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Data Analytics Application in Fashion Retail SMEs (A Case Study in Caracas Fashion Store) Surabani, Santorini; Rodriguez, Bradlow
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (812.071 KB) | DOI: 10.58776/ijitcsa.v1i1.17

Abstract

Data analytics plays a paramount role in maximizing productivity and profitability for businesses by deriving insights from pre-existing data to predict market trends and client habits to make better business decisions. In accordance with Industrial Revolution 4.0, most SMEs have begun to implement an e-commerce business model, thus, customer data is generated at an exponential rate, allowing SMEs to further develop their services for greater user satisfaction. However, the abundance of unsorted and ambiguous data leads to issues such as server overload and inefficient customer sales cycle tracking. This paper will explain the application of data analytics techniques and architectures to overcome these issues in a fashion retail SME, as well as the benefits and drawbacks of these solutions.
Enhancing Online Food Delivery Systems through Comprehensive Text Analytics and Strategic Data Integration Surabani, Santorini
International Journal of Information Technology and Computer Science Applications Vol. 2 No. 1 (2024): January - April 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v2i1.121

Abstract

Addressing challenges in the online food delivery system involves employing various data analytics techniques. Text Analytics, encompassing web analytics, social media analytics, stream analytics, and geospatial analytics, plays a pivotal role in managing and extracting valuable insights. The use of third-party systems by many companies to meet the demand for online food delivery presents issues related to control. Furthermore, information overload and poorly organized data contribute to observed problems. This research proposes effective data integration as a solution, facilitating strategic analytics for optimal system performance. Proper data sorting enables adaptive planning and priority shifts tailored to customer satisfaction. The framework of data integration is crucial in illustrating the comprehensive analysis of online food delivery systems. The report also delves into the challenges associated with implementing text analytics.
Harnessing Text and Web Analytics to Enhance Decision-Making in Job Opportunity Categorization Surabani, Santorini
International Journal of Information Technology and Computer Science Applications Vol. 2 No. 2 (2024): May - August 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v2i2.145

Abstract

Text analytics is defined as a method of analyzing compilations of structured text such as dates, times, locations, semi structured text, such as HTML and JSON as well as unstructured text, such as word documents, videos, and images, to extract and discover trends and relationships without requiring the exact words or terms to convey those concepts. Web analytics on the other hand is the technology that collects, measures, analyses, and provides reports of data on how users use websites and web applications. It is used to track a number of aspects of direct user-website interactions, such as the number of visits, time spent on the site, and click pathway. It also aids in the identification of user interest areas and the enhancement of web application features. We used clustering techniques to categorize the job opportunities that are available for the job seekers. By implementing text analytics, text data may be grouped with the goal of providing outcomes in the form of word frequency distribution, pattern identification, and predictive analytics. Text analytics may create one-of-a-kind values to use in the improvement of decision-making and business processes, as well as the development of new business models.