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The growth of information technology has driven changes in consumer behavior, one of which is through e-commerce platforms such as Shopee. This phenomenon has generated a large number of customer reviews, including those for local cosmetic products such as Wardah. These reviews serve as an important source of information for understanding customer perceptions and satisfaction levels. However, manual analysis of large and linguistically diverse datasets is inefficient and potentially subjective. This study aims to implement the multi-category Naive Bayes algorithm to classify the sentiment of Wardah product reviews on Shopee into three categories: positive, negative, and neutral. The data were collected using a web scraping technique and processed through a series of preprocessing stages including case folding, tokenization, stopword removal, stemming, and text cleaning. Subsequently, term weighting was performed using the TF-IDF method prior to classification. Model performance was evaluated using a confusion matrix as well as accuracy, precision, and recall metrics. The results indicate that the multi-category Naive Bayes algorithm achieved an accuracy of 86.00%, a precision of 86.63%, and a recall of 98.24%. This approach can assist business practitioners in objectively understanding customer opinions and support decision-making in business strategy and product development.

This research investigates how celebrity endorsements, customer reviews, and pricing affect consumers’ intention to purchase Scarlett Whitening products. Amid intense competition in the skincare industry, firms are required to focus not only on product features but also on psychological and perceptual aspects that influence consumer behavior. Celebrity endorsers contribute to strengthening brand trust, customer reviews offer insight based on user experiences, while price reflects consumers’ perceived value of the product. This study adopts a quantitative explanatory design, with data obtained from 204 respondents through structured questionnaires using a five-point Likert scale. The collected data were analyzed using multiple linear regression with SPSS version 26. The findings indicate that celebrity endorsers, customer reviews, and price have both simultaneous and individual positive and significant impacts on purchase intention. An adjusted R-square value of 0.274 suggests that these variables account for 27.4% of the variation in consumers’ purchase intention. Overall, the results highlight that appropriate endorsements, trustworthy reviews, and competitive pricing collectively enhance consumers’ intention to purchase Scarlett Whitening products

This study aims to examine the influence of advertising appeal, influencer marketing, and online customer reviews on purchasing decisions in Tokopedia’s e-commerce platform. The research applied a quantitative method using survey questionnaires distributed to 109 Tokopedia users in Jakarta. Data were analyzed using path analysis with SmartPLS. The results indicate that advertising appeal and influencer marketing significantly and positively affect purchasing decisions, while online customer reviews show no significant impact. These findings suggest that Tokopedia consumers, particularly in electronic products, are more influenced by attractive advertising and influencer endorsements than by online reviews. The study is limited by its sample size, geographic scope, and product focus on electronics. Future research is recommended to expand respondents and product categories for broader insights.

This research aims to examine the influence of Brand Awareness, Social Media Marketing, and Online Customer Reviews on the purchasing decisions of Hijab Azzura among the community of Garu II Harjosari I Medan Amplas. This study uses a quantitative research method with a questionnaire research design. The subject of this research is Hijab Azzura, and the object of the study is consumers who purchase Hijab Azzura, totaling 97 respondents. Data collection techniques include observation, questionnaires, and documentation. Data analysis techniques involve validity tests, reliability tests, and classical assumption tests. The data analysis method used is multiple linear regression with the assistance of SPSS 25 software. The t-test results show that Brand Awareness has a positive effect on purchasing decisions. Social Media Marketing has a positive effect on purchasing decisions. Online Customer Reviews also influence purchasing decisions. The F-test results indicate that Brand Awareness, Social Media Marketing, and Online Customer Reviews simultaneously affect the purchasing decisions of Hijab Azzura among the community of Garu II Harjosari I Medan Amplas, with an F calculated value of 12.781 > F table value of 2.700, and a significance value of 0.000 < 0.05. The adjusted coefficient of determination (R Square) is 0.292, meaning that 29.2% of the dependent variable can be explained by the independent variables, while the remaining 70.8% is explained by other variables outside the ones studied.    

TikTok Shop is a popular application that offers online shopping and interaction experiences for consumers. Marketers at TikTok Shop use various methods to encourage consumer decisions to make purchases. This study aims to determine the effect of celebrity endorsers, online customer reviews, and viral marketing on purchasing decisions for TikTok Shop e-commerce products. This study uses a quantitative method with a survey approach by providing questionnaires to respondents. The population studied was all people in Semarang City who have the TikTok Shop application and have purchased products through the application. A sample of 112 people was taken using the convenience sampling technique. Data were obtained through questionnaires and analyzed using multiple linear regression analysis, F test, R2 test, and t test. The results of the study indicate that celebrity endorsements have a positive and significant effect on consumer purchasing decisions for Tiktok Shop users in Semarang City. The increasing use of celebrity endorsements will encourage consumer decisions to buy. Online customer reviews have a positive and significant effect on consumer purchasing decisions for Tiktok Shop users in Semarang City. The more positive online customer reviews, the more it will encourage consumer decisions to buy. Viral marketing has a positive and significant effect on consumer purchasing decisions for Tiktok Shop users in Semarang City. The increasing use of viral marketing will encourage consumer decisions to buy.  

This study is intended to identify the impact of Online Customer Reviews and Product Quality Perceptions on Skintific Purchase Decisions on TikTok Shop. This study applies a quantitative approach through causal methods. Involving 96 respondents who have purchased and used Skintific products on the platform. Data analysis was carried out through the stages of classical assumption tests (normality, multicollinearity, and heteroscedasticity), and used multiple linear regression to test the research hypothesis. The findings show that online customer reviews and product quality perceptions have a positive and significant influence on purchase decisions, both when tested individually and together. The adjusted coefficient of determination (Adjusted R²) reaches 0.875, which means that 87.5% of the variation in purchase decisions can be explained by the two independent variables, while the remaining 12.5% is influenced by external elements outside of this model. Among the two variables studied, Online Customer Reviews were proven to have a dominant influence on Purchase Decisions, with a higher Beta value than Product Quality Perception. This conclusion emphasizes that positive reviews from customers and a good view of product quality are the main drivers for consumers to purchase Skintific products on TikTok Shop. Thus, companies are advised to maintain product reputation through consistent quality as well as optimize digital communication strategies based on customer reviews to improve consumer purchasing decisions.

The growth of e-commerce in Indonesia has led to an increase in product reviews, including for beauty products on Tokopedia and Shopee. These reviews serve as important sources of information to assess consumer satisfaction; however, manually analyzing thousands of reviews daily is impractical. This study applies Natural Language Processing (NLP) with Naive Bayes, C4.5, XGBoost algorithms to classify sentiment in Indonesian-language reviews. The dataset used consists of 76,256 reviews labeled as positive, negative, and neutral. The research stages include text preprocessing, feature representation using BoW and TF-IDF, data balancing through SMOTE, and model performance evaluation based on accuracy, precision, and recall. Differences in results among the algorithms were analyzed using ANOVA. The results show that Naive Bayes achieved the highest accuracy at 67.71%, followed by XGBoost at 65.91%, and C4.5 at 58.39%, with Naive Bayes performing best in identifying positive and negative sentiments, while XGBoost and C4.5 handled more complex data patterns effectively. These findings provide guidance for sentiment analysis in Indonesian and support businesses in obtaining automated insights from customer reviews to improve product quality and services.

This study aims to analyze the impact of content marketing, influencer marketing, and online customer reviews on the purchasing interest in Skintific products on TikTok among Generation Z students of the Bachelor of Management program at Universitas Semarang. Primary data was collected through a Google Form questionnaire distributed to Generation Z students using purposive sampling technique, based on the criteria of Generation Z age, active TikTok users, and familiarity with Skintific products. A quantitative approach was applied using multiple linear regression analysis after validity, reliability, normality, multicollinearity, and heteroscedasticity tests met the requirements. The results show that content marketing, influencer marketing, and online customer reviews individually have a significant positive effect on purchasing interest in Skintific products. Simultaneously, these three variables significantly influence purchasing interest, with a strong contribution. These findings imply that an integrated digital marketing strategy involving content marketing, influencer marketing, and online customer reviews is effective in increasing purchasing interest among Generation Z students on TikTok. This provides valuable insights for companies in designing more effective digital marketing campaigns to attract young consumers through social media platforms.

The rapid expansion of e-commerce in Indonesia has resulted in a significant rise in the number of customer reviews, which serve as a valuable source of insight for understanding consumer satisfaction. This study aims to classify or identify sentiments from product reviews on the Tokopedia platform into three categories, using the Support Vector Machine algorithm. The classification method data were ethically collected through web scraping and include review text, ratings, and the number of “likes.”  The preprocessing stage involved several NLP techniques such as pre-procesesing data representation was generated using the Term Frequency–Inverse Document Frequency method, while the issue of class imbalance was addressed using the Synthetic Minority Over-sampling Technique.  Based on the test results, the SVM model achieved an accuracy of 79.48% on the test data using a linear kernel, showing the best performance in classifying positive sentiments. However, the classification of neutral and negative sentiments still requires improvement. This study demonstrates that the combination of the TF-IDF method, additional numerical features, and data balancing techniques can produce an an efficient sentiment analysis model within the e-commerce domain.

The rapid growth of Indonesia's tourism sector, especially in East Java, has increasingly created fierce competition between local culinary brands. Steamed coating product Surabaya, as one of the leading souvenirs, appears on a solid brand awerness representation with an authentic customer experience. This study empirically examines the influence of Brand Awareness and Customer Review on the Purchase Decision of Steamed Layer Products of Surabaya Heroes. A causal quantitative approach was applied by purposive sampling on 96 offline and online buyer respondents. Primary data was obtained through questionnaires, analyzed using multiple linear regression supported by validity, reliability, classical assumptions, and hypothesis tests. The results showed that there was a simultaneous positive influence of the two variables on the purchase decision (F = 92.484; Sig. = 0.000). Partially, Brand Awareness (t = 6.457; β = 0.485) was more dominant than Customer Reviews (t = 5.685; β = 0.427). Adjusted R² = 0.658 explains 65.8% of the variation in purchasing decisions, with the rest by other factors. These findings underscore the urgency of brand equity and digital management reviews to build consumer trust as well as competitive advantage.

Micro, small, and medium enterprises (MSMEs) play an important role in the Indonesian economy, both in creating jobs and strengthening the national economy. However, amid the rapid pace of digital technology development, MSMEs cannot rely solely on traditional methods such as manual or offline marketing. Indonesia is a country with a Muslim majority population. This presents a huge opportunity for the Muslim fashion industry, including the Nibras brand located in Sooko Mojokerto. This study aims to examine in depth the application of sharia marketing strategies through the 7Ps at Nibras House Sooko Mojokerto, as well as its implementation in digital marketing. The research method used a descriptive qualitative approach through interviews with the owner and employees of Nibras House Sooko Mojokerto. The results show that Nibras House Sooko Mojokerto has implemented sharia principles in all aspects of marketing with sharia-compliant products, fair prices, honest promotions, strategic locations, good staff, fast and responsive service processes, and good customer reviews. Additionally, Nibras House Sooko Mojokerto utilizes digital marketing through e-commerce and social media to expand its market and strengthen its competitiveness against new Muslim brands.

The food and beverage (F&B) industry in Indonesia has experienced rapid growth, particularly in the ice cream and frozen dessert subsector, marked by increasing sales and intensifying competition. This development requires businesses, including Mixue, to implement effective marketing strategies through the integration of digital and physical channels (Omnichannel Marketing), product assortment, and online customer reviews. This study employs a quantitative causal-associative approach using survey questionnaires analyzed with multiple linear regression to examine the influence of these variables on Mixue consumers’ purchase intention in Medan. The results indicate that Omnichannel Marketing and online customer reviews have a positive and significant effect on purchase intention, while product assortment has a positive but non-significant effect. The dominant indicator in purchase intention is exploratory interest, where consumers actively seek information and try new products. These findings emphasize that channel integration, information transparency, and product quality are key factors in enhancing consumer engagement and loyalty. Recommendations include strengthening omnichannel strategies, actively managing digital reviews, and innovating seasonal products to maintain purchase intention and expand market share.

This study examines the influence of online customer reviews and customer satisfaction on repurchase intention for Erigo fashion products sold on Shopee. The research is motivated by the rapid growth of local fashion sales on e-commerce platforms, yet the Erigo brand shows relatively low repurchase intention despite receiving many positive ratings. This gap between consumer expectations and actual experiences highlights the importance of satisfaction in driving loyalty. The study adopts a quantitative approach with descriptive and verificative methods. The population consists of Shopee consumers who have purchased Erigo products, with purposive sampling applied. A total of 362 valid responses were analyzed after outlier removal from 385 initial respondents. Descriptive results indicate that online customer reviews are categorized as very high (4.40), customer satisfaction as high (4.08), and repurchase intention as good (3.95). The findings show that online customer reviews contribute 47.70%, customer satisfaction 57.10%, and both variables jointly 59.60% to repurchase intention. Hypothesis testing confirms significant partial and simultaneous effects of both predictors on repurchase intention.

The increasing prevalence of online customer reviews has made them a critical component in consumer decision-making processes, particularly in the food and beverage sector. These reviews serve as valuable feedback, influencing both the assessment of product quality and the establishment of consumer trust. In the context of Burger Bangor in Gianyar Regency, this study aims to examine the mediating role of trust in the relationship between online customer reviews and purchasing decisions. Using a purposive sampling technique, an online survey was distributed to 100 respondents who had previously purchased Burger Bangor products. The data collected were analyzed using path analysis to test the proposed hypotheses. The findings reveal that online customer reviews significantly influence purchasing decisions by positively enhancing consumer trust. Furthermore, trust itself was found to have a strong positive effect on purchasing decisions and partially mediates the relationship between online reviews and purchasing decisions. These results highlight the importance of effectively managing online customer reviews as they not only provide crucial information to potential buyers but also play a pivotal role in building trust, which in turn influences consumer purchasing behavior. For Burger Bangor, actively responding to and leveraging these reviews can be an essential strategy for improving customer trust and increasing purchase intentions, ultimately contributing to sustained competitiveness in the food and beverage industry.

The rapid growth of e-commerce platforms has significantly transformed the way consumers share and access product feedback. One of the widely used platforms in Indonesia is Shopee, where customers actively provide reviews of various products, including local skincare brands such as Kahf facial wash. Customer reviews on e-commerce platforms contain valuable information that can be analyzed to understand consumer opinions and preferences. Sentiment analysis, as a branch of natural language processing, enables the classification of textual data into categories such as positive, negative, or neutral. This study aims to classify Shopee user sentiments regarding Kahf facial wash products by implementing the Multinomial Naïve Bayes algorithm, a well-known probabilistic classifier suitable for text categorization. The research methodology consisted of several preprocessing stages, including data cleansing, case folding, tokenizing, stopword removal, and stemming, to prepare raw review texts for further analysis. For feature representation, the Term Frequency–Inverse Document Frequency (TF-IDF) method was applied to capture the importance of words across documents. To evaluate the classification performance, K-Fold cross-validation was employed with K values of 4, 5, 6, and 10 to ensure model reliability and robustness. Considering the issue of imbalanced datasets in user-generated reviews, the Synthetic Minority Over-sampling Technique (SMOTE) was utilized to balance the distribution of sentiment classes. Based on the confusion matrix, the Multinomial Naïve Bayes algorithm demonstrated effective performance in classifying sentiments, achieving satisfactory levels of accuracy, precision, and recall across different folds. These results indicate that the algorithm is capable of handling sentiment analysis tasks for local product reviews effectively. The findings of this study are expected to provide meaningful insights for businesses in understanding consumer perceptions, thereby supporting decision-making processes in product development, marketing strategies, and customer engagement for local brands.

The rapid development of digital technology has significantly transformed consumer behavior, making online applications the primary channel for interaction and transactions. These applications provide convenience for consumers to access various products and services quickly and efficiently. In this context, the quality of service provided, along with the rating and reviews shared online, plays a crucial role in influencing purchasing decisions. For instance, the Fore Coffee app allows consumers to leave reviews and ratings, which can influence other consumers in selecting the desired products or services. These factors are essential in increasing customers' purchase intention, as consumers tend to rely on the experiences of others as references when making decisions. This study uses a quantitative approach by distributing questionnaires to consumers of the Fore Coffee app in West Surabaya. The study aims to determine the extent to which service quality, ratings, and reviews affect consumers' purchase intentions. The data collected were then processed using SPSS version 20 to conduct validity tests, reliability tests, multiple linear regression, and t-tests. Validity and reliability tests were conducted to ensure that the instruments used in this research accurately and consistently measure the relevant variables. Multiple linear regression was used to analyze the relationship between the independent variables (service quality, ratings, and reviews) and the dependent variable (purchase intention). Meanwhile, t-tests were used to examine the significant impact of each variable on purchase intention. The findings of this study can provide valuable insights for Fore Coffee in formulating more effective marketing strategies. The results indicate that service quality, ratings, and reviews significantly influence consumers' purchase intentions. With this understanding, Fore Coffee can improve the customer experience and strengthen its competitive position in an increasingly competitive market.

This study aims to analyze the sentiment of customer reviews of the Grand Jatra Hotel Pekanbaru on the Google Review platform using the Naïve Bayes algorithm. Social media and online review platforms are increasingly becoming the primary source of information for potential customers in making purchasing decisions, particularly in the hospitality sector. Therefore, sentiment analysis of customer reviews is crucial for understanding consumer perceptions and providing strategic input for hotels in improving service quality. The research data was collected using web scraping techniques to obtain publicly available customer reviews. The obtained data was then processed through text preprocessing stages including case folding, tokenizing, normalization, stopword removal, and stemming. The Term Frequency-Inverse Document Frequency (TF-IDF) method was then used to weight each word, so that more relevant words have a greater influence in the classification process. The sentiment classification process was carried out into two main categories, namely positive and negative. The Naïve Bayes model was trained using training data and then tested with test data to measure the algorithm's performance in classifying sentiment. The evaluation results show that the model built is able to achieve an accuracy level of 98%, with a precision value of 97% and a recall of 100% in the positive class, and 92% in the negative class. These findings confirm that the Naïve Bayes algorithm can be effectively used in analyzing customer sentiment towards hotel services and facilities. Practically, the results of this study are expected to provide insight for the management of Grand Jatra Hotel Pekanbaru in understanding customer perceptions, identifying service strengths and weaknesses, and formulating more targeted marketing strategies. In addition, this study can also be a reference for the development of similar studies in the hotel industry and other service sectors.

This study aims to evaluate the extent to which the Shopee e-commerce platform affects the sales rate of clothes in Pasar 16 Ilir, Palembang, which is known as one of the largest clothing trading centers in South Sumatra. The background of this research departs from the phenomenon of the rapid development of e-commerce in Indonesia, where Shopee dominates the fashion category and is the main choice of consumers in online shopping. The change in consumer behavior from conventional to digital shopping patterns encourages businesses in traditional markets to adjust strategies to remain relevant and competitive in the increasingly dynamic era of digital transformation. This research method uses a combination of quantitative and qualitative approaches. A survey was conducted on 100 sellers and 150 consumers to collect data on shopping habits, perception of promotions, and the impact of using Shopee on clothing sales. In addition, in-depth interviews with several business actors at Pasar 16 Ilir were conducted to gain a more detailed understanding of the adaptation strategies they implemented. Data analysis shows that Shopee's promotional features, such as discounts, cashback, and flash sales, are the dominant factors that increase consumer interest. Hedonistic aspects, including the convenience and pleasure of online shopping, as well as customer reviews, also have a significant influence on purchasing decisions. The results of the study confirm that the integration of Shopee with the traditional market contributes to the increase in the volume and sales value of clothes in Pasar 16 Ilir. The online-to-offline (O2O) synergy model helps merchants reach a wider market and improve their competitiveness. In conclusion, optimizing e-commerce platforms through effective promotion strategies, review management, and customer service is the key for MSME actors in facing competition in the digital era.

This study aims to reveal the influence of various factors in digital marketing on consumer purchases on the TikTok Shop platform. This study specifically aims to assess the impact of content marketing and online customer reviews on purchasing decisions with customer trust as an intervening variable on TikTok Shop customer in Pati. This study uses a quantitative method. The population studied was TikTok Shop consumers in the Pati area, with an unknown number. A total of 97 respondents were sampled through a non-probability sampling technique with a purposive sampling approach. Data analysis was carried out using SmartPls 3 software. The results of the study showed that content marketing had an influence on purchasing decisions, while online customer reviews did not have a significant influence. In addition, content marketing and online customer reviews had an effect on purchasing decisions. However, customer trust was not proven to influence purchasing decisions. Content marketing and online customer reviews also had no influence on purchasing decisions through customer trust as an intervening variable on TikTok Shop customer in Pati.

This study aims to analyze the influence of Online Customer Review and Online Customer Rating on the Loyalty of Gen Z consumers on the Shopee e-commerce platform in Medan City. The research method used is quantitative with a sample size of 55 respondents. Data were analyzed using multiple linear regression with the assistance of SPSS version 26. Validity and reliability tests indicated that the research instruments were valid and reliable. Classical assumption tests, including normality, multicollinearity, and heteroscedasticity, were met. The regression analysis results showed that Online Customer Review and Online Customer Rating have a positive and significant effect on Consumer Loyalty, both partially and simultaneously. The Adjusted R Square value of 0.263 indicates that these two variables explain 26.3% of the variation in consumer loyalty.