Error Analysis in Students` Caption
WhatsApp Stories. Supervisor: Efrika Siboro, M.Pd. Thesis. Landak Regency.
Faculty of Teacher Training and Education, Universitas Katolik Santo Agustinus
Hippo.
This research focuses on the errors made by English students in writing
captions on WhatsApp stories. The purpose of this research is to find out the most
errors in captions on WhatsApp stories of English students.
This research uses a descriptive qualitative method. The sample of this
research consisted of 10 screenshots in captions on WhatsApp stories. The data
collection instrument in this study used documentation. Data analysis techniques
include data collection, identification errors, description of errors, explanation of
error, and evaluation.
The findings revealed that the most frequent errors were omission errors
(42%), addition errors (33%), misinformation errors (17%), and misordering
errors (8%). The analysis indicates that omission errors are the most common
type, accounting for 42% of the total errors observed. This research only collected
ten samples from WhatsApp stories due to time constraints. Therefore, another
research is recommended with a larger sample size and involving all English
language students who participated in this research.