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This study is motivated by the dynamic changes in digital consumer behavior in e-commerce, particularly in the purchase of electronic products through the Tokopedia platform. The study aims to analyze and synthesize the influence of online reviews and product ratings on purchase decisions using a systematic literature review approach. The method involves a comprehensive examination of global and local scientific literature, with a focus on peer-reviewed journals and empirical studies published between 2021 and 2026. The findings indicate that online reviews and product ratings are capable of reducing consumer uncertainty as well as the functional risks associated with electronic products. Empirical evidence over the past decade suggests that high ratings can build initial confidence in brand quality, while detailed reviews provide crucial technical validation for potential buyers. Overall, these two indicators work synergistically to strengthen consumer trust and serve as key determinants in the final stage of the purchasing decision. The implications suggest that e-commerce platforms and sellers need to prioritize the management of user-generated content and maintain transparency in reputation to remain competitive in a market increasingly reliant on the credibility of online information.

This study aimed to uncover the extent to which eWOM, perceived brand image, and platform ease of use influence consumer purchasing decisions for Skintific moisturizer on Tokopedia. The method employed was descriptive quantitative, selecting a sample of 96 consumers who had purchased Skintific products, using a purposive sampling technique based on the Lemeshow formula to ensure representativeness. Data were collected through a questionnaire and then analyzed using a series of tests including validity, reliability, classical assumption checking, multiple linear regression, and hypothesis testing using t- and F-tests. The analysis showed that eWOM contributed 13.9% to purchasing decisions, brand image 23.4%, and ease of use 46.1%. The coefficient of determination (R²) of 75.4% indicates that these variables collectively explain most of the variation in purchasing decisions. The t- and F-tests confirmed a positive and significant influence, both individually and simultaneously, on consumer purchasing behavior on Tokopedia.

This study aims to determine the influence of price and free shipping on purchasing decisions. This is a quantitative study using primary and secondary data. The sampling technique used was non-probability sampling with purposive sampling using the Slovin formula to determine the minimum number of respondents. The results of this study indicate that price influences purchasing decisions, free shipping does not influence purchasing decisions, and both price and free shipping influence purchasing decisions.

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.

The integration of Artificial Intelligence (AI) in 2025 has become one of the main pillars in improving operational efficiency in transportation service companies. This study aims to comparatively analyze the potential financial distress of PT GoTo Gojek Tokopedia Tbk as a digital company and PT Blue Bird Tbk as a conventional transportation company. The research employed a quantitative descriptive method using the Operating Cash Flow Ratio (AKO) analysis approach. The data were obtained from consolidated financial statements for the third quarter period from 2023 to 2025. The results indicate that GOTO consistently remained in the financial distress zone with negative ratio values of -0.34, -0.11, and -0.01. However, the implementation of AI technology helped improve operational efficiency, resulting in significant annual ratio improvements. On the other hand, BIRD demonstrated relatively stable and positive cash flow conditions, although in 2025 the company experienced a decline in liquidity with a ratio value of 0.69, which was below the ideal standard of 1.0. This study concludes that the AI trend in 2025 contributed to reducing operational inefficiencies in transportation companies, but it has not fundamentally eliminated the risk of financial distress in digital companies.

The trademark dispute between PT GoTo Gojek Tokopedia Tbk and PT Terbit Financial Technology has become a significant issue in the field of intellectual property law in Indonesia. This conflict arose because PT GoTo used the trademark name “GOTO,” which had already been officially registered earlier by PT Terbit. This study aims to examine the legal protection granted to registered trademark owners under Law Number 20 of 2016 concerning Trademarks and Geographical Indications, as well as to analyze the application of the first to file principle in resolving the dispute. This research employs a normative juridical approach by reviewing relevant legislation and conducting a case analysis based on the Decision of the Central Jakarta Commercial Court Number 71/Pdt.Sus-HKI/Merek/2022/PN Niaga Jkt.Pst. The findings indicate that Indonesia prioritizes the first to file system in determining trademark ownership, meaning that exclusive rights are granted to the party who registers the trademark first. The court decision in favor of PT Terbit confirms that formal registration serves as the primary legal basis for trademark protection. Therefore, this study highlights the importance of conducting trademark verification prior to public use and emphasizes the need to strengthen legal awareness among business actors to prevent similar disputes in the future.

Financial performance is an important indicator for assessing the sustainability and growth prospects of a company, where a sustained negative net profit may indicate financial and operational problems (Aminah, 2015). The purpose of this study is to analyze the financial performance of PT GoTo Gojek Tokopedia Tbk for the period 2019-2023 based on NPM, ROA, and ROE. The research method used in this study is a qualitative method with a descriptive analysis approach. The data was sourced from the official website of PT GoTo Gojek Tokopedia Tbk for the period 2019-2023. The results show that all profitability ratios, namely Net Profit Margin (NPM), Return on Assets (ROA), and Return on Equity (ROE), are in an unfavorable condition and far below the standards set by Bank Indonesia (2004), namely NPM 3%–9.5%, ROA 0.5%–1.25%, and ROE 5%–12.5%. NPM was consistently negative from -276.74% (2019) to -373.12% (2023), indicating that the company has not been able to generate net income from its revenue due to high operating expenses. ROA was also negative throughout the period, ranging from -112.57% (2019) to -167.33% (2023), indicating that assets have not been utilized efficiently. Similarly, ROE recorded negative values from -162.02% (2019) to -253.41% (2023), reflecting that shareholders' capital has not been optimally managed and has not provided returns, so that overall financial performance requires a more effective financial management strategy.

Nowadays, people are more likely to make transactions online. Online transactions are the same as offline transactions, only the online buying and selling process is carried out via the internet rather than offline, where sellers and buyers meet.  In fact, when carrying out online transactions, some customers become disappointed and disadvantaged, such as when the product ordered is not suitable or is not sent by the seller, especially for customers who experience fraud with large amounts of money.  As a result, it is very important to follow Islamic business ethics when making transactions on Tokopedia.  This research uses qualitative descriptive research where researchers use the literature study method to obtain data.  The research results show that Islamic business ethics at Tokopedia fulfill several Islamic ethical principles

This study aims to analyze the effect of e-commerce adoption on the sales performance of Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. E- commerce adoption factors are measured through the dimensions of platform usage, technology integration, and digital marketing activities. Sales performance is assessed based on sales growth, market expansion, and increase in customer numbers. The research method uses a quantitative approach by distributing online questionnaires to 250 MSME owners in five major cities (Jakarta, Surabaya, Bandung, Medan, Makassar) who have used at least one e-commerce platform (such as Tokopedia, Shopee, Bukalapak, or a standalone website) for at least one year. Data were analyzed using multiple regression analysis techniques with the help of SPSS 25 software. The results show that e-commerce adoption has a significant positive effect on the sales performance of MSMEs. Specifically, technology integration (such as the use of inventory management and digital payment tools) and digital marketing activities (advertising and promotions on social media) are the most dominant factors. These findings provide practical implications for MSME owners and policymakers to further encourage digitalization by providing training and supporting infrastructure.

This study evaluates the legal perspective concerning business competition in Indonesia regarding alleged abuse of dominant power in the competition between digital platforms TikTok Shop (including the acquisition of Tokopedia) and Shopee. The method applied is normative juridical with a case study approach, referring to Law Number 5 of 1999, particularly Articles 19–21 related to market control and Article 20 concerning below-cost selling practices. The analysis focuses on inter-platform integration, aggressive discount strategies, use of cross-platform data, as well as post-acquisition behavior that may hinder healthy competition. The assessment is conducted by considering market structure, business actors' behavior, and law enforcement efforts by the Business Competition Supervisory Commission (KPPU). Research findings indicate that although TikTok Shop has strong competitiveness following the acquisition, proving the existence of abuse of a dominant position requires meeting legal and economic provisions rigorously. Therefore, the implementation of conditional approval and remedial measures by the KPPU is considered a reasonable step to maintain a healthy business competition environment in the digital era.

This study aims to analyze the implementation of the Salam contract in the online sales system of Kwala Official, an online store selling bedding through the marketplaces Shopee, Tokopedia, TikTok, and Blibli. The research method used a qualitative case study approach, with data collection techniques through interviews, observation, and documentation. The results indicate that online sales transactions at Kwala Official reflect the principles of the Salam contract, characterized by advance payment before receiving the goods, clear product information, and guaranteed delivery times. Furthermore, the implementation of the Salam contract is further strengthened by the marketplace system, which provides advance payment facilities, return policies, and refund mechanisms, thus providing protection for buyers. The study also identified supporting factors, such as clear product descriptions and good store management, as well as inhibiting factors such as shipping delays caused by the shipping company, differences in product appearance, and marketplace technical issues. Overall, transaction practices at Kwala Official comply with the terms and conditions of the Salam contract from a Sharia perspective.

This study examines the influence of e-commerce developments on the consumption patterns of Generation Z in Indonesia, the first generation to grow up in the digital era with widespread access to technology, the internet, and social media. Using a literature review method and a qualitative descriptive approach, this study analyzes various factors influencing Gen Z's consumption behavior through e-commerce platforms such as Shopee, Tokopedia, and TikTok Shop. The findings indicate that easy access, attractive promotions such as flash sales, and interactions through social media encourage impulsive consumer behavior. However, e-commerce also has a positive impact in the form of opportunities for the development of digital MSMEs that empower the younger generation economically. Furthermore, the COVID-19 pandemic has accelerated the adoption of online shopping, changing consumption patterns and opening new opportunities for MSMEs. The main challenge faced is the risk of impulsive buying, which can lead to financial and mental health problems. Therefore, financial literacy education and digital marketing regulations are essential to shaping healthy and sustainable consumption patterns for Generation Z. This study provides insights for the government, business actors, and the public in optimizing the benefits of e-commerce while minimizing its negative impacts.  

Pakpak Bharat Gambir Tea MSMEs are products extracted from the young leaves of the Gambir plant. Not many people know about Gambir tea and its benefits or functions. Gambir tea products can only be found in online marketplaces, such as Tokopedia, Shopee, Lazada, Mbizmarket.co.id, and Indotrading, where Gambir tea producers are registered with the Pakpak Bharat Regency. One local exporter, Agro Lestari, sells "Gambier Leaf Tea" packaged in boxes with aluminum foil with 25 sachets. Offline sales in Pakpak Bharat Regency are still lacking, both in traditional markets, modern markets such as Indomaret, shops or stalls. Pakpak Bharat Gambir Tea, especially Gambir Sondel leaf tea, has been marketed to several regions in Indonesia, through wholesalers, trading partners and online resellers and social media such as TikTok, Facebook and Instagram, but the content does not provide an explanation of what Gambir tea is, its benefits or functions. The problem is:(1)What types of marketing strategies are effective? (2)How to design online and offline marketing? Objectives:(1)Help the process of understanding effective marketing strategies. (2)Help how to design online and offline marketing. The implementation of the lecture method is accompanied by questions and answers, demonstrations and practice. Gambir Pakpak Bharat tea UMKM carries out effective marketing strategies through market segmentation, targeted markets and fulfilled according to needs. The distribution system is through direct sales at outlets, delivery applications integrated with third-party applications such as GoFood or GrabFood, and online marketplaces as well as marketing communications using social media. and collaborating with local influencers

This study aims to analyze the influence of relationship marketing and e-servicescape on customer loyalty of Tokopedia users in Medan City. The rapid development of digital technology encourages Tokopedia to build long-term relationships with customers while creating a convenient and secure online shopping experience. This research employed a quantitative method with an associative approach, using data collected through questionnaires distributed to 100 Tokopedia users in Medan City and analyzed using multiple linear regression. The results show that relationship marketing has a positive and significant effect on customer loyalty, where effective communication, responsive services, and loyalty programs such as Tokopedia Points increase customer trust and emotional attachment. In addition, e-servicescape also has a positive and significant effect on customer loyalty through an attractive interface, easy navigation, and reliable transaction security. Simultaneously, both variables make a substantial contribution to building customer loyalty toward Tokopedia. Thus, effective relationship marketing strategies and high-quality digital environments are crucial factors in maintaining customer loyalty and enhancing Tokopedia’s competitiveness in the increasingly intense e-commerce industry.

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.

The rapid growth of e-commerce platforms in Indonesia, particularly Tokopedia, has resulted in a large volume of consumer reviews containing valuable information regarding customer perceptions and satisfaction. However, manual analysis of such reviews is inefficient and prone to subjectivity, necessitating an automated approach based on machine learning. This study aims to classify the sentiment of sports product reviews on Tokopedia into positive, negative, and neutral categories by applying Logistic Regression, Support Vector Machine (SVM), and Random Forest using the Term Frequency–Inverse Document Frequency (TF-IDF) approach. The data were collected through web scraping of Indonesian-language sports product reviews and processed through several preprocessing stages, including data cleaning, case folding, tokenization, stopword removal, and stemming. Feature representation was performed using TF-IDF to transform textual data into numerical vectors, after which the dataset was divided into training and testing sets with an 80:20 ratio. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. The results indicate that the application of TF-IDF significantly improves the performance of all models, with SVM consistently achieving the most optimal performance compared to Logistic Regression and Random Forest. These findings demonstrate that classical machine learning algorithms combined with TF-IDF remain highly effective for sentiment analysis of Indonesian-language text. The implications of this study are expected to assist sellers in understanding customer opinions, support consumers in making informed purchasing decisions, and serve as a foundation for the development of sentiment analysis and recommendation systems on e-commerce 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 purchase of secondhand goods, known as thrifting, involves acquiring and reselling pre-owned clothing at low cost. Originating from Western practices during the Great Depression in the United States, this activity is no longer solely about financial considerations it is also an effort to protect the ecosystem by reducing fashion waste and addressing the adverse impacts of fast fashion, such as pollution and unethical labor practices. In Indonesia, thrifting has expanded rapidly since the 2010s, supported by the creative industry, online access, and platforms like Shopee and Tokopedia. It contributes 10% to the nation’s creative economy (BPS 2022), with export value reaching Rp 100 trillion. This phenomenon has gained traction among young generations such as millennials and Gen Z, often aligning with local cultural traditions. In Maumere, a small city in East Nusa Tenggara with limited access to international fashion, thrifting has emerged as a primary option for students. Stores offer t-shirts, blouses, and dresses priced between Rp 20,000 and Rp 50,000, which suits their modest financial circumstances. Jeanette’s (Aunt Cindy’s) business focuses on top garments like crop t-shirts and crop blouses, leveraging online marketing through TikTok, Instagram, and Facebook to compensate for the store’s less-than-ideal location. This study employs a qualitative approach with direct interviews with Jeanette, using SWOT analysis for evaluation. Strengths: Affordable pricing and alignment with current fashion trends enhance customer loyalty. Weaknesses: Delayed inventory arrivals, "PHP" behavior (holding items without purchase), ineffective management, and limited product options. Opportunities: Adoption of digital technology and fashion trends. Challenges: Domestic competitors and low-priced imported goods. This study provides strategic guidance for small businesses in remote areas to adapt to the digital era.

The development of information technology in the era of globalization continues to accelerate. This has brought significant changes in various fields, one of which is online business, namely e-commerce. This study aims to analyze competition and provide optimal strategies for Shopee and Tokopedia in addressing their dependence on subsidies and large-scale discounts, so that both platforms can remain competitive effectively without experiencing a decline in profit margins. The research method used is a quantitative approach with a survey research method. The data used is primary data analyzed using Game Theory with Pure Strategy, Mixed Strategy, and Linear Programming. The results show that Shopee obtained optimal strategies for Price (proportion 0.3568) and Product Completeness (proportion 0.6427). Meanwhile, Tokopedia obtained optimal strategies for Promotion (proportion 0.3568) and Product Completeness (proportion 0.6427). The implication of this study is that companies can use the optimal strategies obtained to overcome their dependence on subsidies and large-scale discounts, which result in declining profit margins for both platforms.

This study aims to analyze the effect of liquidity and solvency ratios on the profitability of PT GoTo Go-Jek Tokopedia Tbk. The liquidity ratio in this study is measured using the Current Ratio (CR), while the solvency ratio uses the Debt to Equity Ratio (DER) and Debt to Asset Ratio (DAR). The research data includes the 2018–2020 financial statements of PT Tokopedia Tbk and the years 2021–2023 after the company transformed into PT GoTo Go-Jek Tokopedia Tbk. The research method uses a descriptive quantitative approach with secondary data from the company's annual financial statements. The results show that the company's liquidity ratio fluctuates in the range of 1.55–3.14, while the DER is in the range of 0.12–0.42 and the DAR is between 0.17–0.34. The results of the simultaneous test showed the value of sig. The F Change of 0.003 < 0.05 indicates that CR, DER, and DAR have a less significant correlation relationship with Return on Assets (ROA). A determination coefficient value of 0.382 showed that 38.2% of the ROA variables were influenced by CR and DAR, while the remaining 67.8% were explained by other factors outside the model. Overall, the research findings confirm the importance of efficient debt management and optimization of capital structure to increase the company's long-term profitability.