Pengaruh Penggunaan Generative Artificial Intelligence terhadap Information Seeking Behavior Mahasiswa Universitas Sumatera Utara

Abstract

This study aims to examine and analyze the influence of generative artificial intelligence on the information seeking behavior of students at Universitas Sumatera Utara, using the Technology Acceptance Model (TAM) and David Ellis’s theory of information seeking behavior. A quantitative research method was employed, specifically correlational research design. The sample was determined using purposive stratified sampling. From a population of 26,012 students, a total of 203 students from 15 faculties were selected as research participants. Data were collected through questionnaires. Instrument quality testing included validity testing at a 5% significance level and reliability testing using Cronbach’s Alpha (> 0.60). Data analysis comprised descriptive statistics, classical assumption testing, simple linear regression analysis, and determination coefficient testing (R²). Hypothesis testing was conducted using F-tests and t-tests. The results indicate that all TAM indicators have a positive and significant influence on information seeking behavior. Perceived Usefulness yielded a t-value of 11.310, Perceived Ease of Use 8.343, Attitude Toward Using 9.317, Behavioral Intention to Use 9.659, and Actual Use 11.515, all exceeding the critical t-value of 1.652 with significance levels below 0.001. The coefficient of determination (R²) was 0.509, indicating that 50.9% of the variance in information seeking behavior can be explained by the use of generative artificial intelligence