Marketplace In Indonesia Research Articles

The INFORMATION SYSTEMS PERSPECTIVE: THE IMPACT OF USER INTERFACE ON CONSUMER PURCHASE INTENTIONS BASED ON A SYSTEMATIC REVIEW OF USER EXPERIENCE

Shopee is one of the largest online marketplaces in Indonesia that conducts the buying and selling process through mobile phones and adopts the concept of social media shopping. As the number of Shopee users increases, the challenges and problems increase, as does the quality of service and system accuracy. User interface (UI) plays an important role in shaping user purchase intent. Various previous studies have studied and identified user interface factors that affect Shopee consumer satisfaction, but there is still more information that can be utilized towards comprehensively understanding and analyzing the trends in UI evaluation methods used, as well as trends in UI factors that affect consumer satisfaction, and factors that affect Shopee consumers' purchase intention. Thus, a systematic review of the literature is needed. A total of 120 peer-reviewed research studies were conducted on the research topic of the impact of user interface on shopee application satisfaction published between 2019-2023 and extracted 30 relevant articles from the discussion of inclusion and exclusion criteria. The results of this study found that service quality is the main factor compared to advertisements and free shipping used in evaluating shopee, and user-friendly factors are in the main position that affects the purchase intention of the shopee application. This study provides further research topics that need to be studied further regarding advertising and free shipping in influencing consumer purchase intention seen from the UI on the shopee application.

Analysis Of The Influence Of Fake Discount Price Labels For A Product In The Marketplace On The Concept Of Business Competition And Responsibility

The influence of fake discount price labels on products in the marketplace on the concept of business competition and liability for losses experienced by consumers is an interesting topic to discuss in the ins and outs of marketplace problems in Indonesia. One of the famous marketplaces in Indonesia, namely Shopee, harbors many fraudulent practices in product sales by sellers, such as the use of fake discount price labels. Due to this, consumer trust is damaged and unhealthy business competition occurs. This research uses normative juridical legal research methods and collects secondary data from scientific sources, regulations and websites. Including fake discount price labels that do not match the actual price can harm consumers immaterially. This action violates various regulations, such as the Consumer Protection Law. The parties responsible for the losses experienced by consumers are sellers who promote fake discount prices in the marketplace. Therefore, it is necessary to discuss the influence of fake discount price labels on the concept of business competition and how to be held accountable for losses experienced by consumers

Non-linear Kernel Optimisation of Support Vector Machine Algorithm for Online Marketplace Sentiment Analysis

Twitter is a social media platform that is very important in the digital world. Fast communication and interaction make Twitter a vital information center in sentiment analysis. The purpose of this research is to classify public opinion about the presence of marketplaces in Indonesia, both positive and negative sentiments, using a Non-linear SVM algorithm based on 1276 tweets. This research involves the stages of data pre-processing, labeling, feature extraction using TF-IDF, and data division into three scenarios: 80% training data and 20% test data, 50% training data and 50% test data scenario, and 20% training data and 80% test data scenario. The last process, GridSearchCV, combines cross-validation and non-linear SVM parameters for model evaluation using a confusion matrix. The best SVM model resulting from the scenario was 80% training and 20% test data, with hyperparameters Gamma = 100 and C = 0.01, achieving 89% accuracy. When tested on never-before-seen data, the accuracy increased to 90%, with an f1-score of 91%, precision of 88%, and recall of 95% on negative sentiments. In conclusion, evaluating the performance of non-linear SVM kernels with a combination of hyperparameter values can improve accuracy, especially on public response information about online marketplaces and public sentiment.

Buying and selling activity of online game accounts containing virtual goods that are sold on an online marketplace

With so many online game players today, various problems arise. There are so many online game players today who carry out buying and selling activities on online game accounts containing virtual objects that are widely available in various marketplaces in Indonesia. However, in these activities, the buyer often suffers losses such as the account being hacked or re-accessed by the seller. For this reason, it is necessary to have the validity of buying and selling online game accounts containing virtual objects, and how to protect the law against the buyer who purchases an account containing virtual objects. This writing uses a normative juridical approach, namely by reviewing the provisions in the Civil Code regarding the validity of buying and selling and most importantly the Law No. 19 of 2016 regarding buying and selling in electronic systems, to then be analyzed descriptively qualitatively, namely by first providing a detailed description and analysis , systematic, and comprehensive regarding the laws and regulations, norms in various countries and legal theories which are then applied to the problems studied. The results of the study show that firstly, the activity of buying and selling online game accounts which contain virtual objects based on the Law No. 19 of 2016 is legal if the organizer does not prohibit the existence of buying and selling activities by third parties. Second, legal protection for buyers who purchase online game accounts containing virtual objects based on Article 30 of the Law No. 19 of 2016 is that the seller is prohibited from re-accessing accounts that have been sold, while based on Article 49 paragraph (3) Regulation No. 71 Of 2019 the buyer has the right to get a return of goods and money if there is a difference between the goods purchased and the goods received.

The Influence of Product Quality, Prices, and Promotions on Customer Satisfaction Through Purchasing Decisions as Intervening Variables for Women's Clothing Customers in The Shopee Market Place, Surabaya City

The Influence of Product Quality, Prices, and Promotions on Customer Satisfaction Through Purchasing Decisions as Intervening Variables for Women's Clothing Customers in The Shopee Market Place, Surabaya City

Evaluation of the Effectiveness of Neural Network Models for Analyzing Customer Review Sentiments on Marketplace

According to the 2019 report, Tokopedia is the most visited marketplace with 140,000,000 visitors per month, making it one of the most popular marketplaces in Indonesia. Customers have the opportunity to write reviews about the products they purchase at the end of the transaction process on Tokopedia. The aim of this research is to conduct sentiment analysis on product reviews on Tokopedia. Three neural networks that will be used for text classification are Bi-GRU, GRU, and LSTM. The data processing technique is divided into training and testing samples, split into 80%:20% using the holdout technique. The BI-GRU algorithm has an accuracy of 0.93% and precision of 0.96, better than the other two methods LSTM and GRU, which each have an accuracy of 0.92 and recall of 0.91.

PENGARUH ULASAN ONLINE, RATING, BEAUTY VLOGGER REVIEW DAN HARGA TERHADAP KEPUTUSAN PEMBELIAN PRODUK LIPSTIK HANASUI DI INDONESIA

This study aims to determine the effect of online reviews, rating, beauty vlogger reviews and prices on purchasing decisions for Hanasui Lipstick products in Indonesia. The population used in this study is consumers who have purchased Hanasui lipstick products online at marketplaces in Indonesia. The sample used was 140 respondents who met the criteria. The criteria in question are having purchased a Hanasui Lipstick product at least once online in the marketplace, a Hanasui Lipstick product user, at least 17 years – 40 years old and accessing Youtube and Tiktok as media to view product reviews from beauty vloggers. Sampling was carried out using a purposive sampling method, namely Non-probability Sampling. The method of data analysis with the help of SPSS 26. The tests used are instrument tests (validity test and reliability test), classical assumption test (normality test, multicollinearity test and heteroscedasticity test), multiple liniear regression analysis test, coefficient of determination test and hypothesis testing (t test and F test). The results of this study indicate that online reviews partially have no effect on purchasing decisions. Ratings, Beauty Vlogger Reviews and Prices partially influence Purchase decisions. Simultaneously Online Reviews, Ratings, Beauty Vlogger Reviews and Prices influence Purchasing Decisions.

Indonesian marketplace: factors in purchasing decisions and impact on sales

The current development has made everything switch to digital form, one of which is in business in Indonesia. Currently, many marketplaces have followed the times to be able to survive in the many marketplace competitions that occur in Indonesia. To maintain it, the marketplace needs to identify influences in increasing its sales. This research discusses the influence of live streaming commerce, influencer marketing, discounts, online customer reviews, on purchasing decisions and their impact on sales in the Indonesian marketplace. This research uses quantitative research methods that collect data by distributing questionnaires to marketplace users. Then the data is processed to determine the relationship between one relationship and another. With this research, it is hoped that it can be a consideration for the marketplace in Indonesia for the sustainability of its business.

POTENSI DAN TANTANGAN MANAJEMEN PEMASARAN SYARIAH DALAM INDUSTRI MARKETPLACE HALAL DI INDONESIA

The advancement of information technology has given rise to various types of online transactions, one of which is marketplace trading. At present, Indonesia is the country with the largest Muslim population in the world, reaching 86.9% of the total population, and they are also active in online shopping. Although awareness and public interest in halal products is increasing, an understanding of the urgency of transactions in accordance with sharia principles is still needed. The purpose of this research is to identify market opportunities as well as existing challenges in order to formulate strategies for developing sharia marketing management in halal marketplaces to be more optimal and in accordance with sharia principles. The research method used in this study is a literature study method. The results show that halal marketplaces in Indonesia have the potential for a large market and are an innovation from previously existing marketplaces. However, in addition to this potential, there are a number of challenges in developing a halal marketplace, including the lack of public understanding of the sharia economy, lack of involvement in the sharia financial system, and the still limited use of the halal marketplace platform by MSMEs focusing on halal products. It is hoped that this potential and challenges can serve as a guide in formulating and developing policies in this field.

Sentiment Analysis on Marketplace in Indonesia using Support Vector Machine and Naïve Bayes Method

Sentiment Analysis on Marketplace in Indonesia using Support Vector Machine and Naïve Bayes Method

Using Supervised Machine Learning to Predict Sales in Marketplaces: Case study Predicting Sales of Padimas Bread in Marketplaces in Indonesia

This project intends to apply supervised machine learning to anticipate sales of Padimas bread in marketplaces in Indonesia, with an emphasis on evaluating sales data to gain more profits and predict future income. Data from the Shopee, Tokopedia, and TikTok markets in 2023 was analyzed, employing techniques like exploratory sales data analysis and machine learning. The analysis findings encompass the top-selling products, the highest sales figures, regions with the most substantial sales, overall market sales, sales patterns, and revenue forecasts. The primary discoveries encompass the widespread appeal of chocolate toast, the most substantial sales of banana chocolate toast in West Java, and Shopee as the marketplace with the most significant sales and revenue. Sales trends exhibit a pattern of oscillation around an average value, but income from sales demonstrates a downward tendency until the 30th day. The strategic ramifications of this analysis encompass augmenting the production of sought-after goods, amplifying sales in specific regions, and delving into prospective marketplaces.

Enhancing E-Commerce with Big Data: From Browsing to Buying Through Recommendation Systems

This research focuses on analyzing the impact of a recommendation system on customer behavior in the e-commerce industry. This study examines the use of big data-driven product recommendations and tailored promotions to enhance customer engagement, conversion rates, and revenue generation. The importance of prioritizing customer engagement in the early stages of the purchasing process is emphasized, and key statistics related to customer behavior in e-commerce are presented. The objective of this research is to investigate the effectiveness of a recommendation system in influencing customer behavior and driving conversions in the e-commerce industry. The research design incorporates a case study analysis of a prominent marketplace in Indonesia. Data were collected from three automation trigger campaigns: browsing abandonment and purchase reminders. The findings of this research indicate that a recommendation system based on big data has a significant impact on customer behavior in the e-commerce industry. This research highlights the importance of prioritizing customer engagement and implementing effective recommendation systems to drive conversion rates and revenue in the e-commerce industry.

The impact of consumer reviews and ratings on purchase decisions on the Tokopedia marketplace in Indonesia

The rapid development of technology has caused a shift in consumer shopping behavior from offline to online around the world including in Indonesia, one of which is marked by the growth of e-commerce which has increased significantly. E-commerce Tokopedia is one of the largest e-commerce in Indonesia which provides a variety of features that are a source of information for consumers in determining the products that consumers will buy, one feature that is quite important is consumer reviews and ratings. The purpose of this study was to determine the effect of the variables of consumer reviews and ratings as independent variables on purchasing decisions as the dependent variable on the Tokopedia marketplace in Indonesia. This study used a survey method by distributing questionnaires to 130 respondents. The sample was taken using the purposive sampling technique, which is a sampling technique with criteria according to the researcher's determination. The analytical method used in this research is Multiple Linear Regression Analysis. The results showed that the variables of consumer reviews and judgments had a suggestive effect on the purchasing decision variable.

Criminal Law Enforcement of Book Copyright Infringement in Digital Market Places in The Ecosystem E-Commerce Through Restorative Justice

Criminal law enforcement against book copyright infringement in Indonesia is still weak and has not ensured legal certainty in its protection. Justice for copyright holders is still not achieved in a restorative manner, due to not updated copyright rules in accordance with the development of digital markets in the marketplace. The purpose of this study is to analyze criminal law enforcement, legal protection and restorative justice against copyright infringement of books on Digital Market Place in Indonesia. This research method uses normative juridical type with descriptive analysis approach and empirical comparison. The results showed that criminal law enforcement against copyright infringement of books on Digital Market Place in Indonesia is categorized in the criminal 'complaint offense' which is carried out through the initial stages of receiving complaints on copyright infringement followed up with mediation in settlement efforts, and if no settlement is found then the next stage is resolved in the judicial process through case examination, investigation and investigation, the process of interception of digital evidence and its handling up to the judicial process. Legal protection of book copyright on Digital Market Place from the perspective of law enforcement is done through efforts to protect the regulatory aspects of copyright automatically copyright holders, recording system / registration of exclusive rights; moral rights and economic rights, guidance systems and internal supervision preventively through socialization of education and respressively through monitoring the market place, as well as external supervision in customs through cooperation beacukai in tackling the sale of goods that violate copyright. Restorative Justice efforts in criminal law enforcement against copyright infringement of books on Digital Market Place is done by dispute resolution through mediation and arbitration in the commercial court. Conceptually, Restorative Justice is designed in the future with the concept of fair restitution in the recovery of repairs for damage to copyright morally and recovery of compensation for the loss of economic rights materially. As the findings of this study the concept of restitution in restorative justice is very relevant to be developed in the future in the global copyright rules along with the development of E-Commerce in the digital market.

Intention to Sell on E-Marketplace: Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Price Value

The rapid growth of electronic marketplaces in Indonesia, coupled with government encouragement for businesses, necessitates a thorough understanding of sellers' adoption factors. This study investigates the influences on e-marketplace application adoption among active Indonesian sellers, incorporating gender, age, and experience as moderating variables. Employing SMARTPLS4 and PLS SEM analysis, the research identifies significant impacts of effort expectancy, performance expectancy, and price value on e-marketplace selling behavior. Contrarily, facilitating conditions and social influence show no effect. Age moderation significantly influences effort expectancy and price value, emphasizing the importance of tailored strategies for different age groups. Gender and experience, however, do not significantly moderate the results. Sellers' expectations emphasize the need for stakeholders to ensure fairness in online transactions, urging the government to establish appropriate e-marketplace regulations, aligning with sellers' needs for a thriving digital marketplace ecosystem.

Text Mining Application With K-Means Clustering to Identify Sentiments and Popular Topics: A Case Study of The Three Largest Online Marketplaces in Indonesia

Text Mining Application With K-Means Clustering to Identify Sentiments and Popular Topics: A Case Study of The Three Largest Online Marketplaces in Indonesia

Marketplace analysis: The Effect of E-Service Quality, Product Brand Perception and Social Support on Repurchase through Consumer Satisfaction and Trust

Technological developments have an impact on business activities and consumer behavior. This can be seen from the increasing number of online businesses. This study looks at consumer behavior by exploring the relationship between e-service quality, product brand perception, and social support on satisfaction; trust; behavioral intentions & repurchases on marketplaces in Indonesia. This quantitative research uses the Structural Equation Model (SEM) method with Lisrel 88 program. The respondents in this research are 450 X-Z generation and have filled out the online questionnaires through google form. The results of this study indicates that e-service quality has a significant effect on consumer satisfaction, product brand perception has a positive impact on trust, and social support has a direct impact on both trust and behavioral intention. Satisfaction, trust, and behavioral intentions, positively affect repurchase. This research offers significant managerial implications for companies, especially in making policy and formatting strategy of business management marketing by taking into account the aspects of customer satisfaction and trust. Companies can formulate strategies through the results of this research by creating innovative products, responsive services, wider and sustainable networks.

Pengaruh e-Service Quality dan e-WOM terhadap Kepuasan Pengguna Shopee pada Ibu Rumah Tangga Pada Pembelian Produk Fashion

The current development of e-commerce has given rise to numerous marketplaces in Indonesia, one of which is Shopee. Shopee is an online-based application that enables people to shop and acquire desired products at affordable prices without being constrained by distance or time limitations. Many applications are being developed as electronic commerce (e-commerce) based apps to be installed on smartphones and made accessible to people worldwide. Researchers selected Shopee due to its higher mention frequency among housewives in Tanjung Anom regarding online shopping, and they found Shopee easier to use compared to other marketplaces. Furthermore, the availability of offline shops selling fashion items is limited, with an insufficient variety of goods, and the distance from the mall to the Tanjung Anom area is considerable. This research stands out due to the scarcity of studies conducted on housewife respondents. Its objective is to assess the extent to which e-service quality and e-WOM impact customer satisfaction using the Shopee application. The study involved a sample of 85 respondents. The research approach employed is quantitative, utilizing the Accidental Sampling technique. Data processing involves multiple linear regression analysis using the SPSS software. The research findings indicate a relationship between the independent variables, namely e-service quality and e-WOM, and the dependent variable, customer satisfaction, either partially or collectively. The independent variables, encompassing e-service quality and e-WOM, jointly exert a positive and significant influence on customer satisfaction.

Sentiment Analysis Performance Value Optimization Using Hyperparamater Tunning With Grid Search On Shopee App Reviews


 
 
 
 The rapid development of technology today has provided convenience for us in today's civilization. One of these developments is the invention of the internet due to high internet penetration and rapid growth in mobile usage, online shopping has increased tremendously. This online shopping is now often referred to as e-commerce. E-commerce is one of the trade models that has been widened under the effect of extensive use of technology. Specifically, e-commerce refers to the usage of the Internet or other networks. Shopee is one of the popular marketplaces in Indonesia that has the highest number of visitors of 129 million per month and can be downloaded on the Google Play Store. Play Store itself has several features such as Reviews that can allow users to give opinions. All complaints and opinions from shopee users can be channeled into this feature. With this a research aims to optimize the performance value of sentiment analysis with the Term Frequency-Inverse Document Frequency (TF-IDF) method and Hyperparameter Tuning with Gridsearch for the Shopee application on the Google Play Store. Based on research the reviews resulting in 3000 data where 2015 user data is positive and 985 data is negative. Testing data was split by a ratio of 90:10 for 300 data test in each classification model to find the accuracy score. With hyperparameter tuning using gridsearch we can see the result of each accuracy score of KNN, DCT, RF, and LR is increasing from 0.73 to 0.77, 0.823 to 0.826, 0.856 to 0.87, and 0.856 to 0.866. This indicated that among the machine learning model that had been tuning using gridsearch, KNN is the one that highly increased.
 
 
 

Employee Well-Being and Voice Behavior on Customer Service Performance

Purpose: The significance of customer service in determining customer happiness has become one of the key indicators for online marketplaces in Indonesia, which experienced phenomenal growth during the Covid-19 pandemic. This study aims to determine how employee well-being affects customer service personnel performance along with the mediating effect of employee voice behavior. Design/Methodology/Approach: The analysis was examined using the structural equation modelling (SEM) approach in customer service within various online marketplaces in Indonesia. Findings: This study finds that psychological well-being has a positive and significant effect on job performance. In terms of mediation effects, promotive voice and prohibitive voice behavior were found to significantly mediate employee well-being on job performance, except promotive voice on psychological well-being. Research, Practical & Social implications: Employee performance in this study was measured as perceived by customer service and gathered through cross-sectional research. Originality/Value: This study extends the knowledge about the link between employee well-being and employee voice performance as well as the mediation generated in terms of promotive and prohibitive voice behavior.