Syntactic Analysis On The Al-Based Sentence Structure And Types In The Passages Of Bahasa Indonesia Textbook
Abstract
This study aims to analyze the syntactic complexity in the discourse of the Indonesian language textbook of the Merdeka Curriculum for grade VII SMP / MTs with the help of Artificial Intelligence (AI) in the form of Word Counter Tool and Natural Language Toolkit. This research uses a mixed-method approach with the content analysis method. The data collection techniques taken include questionnaires, document observation, and literature study. The data source in this study is the Indonesian language textbook for class VIII of the independent curriculum. The data analysis in this study used Miles and Huberman's theory, namely: (1) Data Reduction; (2) Data Presentation; and (3) Conclusion Drawing. The results of this study indicate that the complexity of syntactic aspects in Chapter 1 obtained a weighted score of 375 with a score percentage of 62.5%, chapter 2 obtained a weighted score of 324 with a score percentage of 54%, chapter 3 obtained a weighted score of 359 with a score percentage of 59.8%, chapter 4 obtained a weighted score of 534 with a score percentage of 89%, chapter 5 obtained a weighted score of 340 with a score percentage of 56.6%, and chapter 6 obtained a weighted score of 480 with a score percentage of 80%. The analysis shows variations in the number of single sentences, complex sentences, and keywords contained in each chapter. AI-based discourse analysis produces data presentations related to the application of syntactic aspects quickly and accurately.

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