Analysis of E-Commerce User Acceptance of Technology-Based Loan Application Features Using The UTAUT Model

The purpose of this study was to obtain and determine the variables that influence the interest of pay later loan users in DKI Jakarta using the modified UTAUT 2 model by adding one perceived security variable. This study used a quantitative method by distributing questionnaires online to 163 pay later users. Using the PLS-SEM analysis approach with SmartPLS 3.3, of the 11 hypotheses tested, five had a significant effect, and six had no significant effect. The relationship path that has the greatest influence is behavioral intention and use behavior, while the path that has the least influence is social influence on use behavior. The results of this study provide recommendations on performance extension by increasing the performance of the pay later feature. Effort expectancy by making it easy to activate the pay later and providing limit adjustments. Social influence creates attractive ads and expands paid information. Hedonic motivation by improving the appearance of a more attractive user interface and increasing the use of the system with user experience. Price value by providing low interest and appropriate limits. Habit by following the recommendations of all variables as a reference for future improvement steps. Facilitating conditions pay later cooperates with other merchants as a payment option to expand the network. Perceived security by implementing fingerprint locks and enhancing user information security and privacy. Behavioral intention follows all recommendations on the factors that influence intention. and use behavior following the recommendations on the factors that influence the intensity level of the user's use of the pay later.