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All Journal SCIENCE TECH: Jurnal Ilmiah Ilmu Pengetahuan dan Teknologi
Muiz, Choirummansyah
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Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Engineering Materials Science & Nanotechnology

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Analisis Efektivitas Customer Relationship Management (CRM) Berbasis Otomatisasi dan Artificial Intelligence Muiz, Choirummansyah; Pasmawati, Yanti; Anwar, Andries; Rizal, Syahril
Science Tech: Jurnal Ilmu Pengetahuan dan Teknologi Vol 12 No 1 (2026): February
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/st.vol12.no1.a20718

Abstract

Digital transformation in higher education has accelerated the integration of Customer Relationship Management (CRM) systems with Artificial Intelligence (AI) to enhance service quality and user loyalty. However, empirical studies examining the combined effects of service personalization, response speed, and interaction automation on user loyalty within higher education remain limited. This study aims to analyze the effectiveness of AI-based CRM implementation in the Career Center website of Universitas Bina Darma. A quantitative approach was employed using survey data collected from 215 respondents. Multiple linear regression analysis was conducted to examine the effects of Service Personalization (X1), Response Speed (X2), and Interaction Automation (X3) on User Loyalty (Y). The results indicate that all variables have a positive and significant effect on user loyalty (p < 0.05). Service personalization emerged as the most dominant factor (β = 0.413), followed by interaction automation (β = 0.265) and response speed (β = 0.231). The model demonstrates moderate explanatory power with an R² of 0.267 and an Adjusted R² of 0.257. These findings suggest that in the higher education context, AI-driven personalization and adaptive service delivery play a more critical role in fostering user loyalty than mere technical efficiency. Practically, the study recommends prioritizing data-driven personalization strategies in developing AI-based CRM systems in universities.
Co-Authors Anwar, Andries Syahril Rizal, Syahril Yanti Pasmawati