Accuracy Analysis of Automated Grammar Checkers: A Comparative Study between Grammarly and Quillbot in Detecting Syntactic Errors - Septiani, Riska Endah (Universitas Komputer Indonesia, 2025)
The use of Automated Grammar Checkers (AGC) has become standard in global academic writing, but their effectiveness in detecting complex syntactic structures remains questionable. This study aims to conduct a comparative study between Grammarly and Quillbot in detecting syntactic errors in English text. Using descriptive qualitative methods, the study examined ten specific syntactic error categories, including subject-verb agreement, dangling modifiers, and sentence fragments. Data were analyzed based on the accuracy of detection and the accuracy of correction suggestions provided by both platforms. Initial results indicate that Grammarly is better in detecting formal structural errors, while Quillbot focuses more on fluency of lexical variations, sometimes ignoring purely syntactic rules. These findings are expected to provide guidance for students and academics in selecting writing evaluation tools that suit their grammatical needs.