FITRIA, INDAH (2025) SENTIMENT ANALYSIS OF DAVIENA SKINCARE PRODUCT REVIEWS USING SUPPORT VECTOR MACHINE METHOD (CASE STUDY: SHOPEE MARKETPLACE). S1 Undergraduate thesis, UNIVERSITAS DARUSSALAM GONTOR.
Abstract
The e-commerce industry in Indonesia is driving the growth of marketplaces that make online buying and selling platforms, such as Shopee. One of the most popular product categories is skincare, which is in high demand by Indonesian consumers, especially women. Local skincare brands such as Daviena have attracted attention for offering products that are able to fulfill skincare needs. However, in choosing skincare, consumers are faced with selectivity as it suits the needs of their respective skin types. Reviews of a product that include star ratings and review comments from buyers are important to evaluate a product's quality from a user's perspective. This study collected 4,000 Daviena product reviews from shopee, utilizing web scrapy to manage the data. Sentiment analysis was conducted to classify reviews into positive, neutral, and negative categories, and help product owners understand consumer perceptions. With the classification, consumers can gain a better understanding of the quality of a product. The test results show that the highest accuracy achieved is 94% with a combination of training and test data division of 90:10 using the SVM method to perform classification. Keywords: Shopee, Skincare, Daviena brand, Sentiment analysis
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