User Acceptance Analysis of the ChatGPT Application in Schools in South Tondano District - Indra Rianto; Tesalonika Inryanti Tampi (Jurnal Inovasi Teknologi Pendidikan, 2026)
This research aims to analyze the relationship among Perceived Ease of Use, Perceived Usefulness, and Behavioral Intention to Use within the context of technology acceptance. The research model is tested using Partial Least Squares–Structural Equation Modeling (PLS-SEM) to evaluate the validity, reliability, and the interrelationship among the variables. The analysis is conducted by examining the Measurement Model to ensure the validity and reliability of the indicators, and the Structural Model to test the research hypotheses. Validity is assessed using factor loadings, the Fornell-Larcker Criterion, and cross-loadings, while reliability is examined through Cronbach’s Alpha, composite reliability, and Average Variance Extracted (AVE). Hypotheses are tested using PLS Bootstrapping via the SmartPLS software. The results indicate that Perceived Ease of Use has a significant influence on both Behavioral Intention to Use and Perceived Usefulness. However, Perceived Usefulness does not have a significant effect on Behavioral Intention to Use. These findings underscore that ease of use is the primary factor influencing an individual’s intention to use a technology, while the perceived benefits may depend more on contextual factors. The outcomes of this study can serve as a guideline for technology developers to enhance user acceptance by focusing more on ease-of-use aspects.