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In the digital era, e-commerce has developed not only as a platform for buying and selling activities but also as a strategic medium for marketing and business development. University students theoretically possess strong potential to become edupreneurs because they are closely connected to technology and supported by higher education environments. Nevertheless, the reality at Al-Amien Prenduan University indicates that students tend to act more as consumers in e-commerce rather than as entrepreneurs. This condition creates a gap between theoretical expectations and practical implementation, raising questions regarding the effectiveness of e-commerce in encouraging students’ entrepreneurial spirit. This study examines strategies for strengthening Edupreneurship graduates through the optimization of e-commerce. The research specifically explores ways to maximize e-commerce in supporting the development of Edupreneurship graduate profiles and improving graduates’ competitiveness in entrepreneurship and employment sectors. A qualitative approach with a case study method was employed at Al-Amien Prenduan University. Data were collected through observation, interviews, and documentation involving female students of the Islamic Education Edupreneurship program who actively engage in entrepreneurial activities through e-commerce platforms. The findings reveal that optimizing e-commerce can be achieved through identifying students’ digital competencies and needs, as well as utilizing flexible technologies that support broader market access and global transactions. In addition, strategies such as enhancing digital marketing creativity, strengthening market research capabilities, and understanding consumer behavior significantly contribute to entrepreneurial development. The study concludes that e-commerce effectively fosters entrepreneurial attitudes, adaptability, and competitiveness among students in facing the challenges of the digital economy.

The digital era has fundamentally transformed the market landscape, requiring e-commerce platforms to understand the determinants of consumer behavior. This study aims to analyze the role of E-commerce Trust as a mediating variable in the relationship between Perceived Ease of Use, Perceived Usefulness, and Perceived Enjoyment on Purchase Intention. Using a quantitative approach, data was collected from 326 active users of the Lazada platform in Central Java. Data analysis was conducted using the Structural Equation Modeling-Partial Least Squares (SEM-PLS) method. The results show that the three main factors ease, usefulness, and enjoyment have a positive and significant influence on Brand Trust and consumer Purchase Intention directly. Furthermore, it was found that E-commerce Trust acts as a crucial mediator that strengthens Purchase Intention through positive user experience. Theoretically, this study strengthens the Technology Acceptance Model (TAM) framework and the context of Cross-Border E-commerce (CBEC) in the digital retail industry. Practically, these findings emphasize the importance of optimizing platform features to enhance transaction convenience and security and build long-term loyalty. The research's implications suggest that platform managers should focus on both aesthetics and functionality to create a credible and enjoyable digital shopping ecosystem for consumers in developing regions.

This study aims to analyze the impact of immersive commerce and augmented reality (AR) on consumer trust in e-commerce transactions using secondary industry data from the BrandXR 2025 Research on Augmented Reality in Retail & E-Commerce. Quantitative data was analyzed descriptively to evaluate the adoption rate of immersive technologies (immersive commerce and AR) and their relationship with consumer trust perceptions. The results show that immersive commerce, characterized by interactive and realistic user experiences, has a positive impact on consumer trust. Similarly, AR which offers realistic product visualization, has a significant impact on strengthening consumer trust in purchasing decisions. Simultaneously, the integration of immersive commerce and AR enhance the digital shopping experience, which can reduce risk perception and increase trust in online transactions. These findings empirically contribute to the literature on digital consumer behavior and e-commerce strategies, and suggest that businesses adopt immersive technologies to increase consumer trust and engagement in the online commerce ecosystem.

Micro, Small, and Medium Enterprises (MSMEs) face increasing pressure to adapt to digital transformation and e-commerce in order to enhance marketing performance; however, their implementation is often constrained by limited technological utilization and low levels of consumer trust. This study aims to analyze the role of consumer trust as a mediating variable in the relationship between digital transformation, e-commerce adoption, and the marketing performance of MSMEs. A quantitative approach was employed using a survey of MSME actors in Semarang City to collect data on technology usage, consumer trust levels, and marketing performance outcomes. The results indicate that digital transformation and e-commerce adoption have a positive effect on marketing performance, while consumer trust significantly strengthens this relationship as an intervening variable. The study concludes that the success of MSME digitalization is highly dependent on the ability to build consumer trust; therefore, digital marketing strategies should prioritize enhancing credibility and improving customer experience.

This in-depth study explores the comprehensive marketing strategies implemented by CV. Logam Jaya Gallery, a leading copper and brass craft business entity in Tumang Village, Boyolali. The research aims to identify the key factors behind the company's resilience in the face of intense industry competition. Using a qualitative approach, operational data was obtained in depth. The results show that the company integrates direct marketing through national and international exhibitions, while optimizing digital channels and e-commerce for broader global market penetration. Despite its success, CV. Logam Jaya Gallery faces significant obstacles such as market demand fluctuations, limitations in manual production technology, and competitive pressures. As a mitigation measure, the company diversifies its products and adopts contemporary technology to efficiently increase its operational capacity. Strategic synergies with the government and the private sector were also strengthened to expand promotional access. This success was also supported by fundamental pillars in the form of cultural heritage and intergenerational craftsmanship. Through a combination of organized management, sustainable design innovation, and adaptation to market dynamics, the company has succeeded in establishing itself as a competitive creative industry player on the national and global stage.

The rapid growth of e-commerce in Indonesia, particularly the Shopee platform, has generated a large volume of user reviews on the Google Play Store, which can be analyzed to understand consumer sentiment. This study aims to compare the performance of the Support Vector Machine (SVM) and Random Forest (RF) algorithms in binary sentiment classification (positive and negative) on Shopee reviews, as well as to statistically test the significance of their differences using One-Way ANOVA. A total of 400,498 reviews were collected via web scraping, preprocessed through text normalization, tokenization, and Indonesian language stemming, and then feature-extracted using TF-IDF and Count Vectorizer. Evaluation results show that SVM achieved an accuracy of 91.77%, precision of 91.49%, recall of 91.77%, and F1-Score of 91.56%, while RF achieved an accuracy of 90.07%, precision of 91.68%, recall of 90.07%, and F1-Score of 90.55%. ANOVA confirmed that the performance difference between the two algorithms is statistically significant (p-value = 0.0007) with a large effect size (η² = 0.1815). Therefore, SVM is recommended as a more optimal and consistent algorithm for automated sentiment analysis of Indonesian e-commerce reviews, while also providing a replicable methodological framework for similar future research.

This research develops a machine learning model to classify customer loyalty using the Random Forest algorithm. Customer churn is a critical issue that reduces revenue and increases acquisition costs. A dataset of 50,000 customers from global e-commerce and subscription platforms was processed through data cleaning, imputation, outlier handling, and class balancing with SMOTE. The Random Forest model was built as a baseline and optimized with hyperparameter tuning. Evaluation using accuracy, precision, recall, and F1-score shows that the optimized model achieved 90.81% accuracy and 83.87% F1-score, outperforming previous Naïve Bayes approaches. Feature importance analysis highlights customer service interactions, lifetime value, and demographic factors as key predictors of churn. These findings demonstrate Random Forest’s effectiveness in churn prediction and provide practical insights for customer retention strategies

This study aims to analyze consumer purchasing behavior on e-commerce platforms using the Decision Tree algorithm as an easily interpretable classification method. The dataset used consists of 12,330 transaction records with 18 attributes representing visitor characteristics and user activities during interactions with the e-commerce platform. The research stages include data exploration to identify initial patterns, data preprocessing to handle missing values and class imbalance, splitting the data into training and testing sets, training the Decision Tree model, evaluating model performance, and visualizing the tree structure to analyze decision rules.The test results show that the Decision Tree model with a maximum depth of 3 achieves fairly good performance, with an average accuracy of 89.78%, precision of 69.82%, recall of 59.95%, and an F1-score of 64.51% for the buyer class. The visualization of the decision tree provides clear interpretation of the main attributes influencing purchasing decisions, thereby facilitating understanding for non-technical decision makers. Overall, this study demonstrates that the Decision Tree method is effective in modeling consumer purchasing behavior in e-commerce and can be utilized as a basis for data-driven business decision making, particularly in marketing strategies and improving sales conversion rates.

This community service activity aims to improve the capacity and strengthen the digital literacy of Micro, Small, and Medium Enterprises (MSMEs) in Klambir Lima Kebun Village, Hamparan Perak District, in utilizing digital technology as a means of marketing their products. The main problems faced by MSME players in this village are a low understanding of digital marketing strategies, limited effective use of social media, and a lack of ability to manage digital content that is attractive and suitable for the target market. Through this community service activity, participants were equipped with basic knowledge and digital literacy, digital marketing strategies, the use of e-commerce platforms, and techniques for creating photo and video-based promotional content. The implementation methods included socialization, practical training, and mentoring for community service participants. The results of the activity showed an increase in the understanding and skills of MSME actors in managing digital business accounts and utilizing social media such as Instagram, Facebook, and WhatsApp Business as effective marketing tools. With this activity, it is hoped that MSME actors in Klambir Lima Kebun Village will be able to expand their market reach, increase sales, and adapt to the development of the digital economy in a sustainable manner.

Micro, Small, and Medium Enterprises (MSMEs) in Indonesia and Malaysia constitute the core drivers of employment and economic growth, yet many remain constrained by limited competitiveness in international markets due to uneven digital adoption. This study addresses the problem of how international digital transformation can be effectively leveraged to enhance the performance and sustainability of Smart MSMEs, with the objective of identifying key digital strategies that support sustainable business development. Employing a mixed-methods approach, the research combines quantitative surveys of MSME actors with qualitative in-depth interviews of business owners who have implemented international digital initiatives, including cross-border e-commerce, global payment systems, and international digital marketing. The data are analyzed using descriptive and comparative techniques to examine enabling factors, challenges, and cross-country differences between Indonesia and Malaysia. The findings indicate that international digital transformation significantly improves market access, operational efficiency, and business resilience, while strategic integration of digital platforms and international networks strengthens long-term sustainability. The study concludes that developing Smart MSMEs through internationally oriented digital transformation is a critical pathway for achieving sustainable business development and enhancing regional and global competitiveness, and it offers strategic and policy-oriented recommendations for MSME stakeholders.

The development of digital technology and the Industrial Revolution 4.0 have driven significant changes in marketing activities, including for Micro, Small, and Medium Enterprises (MSMEs). The use of e-commerce has become an important digital marketing strategy for MSMEs to increase competitiveness and business revenue. This study aims to examine the role of e-commerce implementation as a digital marketing tool for MSMEs in facing the Industrial Revolution 4.0 and analyze its impact on increasing MSME revenue and competitive advantage. The research method used is a qualitative descriptive approach with data collection techniques through literature studies of various literature sources such as books, scientific journals, and online publications relevant to the research topic. The results of the study indicate that the implementation of e-commerce has a positive impact on MSMEs, including expanding market reach, increasing marketing efficiency, and driving increased business revenue. In addition, e-commerce also plays a role in increasing MSME competitive advantage through product innovation, improving service quality, and strengthening relationships with consumers. However, the implementation of e-commerce in MSMEs still faces several challenges, such as low digital literacy, limited human resources, and minimal technical assistance. Therefore, ongoing support from various parties is needed so that the use of e-commerce by MSMEs can run optimally and sustainably in the digital era.

The digital transformation era demands printing companies to strategically integrate information technology to enhance efficiency and competitiveness. CV Prima Puspasari still faces several challenges in business process management, such as unintegrated workflows, manual record-keeping, and limited utilization of information systems. This study aims to develop an Information Systems Strategic Planning (ISSP) using the Ward & Peppard method as the main analytical framework. The approach analyzes business and technology conditions through four domains: internal and external business environments, as well as internal and external IS/IT environments. The analysis combines SWOT Analysis, Value Chain Analysis, and the McFarlan Strategic Grid to identify strengths, weaknesses, opportunities, threats, and to determine application priorities. The results produce three main strategies: IS/IT business strategy, IS/IT management strategy, and IT infrastructure strategy. The recommended systems include Inventory Management System, Customer Relationship Management (CRM), Integrated Financial System, Human Resource Information System (HRIS), E-Procurement, and E-Commerce. This strategic planning is expected to serve as a roadmap for CV Prima Puspasari in implementing digital transformation, improving operational effectiveness, and strengthening its competitive advantage in the digital printing industry.

User reviews on the Shopee e-commerce platform represent an important source of information for understanding consumer perceptions of products and services. Sentiment analysis is commonly applied to classify user opinions into positive, neutral, and negative sentiment categories based on textual data. This study aims to analyze the performance of the Long Short-Term Memory (LSTM) method in sentiment classification of Shopee user reviews. The dataset used in this study consists of Indonesian-language user reviews that have undergone preprocessing stages, including case folding, text cleaning, tokenization, and stopword removal. The LSTM model was trained using preprocessed text represented as word sequences. Model performance was evaluated using overall accuracy and class-wise classification results. The experimental results indicate that the LSTM method achieved an overall accuracy of 87.62%. In addition, the classification performance for the positive sentiment class reached 95.27%, the neutral class achieved 4.96%, and the negative class reached 74.26%. These results demonstrate that the LSTM method performs well in classifying sentiment in Shopee user reviews, particularly for positive sentiment. This study is expected to provide insights and references for the application of deep learning methods in sentiment analysis of Indonesian e-commerce review data.

The development of e-commerce as part of digital transformation has changed marketing and business transaction patterns, including in the Micro, Small, and Medium Enterprises (MSMEs) sector. This study aims to analyze the implementation of e-commerce and the Quick Response Code Indonesian Standard (QRIS) payment system in increasing revenue for the Sultan Snacks MSME in Parepare City. This study used a qualitative approach with a case study method. Data collection techniques included in-depth interviews, observation, and documentation with business owners and related parties. The data obtained were analyzed using descriptive qualitative analysis techniques through the stages of data reduction, data presentation, and conclusion drawing. The results show that the implementation of e-commerce at the Sultan Snacks MSME is carried out through the use of digital platforms and social media as a means of product promotion and sales, which can expand market reach and increase the number of orders. Furthermore, the implementation of the QRIS payment system provides convenience and speed in the transaction process and helps business owners maintain more orderly financial records.

This study analyzes the influence of Islamic business ethics principles on online buying and selling transactions in the predominantly Muslim community of South Sumatra. Using a quantitative approach through a survey of 200 respondents in Palembang with a Likert scale questionnaire, the data were analyzed using multiple linear regression with SPSS 26. The results showed that the principle of honesty (sidq) had the strongest significant influence (β = 0.029, p = 0.002), followed by unity (tawhid) (β = 0.016, p = 0.049), while other principles such as balance, free will, and responsibility showed a positive but insignificant influence. The regression model explained 10.3% of the variation in transaction behavior (R² = 0.103). This study concluded that the application of Islamic ethics can increase trust and sustainability in e-commerce in the region, with implications for the development of halal businesses. In the future, the application of these principles is expected to mitigate ethical issues in e-commerce, such as fraud and uncertainty that often occur, as well as strengthen transparency and fairness in online transactions.

This research has a purpose to determine the effect of online transaction security on purchasing decisions through the Shopee application. The respondents consisted of 74 students from the Digital Business Study Program at Universitas Amikom Purwokerto who actively use Shopee. This research employed a quantitative descriptive method with simple linear regression analysis. The results indicate that online transaction security has a positive and significant effect on purchasing decisions, with a regression coefficient of 0.887 and a significance value of 0.000. The coefficient of determination of 35.2% shows that transaction security contributes to purchasing decisions, while the remaining percentage is influenced by other factors. The higher the level of security perceived by consumers during online transactions, the greater the likelihood of making a purchase. These findings highlight the importance of improving security systems and information transparency on e-commerce platforms such as Shopee to create a safe, comfortable, and trustworthy shopping experience for users.

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.

Security in e-commerce applications is a crucial factor that significantly affects user trust. Many users often feel anxious about the confidentiality of personal data, transaction security, and the potential for misuse of information. This study is a systematic literature review (SLR) using the PRISMA model, aiming to analyze in depth the influence of security on user trust in the context of e-commerce applications. Through this review, relevant previous studies on user security and trust were identified and evaluated to provide a more comprehensive understanding. The results of the analysis show that the improvement and implementation of superior security features, including strict data protection, multi-layered authentication, and transparent and robust privacy policies, have an essential role in growing and strengthening user trust. Guaranteed security not only creates a sense of convenience during the transaction process, but it is also very effective in increasing and maintaining user loyalty to the e-commerce platform in question. Improving security can be interpreted as a strategic investment for the sustainability of digital businesses.

This study aims to analyze the influence of digital marketing on customer loyalty at the Uban Muslim Clothing Store MSME in Cianjur in the context of e-commerce development. The increasingly rapid digital transformation requires MSMEs to adapt to technology-based marketing strategies to be able to compete and retain consumers. This study uses a quantitative approach with a survey technique on 20 adult respondents, both men and women, who have interacted with the store. The research instrument in the form of a questionnaire distributed through Google Forms, measuring two main variables: digital marketing (as an independent variable) and customer loyalty (as a dependent variable). The analysis technique used is simple linear regression. The results of the analysis show that there is a positive influence of digital marketing on customer loyalty, as indicated in the regression equation Y = 3.5226 + 0.582XY = 3.5226 + 0.582XY = 3.5226 + 0.582X. The regression coefficient of 0.582 indicates that every one unit increase in digital marketing activity can significantly increase customer loyalty. Meanwhile, the intercept value of 3.5226 indicates that customer loyalty remains high even without digital activities, indicating a strong foundation of loyalty from non-digital factors. This finding has important implications: digital marketing is not just a promotional tool, but a key strategy for building long-term customer engagement. This study recommends that MSMEs optimize digital content, online interactions, and data-driven communication systems to maintain and enhance customer loyalty in the digital marketing era.

This article discusses the development of an e-commerce website for a batik store as an effort to digitize marketing and improve operational efficiency. The study focuses on system development strategies, integration of essential features such as product catalogs, shopping carts, digital payment methods, and their impact on customer accessibility. A descriptive qualitative approach was used, employing observation, interviews with the store owner, and a literature review related to e-commerce and digital marketing for MSMEs. The analysis results show that the implementation of a web-based digital platform can expand market reach, enhance customer convenience in shopping, and support more organized and structured transaction recording. The website development was carried out using the Waterfall method to ensure a step-by-step and structured process. These findings indicate that digital transformation through an e-commerce website is a strategic solution for batik MSMEs in facing modern market challenges.