Hubungan preferensi membaca novel utuh dan Intensitas penggunaan ringkasan berbasis AI generatif dengan minat belajar sastra pada siswa SMA

Abstract

The rise of generative AI has reshaped how students find and understand literary works like novels. Still, literature class requires reading texts in full if students are to deeply understand them and build a real interest in learning. This study looks at how a preference for reading full-length novels and the frequency of using AI summaries relate to high school students' interest in literature. We used a  quantitative survey approach with correlational analysis, involving 132 eleventh-graders selected through purposive sampling. Data were gathered using a validated and reliable Likert-scale questionnaire, then processed in IBM SPSS Statistics through descriptive stats, normality tests, Pearson  correlation, and multiple linear regression. The findings show that reading whole novels has a strong positive link with interest in literature, whereas relying heavily on AI summaries shows a clear negative connection. Combined, these two factors share a moderately strong relationship with students' interest,  explaining 35.9% of the variance. Overall, these results highlight why encouraging complete reading habits matters in literature education, along with using AI as a helpful tool rather than a replacement for actual reading and appreciation.