Utilization of Artificial Intelligence in Management Information Systems to Increase Student Productivity in Early Semester

Diah Pertiwi; Dinda Qorri Aena; M. Haikal Kamil; Nova Zahrotul Muhibah; Vinka Aisyahtiawan

doi:10.31004/riggs.v5i2.12846

Authors

Diah Pertiwi Universitas Islam Negeri K.H. Abdurrahman Wahid
Dinda Qorri Aena Universitas Islam Negeri K.H. Abdurrahman Wahid
M. Haikal Kamil Universitas Islam Negeri K.H. Abdurrahman Wahid
Nova Zahrotul Muhibah Universitas Islam Negeri K.H. Abdurrahman Wahid
Vinka Aisyahtiawan Universitas Islam Negeri K.H. Abdurrahman Wahid

DOI:

https://doi.org/10.31004/riggs.v5i2.12846

Keywords:

Artificial Intelegence, Early Semester Students, Management Information Systems, Productivity

Abstract

The rapid integration of Artificial Intelligence (AI) into higher education has changed how students search for information, organize academic tasks, and produce learning outputs. This study examines the utilization of AI within personal Management Information Systems and its relationship with the productivity of early-semester students. A quantitative associative design was employed using an online questionnaire completed by 102 second-semester students, most of whom were enrolled at UIN K.H. Abdurrahman Wahid Pekalongan. The independent variable measured the intensity, accessibility, and perceived efficiency of AI use, while the dependent variable represented time management, assignment quality, and speed of task completion. The research instruments met the validity and reliability requirements, and the data fulfilled the normality and linearity assumptions. ChatGPT was the most frequently used platform (83.3%), followed by Gemini AI (49%), Claude AI (20.6%), Notion AI (3.9%), and Zotero AI (3.9%). Pearson analysis produced a positive and significant correlation of 0.374, Spearman’s rho reached 0.414, and Kendall’s tau was 0.349, with significance values below 0.001. The coefficient of determination showed that AI utilization explained 14% of the variation in student productivity. These findings indicate that AI supports faster information retrieval, better task organization, and more efficient assignment completion, although productivity is also shaped by learning motivation, prior knowledge, self-regulation, and other factors outside the model. Responsible use, digital literacy, source verification, and institutional guidance are therefore necessary to ensure that AI strengthens productivity without reducing critical thinking, creativity, academic integrity, or independent learning.

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