Meta Tags Research Articles

INTEGRAÇÃO DA INTELIGÊNCIA ARTIFICIAL COM AS TÉCNICAS DE SEARCH ENGINE OPTIMIZATION

The internet has become an indispensable resource for accessing information. In this digital ecosystem, search engines play a crucial role in helping users find the most relevant content for their queries. This study aims to investigate how the application of Artificial Intelligence in content optimization can improve the relevance and accuracy of search results in Search Engine Optimization. Using an exploratory and descriptive methodology, the research explores the intersection between On-page and Off-page Search Engine Optimization techniques and AI, highlighting the application of Artificial Intelligence technologies such as natural language processing and machine learning. The results show that Artificial Intelligence has a significant impact on On-page Search Engine Optimization techniques, both in terms of the accuracy and relevance of search results. The research reveals that Artificial Intelligence can improve On-page Search Engine Optimization techniques, such as the optimization of Meta Tags and Title Tags, and On-page and Off-page Search Engine Optimization strategies. It is concluded that the integration of Artificial Intelligence into Search Engine Optimization strategies represents a significant evolution in digital marketing, offering more sophisticated and efficient methods for search engine optimization.

Evaluating the Websites of Academic Departments Using the GRA Method

The academic world heavily relies on search engine referrals, making SEO particularly relevant in this sector. To effectively improve page rankings, SEO encompasses two primary categories of factors: 'on-page' and 'off-page. ‘The on-page' factors are elements directly controlled on the website itself. These include strategic keyword usage, content quality, meta tags, URL structure, and internal linking. Conversely, 'off-page' factors involve external elements that influence a website's ranking. Examples include acquiring quality backlinks, maintaining a strong social media presence, and managing online reputation. To attain the maximum benefits from SEO, it is essential to consider relevant factors and criteria. Employing MCDM techniques allows website owners to evaluate and prioritize various SEO elements effectively, enabling a strategic and data-driven approach to improve their web content's search engine rankings. Today, with the advancement and widespread adoption of information systems, the quantity of websites has risen significantly. According to World Wide Web estimates based on the page index by search engines like Google and Bing, the total number of web pages has reached an impressive 4.48 billion. However, this sheer volume of websites makes it challenging for visitors to promptly find the information they are looking for. Thankfully, search engines play a crucial role in helping users access the relevant information they seek quickly and efficiently. The purpose of this study is to explore the challenges of multiple attribute decision-making when dealing with intuitionistic fuzzy information. In this scenario, the attribute weights are not entirely known, and the attribute values are represented by intuitionistic fuzzy numbers. To determine the attribute weights, an optimization model is constructed based on the traditional Grey Relational Analysis (GRA) method's fundamental principles. The proposed method involves calculating the Grey Relational degree between each alternative and the positive-ideal solution and negative-ideal solution. This degree is then used to define a relative relational degree, which enables the ranking of all alternatives simultaneously with respect to both the positive-ideal solution (PIS) and negative-ideal solution (NIS). Alternative taken as Performance criteria(C1), Design criteria (C2), Content criteria (C3), Meta tags criteria (C4), Backlink criteria (C5). Evaluation preference taken as Abdullah Gul University, Turkey (A1); Adana Science and Technology University, Turkey (A2); Aksaray University, Turkey (A3); Alanya Alaaddin Keykubat University, Turkey (A4); Anadolu University, Turkey (A5).

WCA: Integration of Natural Language Processing Methods and Machine Learning Model for Effective Analysis of Web Content to Classify Malicious Webpages

Malicious websites have become a pervasive concern in the digital realm, targeting careless users as well as organizations. It may result in substantial financial losses, identity theft, data intrusions, and damage to reputation. In order to create efficient countermeasures, it is crucial to comprehend the effects of interacting with such websites. There are several ways to classify malicious webpages. Web content analysis is one such way for protecting internet users from malicious activities. It entails analysing websites to identify potential hazards, such as phishing attempts, malware distribution, and fraudulent activities. Traditional methods relied on rule-based systems, but recent advances in natural language processing and machine learning have opened up new avenues for increasing the precision and scalability of web content analysis to classify malicious webpages. Most of the exciting research work focuses more on URL alone for risk free processing. This paper introduces novel method for analysing web contents especially textual contents of the webpages for classification. Among various tags in web technology, proposed method focuses on div, paragraph and meta tags. The textual contents of these tags are extracted and vectorized using three different vectorizers in natural language processing and classify the webpages using machine learning models. Seven different machine learning models are used for performance evaluation. The result shows that a combined textual content of three distinct tags with count vectorizer + random forest achieves the higher accuracy of 93.46% with 1000 features.

INCREASE WEBSITE VISIBILITY ON THE INTERNET BY GOOGLE SEARCH CONSOLE

The article "Increase Website Visibility On The Internet By Google Search Console" is devoted to the consideration of the importance and use of Google Search Console for website optimisation and improvement of its visibility in search engines. The article discusses the main aspects of search engine optimisation, as well as the role of Google Search Console as a powerful tool for analysing, monitoring and improving SEO strategy. The article describes methods of integrating Google Search Console with Google Analytics to obtain more detailed information about traffic, keywords, CTR and other important metrics. The article emphasises that using Google Search Console allows you to identify technical issues, analyse content, monitor website health, and perform competitive analysis to achieve better results in search results. Thanks to these insights, website owners and marketers can develop an effective strategy to increase the visibility of their site and attract a larger audience of users.
 Website indexing is an important part of the search engine optimisation process and is essential for increasing the visibility and accessibility of a website on the Internet. Indexing allows search engines such as Google, Bing, Yahoo, and others to find, analyse, and index the pages of a website. This allows search engines to include the site in their search results, which ensures its visibility to potential visitors. Indexing can help you drive more organic traffic to your website. When pages of a website are indexed, they can appear in search results when users make relevant requests. This opens up the possibility of attracting new visitors who are looking for relevant information or products and services. Indexing allows search engines to analyse website content, including keywords, meta tags, URLs, and other elements. This is important for SEO because this data affects the ranking of a website in search results. The better a website is indexed, the more chances it has to reach the top positions in search results and attract the target audience.
 During indexing, search engines can detect technical issues such as page errors, broken links, or duplicate content. This allows you to quickly identify and fix issues that could negatively affect your site's visibility and rankings. Using tools such as Google Search Console, you can track and analyse your site's indexing data. You can see which pages are being indexed, which get the most traffic, which keywords attract the attention of search engines, and much more. This information helps you understand how your site performs in search engines and how you can improve its visibility.

The Effectiveness of Search Engine Optimization Practices in Promoting Turkey's Tourism Destinations. A case Study of Tourism Destinations in Istanbul City

This study examined the effectiveness of Search Engine Optimization (SEO) practices in promoting Turkey's tourism destinations, focusing specifically on Istanbul city. Recognizing SEO as a crucial digital marketing tool, the study significantly contributed to the understanding of how SEO influences the visibility and attractiveness of destinations online. Employing a descriptive survey design, the research evaluated SEO practices on a representative sample of tourism-related websites in Istanbul, including official tourism websites, hotel sites, and travel blogs. The websites were analyzed based on established SEO parameters such as keyword usage, meta tags, backlink quality, website speed, and mobile optimization. The study also performed a comprehensive SERP (Search Engine Result Pages) analysis to gauge the visibility of these websites in organic search results. User engagement metrics such as bounce rate, time spent on the site, and conversion rates were studied to understand the effectiveness of the websites in attracting and retaining potential tourists. Furthermore, surveys were conducted with potential tourists to glean insights into their online search behavior, the perceived credibility of high-ranking websites, and their likelihood of visiting a destination based on its online representation. The findings revealed a strong correlation between effective SEO practices, high SERP rankings, and positive user engagement metrics. The study concluded that well-implemented SEO strategies significantly improved the online visibility and credibility of Istanbul's tourism destinations, thereby attracting a greater number of potential tourists. The findings underscored the necessity for local tourism businesses to invest in building SEO expertise and resources to capitalize on the potential of digital marketing in promoting tourism. Keywords: Search engine optimization, turkey's tourism, Istanbul tourism destinations, digital marketing in tourism, online visibility

Design of Enhanced Document HTML and the Reliable Electronic Document Distribution Service

Electronic documents are becoming increasingly popular in various industries and sectors as they provide greater convenience and cost-efficiency than physical documents. PDF is a widely used format for creating and sharing electronic documents, while HTML is commonly used in mobile environments as the foundation for creating web pages displayed on mobile devices, such as smartphones and tablets. HTML is becoming a more critical document format as mobile environments have been raised as the primary communication channel nowadays. However, HTML does not have the standard content integrity feature, and an electronic document based on HTML consists of a set of related files. Therefore, it has a vulnerability in terms of reliable electronic documents. We have proposed Document HTML, a single independent file with extended meta tags, to be a reliable electronic document and Chained Document, a single independent file with a blockchain network to secure content integrity and delivery assurance. In this paper, we improved the definition of Document HTML and researched certified electronic document intermediaries. Additionally, we designed and validated the electronic document distribution service using Enhanced Document HTML for real usability. Moreover, we conducted experimental verification using a tax notification electronic document, which has one of the top distribution volumes in Korea, to confirm how Document HTML provides a content integrity verification feature. Document HTML can be used in an enterprise that must send a reliable electronic document to a customer with an electronic document delivery service provider.

Penerapan Search Engine Optimazation untuk Optimasi Performa Konten Pada Website Kampus

The use of content on the campus website that is still static, using a single meta tag, and not applying meta writing techniques causes the content on the website to be not optimal and the use of meta tags, headings and subheadings in website content is not yet effective, so optimization on page optimization is still weak. Search Engine Optimization (SEO) is a way to optimize a website so that it ranks at the top of search results. On Page Optimization is a technique for optimizing content on website pages. This study applies Search Engine Optimization On Page to optimize content on the Binaniaga Indonesia University website. The results of the measurements carried out for one week obtained the final result measurement of 3.59, the average number of persession pages from 5 users, with an increase of 41.78% after implementing Search Engine Optimization. So that the developed application can be categorized into a very feasible interpretation.

Studying cognitive services for websites search engine optimization

The subject of research in the article is machine learning models for classifying web-pages by quality and compliance with SEO rules. The goal of the article is improving the efficiency of search engines by establishing and using factors that have the greatest impact on the degree of SEO optimization of web pages. The article solves the following tasks: study of the effectiveness of using machine learning methods to build a classification model that automatically classifies web pages according to the degree of adaptation to SEO optimization recommendations; assessment of the influence of relevant page factors (text on a web page, text in meta tags, links, image, HTML code) on the degree of SEO optimization using the developed classification models. The following methods are used: machine learning methods, classification methods and statistical methods. The following results were obtained: analysis of the effectiveness of the application of machine learning methods to determine the degree of adaptation of a web page to SEO recommendations was carried out; classifiers were trained on a data set of web pages randomly selected from the DMOZ catalog and rated by three independent SEO experts in the categories: “low SEO”, “medium SEO” and “high SEO”; five main classifiers were tested (decision trees, naive Bayes, logistic regression, KNN and SVM), on the basis of which it was revealed that all the studied models received greater accuracy (from 54.69% to 69.67%) than the accuracy of the baseline (48.83%); the results of the experiments confirm the hypothesis about the effectiveness of adapting web pages to SEO recommendations using classification algorithms based on machine learning. Conclusions. It was confirmed that with the help of classification algorithms built on the basis of machine learning and the knowledge of experts, it is possible to effectively adjust web pages to SEO recommendations. The considered methods can be adapted for various search engines and applicable to different languages, provided that a stamping or lemmatization algorithm has been developed for them. The results of the study can be used in the development of automated software to support the work of SEO in audit technologies to identify web pages in need of optimization and in spam detection processes.

Biomedical Scholarly Article Editing and Sharing using Holistic Semantic Uplifting Approach

Efficient practices to provide access to biomedical publications facilitate the timely transfer of information from the scientific research community to peer investigators and other healthcare practitioners. At present, the portable document format (PDF) is one of the dominating formats to share scientific knowledge offline. Additionally, some HTML-based formats have been introduced to share scientific content online. Online Search engines, e.g., GoogleScholar, require machine-interpretable metadata to correctly index items in a context-aware manner for accurate biomedical literature searches. We have developed a lightweight technical infrastructure (goSemantically) and miniaturized that as Google Docs add-ons that helps authors to add machine-interpretable metadata at the content and structural levels while authoring biomedical content. The infrastructure uses the NCBO Bioportal resources to annotate the biomedical content with appropriate semantic vocabularies. It further utilizes the Schema.org meta tags and provides an intuitive interface for users to associate the semantics tags at the document level. Additionally, our infrastructure supports users in exporting their content in various online interoperable formats preserving the embedded semantics. As a result, the biomedical metadata content would easily be indexed by search engines, making them more favorable for semantic intelligence searches.

OWGC-HMC: An Online Web Genre Classification Model Based on Hierarchical Multilabel Classification

Web genre plays an important role in focused crawling, web link analysis, and contextual advertising. In this paper, web genre is defined as the functional purpose and the information type contained in the website. The intelligent classification of web genre can predict the content and functional type of website. However, there are several critical challenges to solve the web genre classification problem: lack of web genre classification dataset and efficient web genre classification mechanism. To improve web genre classification performance, we crawled Chinese websites of different web genres and converted crawled data into a hierarchical multilabel classification dataset. A website knowledge graph is constructed based on the relationship of website and meta tag features. Using entity features extracted from the knowledge graph, we propose an online web genre classification model based on hierarchical multilabel classification (OWGC-HMC) to mine the functional purpose of the corresponding website. Experimental results show that our OWGC-HMC model can mine hierarchical multilabel structure of web genre and outperform other web genre classification methods.

Online shopping site selection attributes and meta tags: an empirical analysis

With the availability of better information technology infrastructure in India, there are many national and global online shopping sites that have started to emerge in the Indian online shopping front. India, with 400 million internet users, is the world's second largest internet market and the e-commerce market of India is projected to touch $84 billion by the year 2021. The need of the hour is to identify attributes of shopping sites that play part in shaping consumer's online platform selection intention and also to access the understanding of online shopping site about customer preferences. Prior studies have investigated factors that affect the preference of consumers towards e-retail websites but what attributes of e-retailers attract them to use such services is still an unexplored area. Meta tag analysis of the major online retailers will help in the assessment of the online retailer's knowledge of customer preferred attributes. This study will help e-retailers to understand the kind of attributes that are preferred by customers in selecting a website for online shopping and where do online retailers stand in exploiting consumer preferences in their search engine optimisation efforts.

Hierarchical Contaminated Web Page Classification Based on Meta Tag Denoising Disposal

Web page classification is critical for information retrieval. Most web page classification methods have the following two faults: (1) need to analyze based on the overall web page and (2) do not pay enough attention to the existence of noise information inside the web page, which will thus decrease the efficiency and classification performance, especially when classifying the contaminated web page. To solve these problems, this paper proposes a denoising disposal algorithm. We choose the top-down method for hierarchical classification to improve the prediction efficiency. The experimental results demonstrate that our method is about 7 times faster than the full-page method and achieves good classification results in most categories. The precision of 7 parent categories is all above 88% and is 24% higher than the other meta tag-based method on average.

Software review: The JATSdecoder package\u2014extract metadata, abstract and sectioned text from NISO-JATS coded XML documents; Insights to PubMed central\u2019s open access database

JATSdecoder is a general toolbox which facilitates text extraction and analytical tasks on NISO-JATS coded XML documents. Its function JATSdecoder() outputs metadata, the abstract, the sectioned text and reference list as easy selectable elements. One of the biggest repositories for open access full texts covering biology and the medical and health sciences is PubMed Central (PMC), with more than 3.2 million files. This report provides an overview of the PMC document collection processed with JATSdecoder(). The development of extracted tags is displayed for the full corpus over time and in greater detail for some meta tags. Possibilities and limitations for text miners working with scientific literature are outlined. The NISO-JATS-tags are used quite consistently nowadays and allow a reliable extraction of metadata and text elements. International collaborations are more present than ever. There are obvious errors in the date stamps of some documents. Only about half of all articles from 2020 contain at least one author listed with an author identification code. Since many authors share the same name, the identification of person-related content is problematic, especially for authors with Asian names. JATSdecoder() reliably extracts key metadata and text elements from NISO-JATS coded XML files. When combined with the rich, publicly available content within PMCs database, new monitoring and text mining approaches can be carried out easily. Any selection of article subsets should be carefully performed with in- and exclusion criteria on several NISO-JATS tags, as both the subject and keyword tags are used quite inconsistently.

CIVIL LIABILITY FOR MISUSE OF A TRADEMARK ON THE INTERNET

The article considers the problematic issues of civil liability for misuse of a trademark on the Internet, namely: insufficient legal regulation of civil relations in the field of trademark use on the Internet; lack of a clear mechanism for establishing the owner of a website on which a trademark is illegally used; lack of a clear mechanism for determining the amount of non-pecuniary damage caused by the improper use of a trademark on the infringer’s website; lack of a clear mechanism for determining the amount of damages and lost profits for improper use of the trademark on the infringer’s website. It is proposed to solve these problems by making changes and additions to current legislation and the adoption of new regulations, as well as by creating a Unified State Register of website owners, following the example of the WHOIS database. Variants of illegal use of the trademark in the technical part of the website, namely in the meta tags keywords, title, description, are considered. In addition, special attention is paid to the analysis of the provisions of the Association Agreement between Ukraine, on the one hand, and the European Union, the European Atomic Energy Community and their Member States, on the other, which revealed two approaches to calculating the amount of damage determining the amount of damages caused by a civil offense. Also, the analysis of the norms of the Civil Code of Ukraine, the Law of Ukraine “On protection of rights to marks for goods and services”, the Law of Ukraine “On protection of personal data”, which regulate this industry. Also, doctrinal researches of scientists concerning compensation of moral damage and losses, ways of illegal use of a trademark on the Internet are considered. Thus, within the framework of consideration of the specifics of moral damage, the subjective side is analyzed, namely the guilt of the offender. Problematic issues are considered, namely the violation of the violator’s illegal behavior and cases of creating a website on request.

Automation of Archival Documents Meta Tagging

The main goal of this project is to create a corpus of documents from the «Mikhailovsky stanichny ataman» archival fund. The methods of corpus linguistics seem to be the most optimal in this case, since they involve the processing of a large number of texts in order to solve a wide variety of linguistic problems. Our group joined the team of philologists to provide the technical and software part of the project. The main task for us is to create a document corpus engine, that is, software that solves the tasks of storing a database of marked-up texts, executing queries to this database, and also providing users with a convenient interface for work that does not require special qualifications in the field of information technology. However, it is necessary to prepare documents for inclusion in the corpus: all texts must undergo special markup. There are many types of markup, and in the previous publications [6; 9] our group has already described the solution to the problem of morphological tagging. This article is about meta tagging. Meta tagging refers to the assignment of certain descriptive attributes to text. In the case of office documents, these are such parameters as the type of document (genre), author (compiler), addressee, date and place of creation. Meta tagging is necessary for the implementation of the corpus search features, so that the researchers can receive text samples with specified external parameters: for example, texts of a certain type, created at a certain period, addressed to a certain addressee, etc. The archives of the «Mikhailovsky stanichny ataman» fund mainly contain documents from the Chanceries of the Don Army from the mid-18th to the first third of the 19th century, that’s why there are not so many varieties of these documents. Moreover, these are mostly official documents, and they were written up according to certain templates, forms, the parameters of which can be relatively easily extracted from documents through preliminary analysis. This work is also carried out by the team of philologists from VolSU under the guidance of Professor O.A. Gorban. The result of their systematization of documents was the description of special speech markers of genre parameters for all document types in the archive. Thus, in our case, there is no need for heavy methods of statistical analysis or machine learning, it is enough to search for certain markers in the document. Moreover, the main marker in all reviewed documents is a direct indication of their type. Other markers are auxiliary elements of meta tagging. The paper is devoted to the description of the created application for determining the type of a document and its meta tagging by searching the text for certain regular expressions derived from the markers.

Search engine optimization as a tool to increase the competitiveness of pharmaceutical companies in modern conditions

Search engine optimization (SEO), which is currently actively used by the majority of pharmaceutical companies all over the world, is one of the most relevant digital marketing technologies. The features of the SEO in pharmaceutical companies as one of the modern tools of digital marketing have been considered in the article.Most of the companies, which operate in the natural sciences, are several years behind in development from other industries, due to the low level of SEO strategy application. As a result, the marketing budgets of pharmaceutical companies are focused on maintaining traditional classical approaches in the field of marketing. This bias in the budget arises mainly from the underestimation of the role of the SEO strategy in the organization’s activities by the majority of pharmaceutical companies. Companies should clearly understand how significant is the impact of digitalization on their activity in modern conditions. SEO is much broader than using search queries and meta tags. Due to implementing digital tools, it is possible to create “social signals” for attracting a new target audience.It has been noted in the article that search algorithms, developed by search platforms, change very often, and it is necessary to constantly monitor and improve them. Moreover, SEO is required to help people to find the content that best matches their intended goal, rather than to misinform them by showing inappropriate pages with matched search keywords in search results.Competition among the largest companies is constantly increasing in the global pharmaceutical market, and the use of digital marketing tools, such as SEO, will allow companies to change radically the situation. As a result of the research, recommendations for the effective use of SEO as one of the digital marketing tools in the business of pharmaceutical companies have been proposed. Finally, the conclusions about the increasing the role of digital marketing in modern conditions have been made.

ON THE USEFULNESS OF HTML META ELEMENTS FOR WEB RETRIEVAL

Web retrieval studies have mostly used URL, title, body, and anchor text fields to represent Web documents. On the other hand, HTML standards provide a rich set of elements to define different parts of a Web page. For example, meta elements are used to provide structured metadata about a Web page not to end users, but instead to browsers or crawlers. However, it is unclear whether meta tags are or are not useful for Web retrieval, as most of the previous studies leveraged URL, title, body, and anchor text fields. In this work, we examine the usefulness of two meta tags, namely keywords and description, based on ad-hoc tasks of previous TREC studies. Through experiments on the standard TREC Web datasets and several query sets, our results using the state-of-the-art term-weighting models show that the utilization of description field systematically increases the retrieval effectiveness, to a statistically significant degree most of the time. By contrast, the employment of keywords field may cause a significant deterioration in retrieval effectiveness for certain term-weighting models.

Contextual weighting approach to compute term weight in layered vector space model

The World Wide Web (WWW) is the largest available repository of information. This huge amount of information put forward the challenges of retrieval of trustworthy information from WWW. It defies researchers with new issues of diversity and complexity while retrieving the web information. Information retrieval from the web demands approaches that span beyond conventional information retrieval. Heterogeneity, complexity and the huge volume of web information requires a unique approach to retrieve information. Besides, end-users introduce some difficulties in the retrieval process. Sometimes queries submitted by the user are subtle and ambiguous. The primary concern in information retrieval is the issue of predicting the relevance of documents. In this article, a new approach is proposed that rationally separates web document into five layers, namely, title, header, hyperlink, meta tag and body layer. The proposed method effectively combines the textual information and structural evidence of web document for retrieving information from Web. In the proposed layered vector space model, each layer has an allocated priority which is used to compute weight factor for these layers. The proposed method deduces equation that effectively combines priority of the layer and length of the layer to calculate the weight of the layer.

Web Page Classification Using RNN

Web page classification is an information retrieval application that provides useful information that can be a basis for many different application domains. In this study, a deep learning-based system has been developed for the classification of web pages. The meta tag information contained in the web page is used to classify a web page. The meta tags used are title, description and keywords. RNN based deep learning architecture was used during the tests. Transfer learning is the name given to the approach to building a machine learning model with the use of pre-trained parameters to solve a problem. The effect of using transfer learning on the system has also been examined. According to the results obtained, success rate of web page classification system is approximately 85%. It is not observed that transfer learning has significant contribution to the success rates. However, the use of transfer learning has reduced the consumed system resources.

PELUANG BISNIS ONLINE SITUS VOUCHER DISKON

<p align="center"><strong>ABSTRACT</strong><strong> </strong><strong></strong></p><p><em>Discount voucher / voucher sites are one part of e-commerce. Rampant discount sites in Indonesia, a separate phenomenon, especially in terms of the development of Internet-based commerce (e-commerce). Discount voucher sites are sites or mobile apps that market advertisements about promos and discounts being held by companies into the world of the internet so that the spread becomes more widespread. With a discount voucher site, companies can advertise their promotions and discounts to the internet. The methodology of data collection is done by observation, namely: direct observation on various voucher and discount voucher sites in Indonesia and with Library Studies, reading books, articles and sites that can assist in the analysis. For marketing strategy done with Organic Marketing, that is by using SEO (Search Engine Optimization) Hash Tags, Meta Tags, Achor Links that must be applied into the website, outside of the side of the website, organic marketing can also be done by way of broadcasting and social media press. For offline marketing channels, discount voucher sites can be made by distributing flyers to public places, such as malls, to inform the public that there is a discount voucher Site presence that they can download using a smartphone. Business analysis is carried out by assessing business feasibility studies in terms of financial aspects. Based on the calculation of investment feasibility study, by using the method of payback period, net present value, internal rate of return, and profability index, it can be concluded that discount voucher sites deserve to be a business opportunity.</em><em></em></p><p><em> </em></p><p><strong><em>Keywords</em></strong><strong><em> : E-commerce, Discount Vouchers, Investment Feasibility Study</em></strong><em></em></p>