Store Website Research Articles

Accelerating User Profiling in E-Commerce Using Conditional GAN Networks for Synthetic Data Generation

Abstract This paper presents the findings of a study on the profiling of online store users in terms of their likelihood of making a purchase. It also considers the possibility of implementing this solution in the short term. The paper describes the process of developing a profiling model based on data derived from monitoring user behaviour on a website. During the customer’s subsequent visits, information is collected to identify the user, record their behaviour on the page and the fact that they made a purchase. The model requires a substantial amount of training data, primarily related to the purchase of products. This represents a small percentage of total website traffic and requires a considerable amount of time to monitor user behaviour. Therefore, we investigated the possibility of using the Conditional Generative Adversarial Network (CGAN) to generate synthetic data for training the profiling model. The application of GAN would facilitate a more expedient implementation of this model on an online store website. The findings of this study may also prove beneficial to webshop owners and managers, enabling them to gain a deeper insight into their customers and align their price offers or discounts with the profile of a particular user.

Management of Management Information Systems at Jomelo Cosmetic Shop on Bukit Kaminting Induk Street, Palangka Raya City

This research explores the management of management information systems at Jomelo Cosmetic Shop on Bukit Kaminting Induk Street, Palangka Raya City using qualitative methods and a holistic approach. Data were collected through observation, interviews, and documentation. The study discovered that the deployment of a management information system has a significant impact on the efficacy of the organization's data source system, with 100% of respondents stating that SIM helps improve operational efficiency and decision-making. In the study, one hundred percent of respondents stated that SIM improves operational efficiency and decision-making processes, which shows how important the implementation of a management information system is to improve the performance of enterprise data source systems. The study recommends several measures to improve the effectiveness and efficiency of management information system, such as increasing staff training on the use of SIM (80% of respondents agreed), monitoring and evaluating SIM performance regularly (75% of respondents agreed) and optimizing the use of information technology to support SIM (65% of respondents agreed). This study also recommends several steps to improve product information for customers, such as providing more complete product information on the store website (90% of respondents agreed), utilizing social media to promote products (85% of respondents agreed), and training store staff to provide proper product information (70% of respondents agreed The findings of this study indicate that Jomelo Cosmetic Shop can improve its competitiveness and quality of service to customers by implementing best practices in information systems management. This is expected to improve operational efficiency and better delivery of product information to customers.

Framework CSS: Tailwind CSS Untuk Front-End Website Store PT. XYZ

This research aims to apply Tailwind CSS as a CSS Framework on the website store’s PT. XYZ to be more responsive and have the freedom to determine the style and layout according to the analysis of website needs. This study was carried out at PT. XYZ in Subang Regency, where conducting product transactions with customers needs the creation of a store website. The phases of requirements analysis, design, implementation, and modification are all included in the research methodology. The UI/UX design at PT is reflected in the front end of the website store. Utilize utility classes to create UI elements in Tailwind CSS during the front-end design phase. It has been demonstrated that you may implement internet shop display designs more rapidly and freely give styles and layouts according to your demands by using the Tailwind CSS Framework. In addition, the responsive display facilitates cross-platform user experience by making it simpler for customers to complete transactions.

THE FIELD APPROACH TO THE IDENTIFICATION AND EXAMINATION OF SEMANTIC GROUPS OF LANGUAGE UNITS (BASED ON THE MATERIAL OF THE GROUP “TOYS FOR CHILDREN” IN THE ENGLISH LANGUAGE)

Statement of the problem. The article considers various criteria for identifying groupings of linguistic units and the possibility of attributing a particular grouping to a certain type of semantic association of linguistic units. The objectives of the research are to describe the methods and the process of identifying semantic groupings of linguistic units, taking into account their various characteristics; to use the field method for identifying and describing the semantic field (SF) “Toys for children” in the English language and to define its boundaries. Results. The types of field structures and criteria for their differentiation are given. The methods of distinguishing lexical groupings and the fundamentals of the field theory are listed. The criteria to attribute the grouping of linguistic units naming children's toys to the semantic field are given. Dictionaries and websites of British and American stores containing catalogs of toys, as well as online platforms for the sale of children's toys serve as the sources of the research material. The quantity and quality of the material makes it possible to identify the SF “Toys for children" and define its boundaries. Conclusion. The group of English-language units “Toys for children” is one of the groupings that is dynamically replenished and updated as a result of linguistic and extralinguistic factors. The linguistic factors of the grouping growth include the detailing of toy names (doll: fashion doll, paddle doll, Matryoshka doll), the appearance of synonyms (Matryoshka doll, stacking dolls, nesting dolls, Russian tea dolls, Russian dolls), hyponyms and hyperonyms (vehicle: truck, car, bulldozer, tractor). The SF “Toys for children" is an open grouping as a result of its constant replenishment with new units (Aquabeads, Nerf blaster, glowpad, Magna Doodle, Neocube, Orbeez, flashlight projector.).

Experience in Developing an Auto Parts Online Store Website Using the Yii Framework and Integration with the Company's Corporate Information System

Experience in Developing an Auto Parts Online Store Website Using the Yii Framework and Integration with the Company's Corporate Information System

Sentiment Analysis of Honkai: Star Rail Indonesian Language Reviews on Google Play Store Using Bidirectional Encoder Representations from Transformers Method

Online games are a type of entertainment that is done by humans to have fun and forget all the problems in everyday life. Honkai: Star Rail is a new online game application owned by miHoYo which is currently popular and widely downloaded on the Google Play Store. Reviews on the Honkai: Star Rail app are increasing over time so this makes it difficult for app developers to know past user reviews on their apps. Therefore, the author conducted a study to analyze sentiment towards Honkai: Star Rail application reviews in Indonesian on the Google Play Store using the Bidirectional Encoder Representations from Transformers (BERT) method to determine user sentiment towards the Honkai: Star Rail application and then processed further so that it becomes a record for developers, users, and prospective users of the Honkai: Star Rail application. This study uses Indonesian language review data from users of the Honkai: Star Rail application found on the Google Play Store website as many as 6000 reviews. The BERT method applied in this study consisted of data collection, dataset labeling, data preprocessing, dataset splitting, modeling, model training, and evaluation. Based on the evaluation results that have been carried out on the test data, 97 data are true positive with 27 data are false positive, 4 data are true neutral with 47 data are false neutral, and 381 data are true negative with 37 data are false negative. So, it can be concluded that the model still has difficulty predicting reviews with neutral sentiment but is good enough at predicting reviews with positive and negative sentiment. In addition, the accuracy of the model is 81% with a precision of 63% for positive sentiment reviews, 36% for neutral sentiment reviews, and 89% for negative sentiment reviews.

Digital exposure notification tools: A global landscape analysis.

As the COVID-19 pandemic continues, digital exposure notification systems are increasingly used to support traditional contact tracing and other preventive strategies. Likewise, a plethora of COVID-19 mobile applications have emerged. Objective: To characterize the global landscape of pandemic related mobile applications, including digital exposure notification and contact tracing tools. The following queries were entered into the Google search engine: "(*country name* COVID app) OR (COVID app *country name*) OR (COVID app *country name*+) OR (*country name*+ COVID app)". The App Store, Google Play, and official government websites were then accessed to collect descriptive data for each application. Descriptive data were qualified and quantified using standard methods. COVID-19 Exposure Notification Systems (ENS) and non-Exposure Notification products were categorized and summarized to provide a global landscape review. Our search resulted in a global count of 224 COVID-19 mobile applications, in 127 countries. Of these 224 apps, 128 supported exposure notification, with 75 employing the Google Apple Exposure Notification (GAEN) application programming interface (API). Of the 75 apps using the GAEN API, 15 apps were developed using Exposure Notification Express, a GAEN turnkey solution. COVID-19 applications that did not include exposure notifications (n = 96) focused on COVID-19 Self-Assessment (35·4%), COVID-19 Statistics and Information (32·3%), and COVID-19 Health Advice (29·2%). The digital response to COVID-19 generated diverse and novel solutions to support non-pharmacologic public health interventions. More research is needed to evaluate the extent to which these services and strategies were useful in reducing viral transmission.

PERANCANGAN SISTEM INFORMASI PENJUALAN PADA TOKO BUKU BINA MEDIA SARANA BERBASIS WEBSITE

Bina Media Sarana bookstore needs to adopt information technology to enhance the efficiency and quality of its book sales services. In this context, the author designs a website-based sales information system to optimize the store's operations and expand its market reach. This study aims to design an effective and practical sales information system for the bookstore. Through needs analysis, intuitive user interface design, structured database development, and website-based system implementation, these objectives can be achieved. The sales information system enables customers to make online book purchases through the store's website. Additionally, it assists the store owner in inventory management, order processing, sales analysis, and shipment tracking. By implementing this system, it is expected that Bina Media Sarana Bookstore can improve operational efficiency, enhance the quality of customer service, and expand market reach through online presence. Furthermore, this system provides a competitive advantage for the store in the increasingly competitive book sales industry in this digital era.

THE INFLUENCE OF ONLINE CUSTOMER REVIEWS AND E-SERVICE QUALITY ON BUYING DECISIONS IN ELECTRONIC COMMERCE

Tokopedia online store has seen a drop in visitors; the drop in online shop visitors at Tokopedia can be interpreted as consumer purchasing decisions at Tokopedia remaining unappealing to the general public, so the Tokopedia online store redoubles its efforts to prevent customers from switching to other online store websites. Requirements for elements that impact purchasing decisions at the Tokopedia online store, such as online customer reviews and the influence of e-services. The purpose of the review is to decide and assess the impact. 1. Determine the impact of an online client survey on purchasing decisions. 2. To determine the impact of e-services on purchasing decisions. 3. To determine the simultaneous impact of online customer reviews and e-service quality on purchasing decisions. Exploration utilizing quantitative methodologies. As many as 278 people participated in the exploratory test. SPSS is used to manage the testing. Given the effect of reviews that online customer reviews influence purchase choices at the Tokopedia online store, e-service quality influences purchase choices at the Tokopedia online store, the concurrent impact of online customer reviews and e-service quality on purchasing decisions at the Tokopedia online store. Tokopedia is an online shopping mall.

PENGARUH KUALITAS INFORMASI DAN PELAYANAN TERHADAP KEPUASAN PELANGGAN DAN MINAT BELI ULANG PADA SITUS BELANJA ONLINE SHOPEE

The observe aims to have a look at The effect Of information pleasant And carrier excellent On client delight And Repurchase aim On on-line store websites In Shopee for patron Shopee in Indonesia. The sampling approach used in this look at is nonprobability sampling, specifically the purposive sampling technique. The range of sampling used in this observe consisted of a 170 respondents aged 18-26. The approach of amassing statistics the use of survey technique. The analytical tool utilized in the SEM (structural equation version) with the AMOS 22 application program. The result shows that information quality has a effective and enormous impact on Repurchase purpose. Carrier first-class has a fine and good sized impact on Repurchase purpose. Purchaser satisfaction has a fantastic and substantial impact on Repurchase aim. Information best has a positive and significant impact on patron pride. Service first-rate has a effective and enormous effect on client pleasure. Client satisfaction mediates statistics first-class with Repurchase aim. Client satisfaction mediates carrier nice with Repurchase intention. 

Machine Learning Approach for Prediction of the Online User Intention for a Product Purchase

The deployment of self-learning computer algorithms that can automatically enhance their performance via experience is referred to as machine learning in ecommerce and is a crucial trend of the retail digital transformation. Machine learning algorithms can be unambiguously trained by analysing big datasets, identifying repeating patterns, relationships, and anomalies among all of this data, and creating mathematical models resembling such associations. These models are improved when the algorithms analyse ever-increasing amounts of data, providing us with useful insights into specific ecommerce-related events and the links between all the variables that underlie them. A tool that has been quite effective in studying current affairs, predicting future trends, and making data-driven decisions. The present work investigates the implementation of machine learning algorithms to predict the user intention for purchasing a product on a specific store's website. An Online Shoppers Purchasing Intention data set from the UC Irvine Machine Learning Repository was used for this investigation. In this study, two classification-based machine learning algorithms i.e. Stochastic Gradient Descent (SGD) algorithm and Random Forest algorithm were used. SGD algorithm was used for first time in prediction of the online user intention. The results showed that the Random Forest resulted in the highest F1-Score of 0.90 in contrast to the Stochastic Gradient Descent algorithm.

Primeiro registro da espécie exótica, plati Xiphophorus maculatus (Günther, 1866), na área de inundação urbana de um rio neotropical brasileiro

Abstract: Aim This work reports the first occurrence of the exotic species Xiphophorus maculatus (Günther, 1866) in the Sorocaba River Basin. The introduction of non-native fish species has become common and many species have been introduced mainly through sport fishing, aquaculture and aquarium keeping. In the case of the Poeciliidae, most of the introduced species that have been recorded come aquarium keeping. The environment where the specimens were captured had a large number of macrophytes due to anthropization and is located in a strictly urbanized area of the municipality. Methods The collection was done through a rectangular dip net, with measures of 70 cm x 60 cm and a mesh of 1 mm. The specimens were anesthetized in eugenol solution, fixed in 10% formalin solution and preserved in 70% alcohol. The specimens were later deposited in a scientific collection. Results The record includes two female specimens from an urban wetland on the Sorocaba River, São Paulo State, Brazil. Conclusions In the municipality of Sorocaba, 63 species of fish have already been identified, belonging to 7 orders and 19 families and 6 are exotic, such as the Xiphophorus maculatus. Urban floodplains are poorly studied environments, thus presenting great potential for the occurrence of species that have not yet been inventoried. The monitoring and inventory of exotic species must be carried out systematically so that mitigating measures can be proposed in relation to the control of these species, and this is one of the major causes of biodiversity loss. In addition, developing a program for returning unwanted fish to aquarium stores can be effective in preventing the introduction of new aquarium fish and displaying warnings informing of the negative ecological effects of releasing aquarium fish in all bags, fish plastics, and aquarium store websites.

Analisis Potensi Pasar Dan Persaingan Wall Decoration Berbahan Metal di Marketplace dengan Metode Roda Deming

This research aims to determine the market potential and business opportunities for wall decorations made of metal with CNC laser in the industry by determining the market size, evaluating competition, determining product trends, and identifying business opportunities. The quality management method of Deming's Wheel or PDCA (Plan-Do-Check-Act) is used to analyze the market potential and competition of metal wall decoration products in various marketplaces. The research results show that Shopee is the e-commerce platform that sells the most metal wall decorations in Indonesia. The sales of metal wall decorations on Shopee reached 17,830 units, followed by Lazada with 2,794 units and Tokopedia with 789 units. The most popular motif or design among consumers is the leaf motif, with a total sales of 14,600 units on Shopee. The average monthly sales on Shopee are quite high, where store A is able to sell 160 units of wall decoration. The factors that influence high sales are quick chat replies, high ratings, positive testimonials from customers, and having their own online store website. Having their own online store provides advantages for store owners, such as advertising.

Design and Build Online Store Website at Toko Mas Djanoko

Sources of information and media for communication are incredibly simple for us to obtain and use in the development of technology in the era of digital transformation as it is today. The internet is one example of how quickly information and communication technology has advanced. There is little doubt that this has a significant impact on many areas, including the business sector. Businesses can expand quickly in their ability to perform trading activities thanks to technology improvements. Even though technology has evolved and changed, many firms are still unable to keep up with new developments. Toko Mas Djanoko is one illustration. This jewelry store continues to sell its goods using traditional strategies. Toko Mas Djanoko is undoubtedly not benefiting from this too much. By developing a store website that is connected to the marketplace, this study aims to offer Toko Mas Djanoko a solution for marketing and introducing their items. It is intended that this website would make Toko Mas Djanoko more successful at selling their goods. adopting the System Development Life Cycle (SDLC) approach to system development. The study's findings show that Toko Mas Djanoko's items may be successfully and widely marketed thanks to the website system that was developed.

Implementation Of Teak Furniture Sales Information System In Mass Furniture Shop

The rapid development and growth of information technology has a positive impact on agencies engaged in industry, sales, and services. Currently, sales are no longer carried out by sellers and buyers who meet face-to-face at the point of sale. Sales can already be done without having to go to the point of sale, and the seller and the buyer do not have to meet in person. Sales systems such as utilizing internet services for buying and selling online This research was conducted at the Mass Furniture Store using a field research methodology and library research. The Mass Furniture Shop is a shop that sells teak furniture. In selling furniture, it turns out that the shop has problems providing information to the public about the activities that exist in the store. Data processing is still done manually, or, in other words, there is no special program designed to process sales data, so the preparation of sales reports often experiences delays. The Mass Furniture Store's website design for socialization media, ordering media, and online sales media is built with the PHP programming language and MySQL database, and it is expected to optimize product sales, facilitate sales transactions, and make data processing faster, more precise, and more efficient. With the design of the website as a medium for socializing, selling, and ordering goods online, it can provide convenience for users, both the general public and customers, to get to know the Mass Furniture Store more easily, closely, and without being limited by space or time.

Analisis Sentimen Aplikasi WETV di Google Play Store Menggunakan Algoritma Support Vector Machine

WeTV is an online streaming application widely used by Indonesia’s people as an entertainment medium while at home. This application has been downloaded more than 50 million times on the official Google Play Store website. The number of users who use it makes the reviews of this application abundant as well. Large numbers of reviews are very difficult to read manually, sentiment analysis is needed to classify reviews into positive and negative classes. This study uses a support vector machine algorithm with a linear kernel to classify review data from the WeTV application. KDD was used as a method to complete this research. In the analysis process to obtain information, 4 scenarios were carried out, with the division in the first scenario consisting of 60% training data and 40% test data, the second scenario consisting of 70% training data and 30% test data, the third scenario 80% training data and 20% test data, and the last scenario 90% training data and 10% test data. The highest test results of 85% were obtained from the second scenario with the distribution of training data of 70% and 30% of test data, the third with the distribution of training data of 80% and 20% of test data, and the fourth with the distribution of training data of 90% and test 10% data. The confusion matrix is used as an evaluation of the model that has been made, the results show an accuracy in the first scenario of 83%, with a precision value of 83%, recall 89%, and an f1-score of 86%. The accuracy in the second scenario is 85%, precision is 86%, recall is 89%, f1-score is 87%, accuracy in the third scenario is 85%, precision is 85%, recall is 90%, and f1-score is 88%. And the fourth scenario gets an accuracy of 85%, precision 86%, recall 90%, and f1-score 90%.

Penerapan Algoritma Apriori Untuk Rekomendasi Display Produk Mebel Furnitur

In a business , the ability to process data is very necessary, information obtained from a business can provide benefits in an effective and efficient business strategy, but with the development of online business strategy information, some users, in business furniture products are confused choosing product according to the wishes of the buyer Therefore, research is made with the aim of making it easier for users, especially in the field of furniture product business to determine the desired product by implementing a recommendation system on the furniture store website which is taken from the amount of data, this data can be in the form of databases. this is also beneficial for shop owners because with this recommendation system it can help as a means of promoting products that are not selling well. the recommendation system uses the a priori algorithm method with data mining techniques, namely association rules.

Smart Trolley System

Abstract: While shopping is really exciting and appealing, it also means growing exhausted from waiting in long lines to pay bills. Therefore, it is suggested that a smart trolley be created that can handle both shopping and invoicing. By doing this, the consumer may enter the store without stopping, load up the smart trolley with their purchases, and then leave. He receives the electronic bill in the mail and may examine the specifics of his transaction on the store's website. We need an Arduino board, an RFID reader, an RFID tag, an LCD display, an Wi-Fi module, a database manager, and a website to keep customer and product information that can be viewed from anywhere in the globe by the admin in order to do this. The trolley can communicate with the global network using this IOT-based technology.

QUESTIONING ONLINE STORE CUSTOMER LOYALTY

This research aims to investigate whether the customers repurchase at their favorite online store after browsing several web online stores and evaluating the product to be purchased (online behavior). The research uses the Smart PLS Structural Equation Model (SEM) along with descriptive analysis to test a hypothesis. This study involves 21905 internet users who browsed the online store websites. Respondents were classified according to various factors such as their age, occupation, address, and visiting frequency to the online store. The questionnaire was designed based on a 5-point Likert model. Online behavior (free shipping evaluation, discount evaluation, and read testimonies) influences repurchase and online behavior affects loyalty. This research identified several types of loyalty behavior, including deciding to buy at their favorite web store, visiting their favorite web store even though they have browsed other web shops, and believing that their favorite website provides everything they need. Repurchase behavior affects loyalty. The repurchase behavior identified repeat purchases at the favorite online store and word-of-mouth recommendations. The researchers believe that both are very decisive factors in deciding to repurchase, even though other places have more attractive promotions. The combination of online and repurchase behaviors creates a 54% R2 value. This means that 54% of online and repurchase behaviors create loyalty.

Evaluation of UAE E-Commerce Websites – MyGrocery as a Case Study

The MyGrocery Website is mainly used at the store, which is mostly random use or when the customer is at home. Understand how users can scan and know where the barcode is Make sure they are using it properly and coordinate with what is at home. Let's pretend you're stuck in the supermarket, unable to move. Check to see whether you have any tomato paste on hand. You spend the most of your time thinking about the fantastic handmade spaghetti meal you'll cook after a 12-hour workweek. To go to the grocery store, you'll have to struggle through heavy traffic and wait for 20 minutes in the corridor. If you don't have any tomato paste on hand, you'll either must pay extra money or keep it in your closet. While it is hardly a life-changing decision, we make it every time we go grocery shopping. Saving money by repurchasing items you already have might pile up quickly at the end of the month. The MyGrocery store Website eliminates the mental upheavals that must be dealt with in the five corridors. There's no need to construct a shopping list. Let's assume you go to the grocery because you need milk, bread, and wheat flakes. The supermarket website scans the barcode of your grocery shop and adds newly acquired milk, bread, and wheat to all of your kitchen's ongoing lists. Scan the barcode on your grocery receipt or use the Website to scan the barcode and record your whole purchase. After you've done eating your brown grass, you'll be ready to go on to the next step.