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All Journal Marlajar: Journal of Science, Technology, and Innovation
Melicha Solagratiae Sirait
Universitas HKBP Nommensen, Medan, Indonesia

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The Effect of the Intensity of Artificial Intelligence (AI) Model Use on Academic Procrastination Among Current Students Melicha Solagratiae Sirait; Hotpascaman Simbolon
Marlajar: Journal of Science, Technology, and Innovation Vol. 1 No. 2 (2026): August
Publisher : PT. TAROMBO RESEARCH DEVELOPMENT pak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66784/marlajarjournal.v1i2.53

Abstract

Advances in Artificial Intelligence (AI) have transformed the learning process in higher education by making it easier to search for information, complete assignments, and write academic papers. However, these conveniences have the potential to increase the tendency toward academic procrastination. This study aims to analyze the influence of the intention to use Artificial Intelligence on academic procrastination among currently enrolled students at HKBP Nommensen University in Medan. The study is limited to measuring the intention to use AI based on the Theory of Planned Behavior (Ajzen, 1991) and academic procrastination based on the theory by Ferrari, Johnson, and McCown (1995). This study employed a quantitative approach using a survey method involving 350 students selected through purposive sampling. Data were collected using a Likert scale, while data analysis employed simple linear regression. The results indicate that the intention to use AI has a positive and significant effect on academic procrastination (R = 0.760; R² = 0.577; t = 21.808; p < 0.001). These findings indicate that 57.7% of the variation in academic procrastination is explained by the intention to use AI, while 42.3% is influenced by other factors outside the scope of this study. Most respondents exhibited moderate levels of both AI usage intent and academic procrastination. This study concludes that the higher students’ intent to use AI, the greater their tendency toward academic procrastination. It is hoped that these findings will serve as input for higher education institutions in improving students’ AI literacy, ethical use of technology, and self-regulation skills so that the use of AI continues to support the quality of learning
Co-Authors Hotpascaman Simbolon