Application of the PIECES Method to Determine User Satisfaction Level Analysis on the Traveloka Application

Abstract

This study evaluates the user satisfaction of the Traveloka application using the PIECES framework, which includes Performance, Information, Economy, Control, Efficiency, and Service. The population and sample of the study were Traveloka application users totaling 202 respondents. Data was collected through linear regression analysis and One-way ANOVA to examine the impact of these factors on user experience. The analysis showed highly significant p values (p < 0.001) for all independent variables, indicating that each PIECES category has a significant influence on user satisfaction. In particular, Efficiency_Index showed the strongest influence with a coefficient of 0.521 (p = 0.000), followed by Control_Index and Info_Index with coefficients of 0.251 (p = 0.002) and 0.249 (p = 0.001) respectively. The regression model explained 66.1% of the variance in Satisfaction_User_Index (R² = 0.661), which confirms the reliability of the model. These findings provide valuable insights for Traveloka to identify service strengths and weaknesses and recommend strategic improvements to enhance user experience.