<![CDATA[This study aims to analyze the effects of discount and promotional strategies on impulse buying tendencies. The development of consumer behavior, particularly on digital platforms such as Shopee, has made impulse buying an increasingly relevant phenomenon to investigate, especially in relation to price incentives offered by sellers. To achieve this objective, this study employs a quantitative approach by analyzing data from 150 respondents. The analytical methods include Principal Component Analysis (PCA) to reduce ten independent variables into a simpler set of components and Principal Component Regression (PCR) to examine the effects of these components on impulse buying tendencies. The results indicate that PCA successfully reduced the dimensionality of the data. The first principal component (PC1) explained 33.49% of the total variance, while the first two components (PC1 and PC2) jointly explained 49.01%. By including the sixth component (PC6), the cumulative explained variance reached 83.48%, indicating that most of the information in the data could be represented by six principal components. In the model diagnostics, 10 out of 150 respondents had Cook's Distance values exceeding the established threshold, indicating the presence of several influential observations that should be considered when interpreting the stability of the regression model. Based on these findings, discount and promotional strategies were found to have a statistically significant relationship with impulse buying tendencies, although the presence of influential observations should be taken into account when interpreting the model results. Keywords: Principal Component Analysis, Principal Component Regression, Diskon, Promo, E-Commerce]]>
