/conversations online discussion forums for Indonesian language lectures for students at the Islamic University of Sheikh-Yusuf Tangerang on the UNIS SPADA platform which shows language errors. The results of this study are as follows 1) phonological language errors as many as 30 data; 2) morphological language errors as many as 25 data; and 3) Syntax language errors as many as 23 data

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