Construction of e-commerce system based on 5G and Internet of Things technology

In order to improve the comprehensive performance of the e-commerce system, this paper combines 5G communication technology and the Internet of Things technology to improve the e-commerce system, and conduct end-point analysis on the e-commerce client data analysis system and smart logistics system. Moreover, this paper uses 5G technology to improve machine learning algorithms to process e-commerce back-end data and improve the efficiency of e-commerce client data processing. In addition, this paper combines the Internet of Things to build an e-commerce smart logistics system model to improve the overall efficiency of the logistics system. Finally, this paper combines the demand analysis to construct the functional module structure of the e-commerce system, and verifies the practical functions of the system through experimental research. From the experimental research results, it can be seen that the e-commerce system based on 5G communication technology and Internet of Things technology constructed in this paper is very reliable.

Peningkatan Akses Penyimpanan Data Client Menggunakan Website Pada Inside Lombok

The service on improving access to client data storage using the website at Inside Lombok is carried out so that data storage can be carried out effectively and efficiently. With this web, it is hoped that it will make it easier for Lombok insiders to enter and access client data wherever they are. The purpose of this activity is the development of a client database information system in Inside Lombok so that it can be accessed easily and can be done anywhere. The types of this activity are manufacture and training. This activity was carried out for 20 days with Inside Lombok employee participants. The evaluation carried out is divided into two. The first evaluation of the website creation that has been developed consists of a functional test and a satisfaction test, the second is an evaluation of satisfaction regarding the use of the web that has been used. The result of this activity is that the team has succeeded in creating a website to store client data so that Inside Lombok employees do not need to use excel anymore, which is where this website can save time for employees who want to enter client data because the format for entering data already exists and can be accessed anywhere.

Getting Your Data Into SSDforR

This chapter covers how to measure target behaviors and use common software to record and edit client data. Readers are then shown how to import data into R and use the SSD for R functions to analyze their data. The first part of this chapter focuses on the type of data that is most appropriate to record and some common issues related to collecting these. Four different types of measurement are covered, each of which has its own strengths and weaknesses. These include direct behavioral observations, standardized scales, individual rating scales, and logs. When selecting one or more methods of measuring a target behavior, readers will want to consider the specific needs of their clients, the identified problem, and the practice or research situation. The second part of this chapter demonstrates how to use Excel or other spreadsheet programs to quickly and effectively record this data.

A SURVEY OF E-COMMERCE SECURITY THREATS AND SOLUTIONS

E-commerce security is part of the Web security problems that arise in all business information systems that operate over the Internet. However, in e-commerce security, the dimensions of web security – secrecy, integrity, and availability-are focused on protecting the consumer’s and e-store site’s assets from unauthorized access, use, alteration, or destruction. The paper presents an overview of the recent security issues in e-commerce applications and the usual points the attacker can target, such as the client (data, session, identity); the client computer; the network connection between the client and the webserver; the web server; third party software vendors. Discussed are effective approaches and tools used to address different e-commerce security threats. Special attention is paid to Cross-Site Scripting (XSS), Cross-Site Request Forgery (CSRF), phishing attacks, SQL injection, Man-in-the-middle, bots, denial-of-service, encryption, firewalls, SSL digital signatures, security certificates, PCI compliance. The research outlines and suggests many security solutions and best practices.

Understanding the Profile and Needs of Abused Men: Exploring Call Data From a Male Domestic Violence Charity in the United Kingdom

Current understandings on service engagement by male victims of domestic violence and abuse (DVA) within the United Kingdom (UK) have generally been captured by qualitative research. As such, large-scale quantitative data detailing the profile, needs and outcomes of abused men, upon both presentation and use of services, is currently lacking. The present study analyzed the client data of 719 callers to a domestic abuse helpline for men in the UK. Findings showed that the overwhelming majority of callers reported they were abused by female perpetrators, most of whom were still their current partner, and that many of the men were fathers. Vulnerable populations (GBTQ+ and disabled men) were under-represented in the sample. Most men were seeking emotional support, along with a range of practical advice and signposting to other services. The confidentiality of the helpline was crucial for many men, and almost half had struggled to access the service (suggesting a severe lack of resourcing). Findings are discussed in relation to the need for gender-inclusive services, which cater for the unique challenges and barriers experienced by abused men.

Customer Behavior Analysis using Machine Learning

RFM (Recency, Frequency, Monetary) investigation is a demonstrated showcasing model for conduct based client division. It groups clients dependent on their exchange history – how as of late, how frequently and what amount they buy.RFM helps partition clients into different classes or groups to distinguish clients who will react to advancements and how. This RFM examination depends on a blend of three boundaries. For instance, we can say that individuals who spend the most on items are our best clients. A large portion of us coincide and think about something very similar. In any case, Imagine a scenario in which they were bought just a single time. Or on the other hand an extremely quiet past? Consider the possibility that they are done utilizing our item. would they be able to in any case be viewed as your best clients? Most likely not. Making a decision about client esteem from only one perspective will give you a mistaken report of your client base and their lifetime. That is the reason, the RFM model joins three diverse clients ascribed to rank clients. In the event that they purchased in the recent past, they get higher focus. On the off chance that they purchase ordinarily, they get a higher score. What's more, on the off chance that they spend greater, they get more focus. Thus, we Combine these three scores to make the RFM score. At long last we can portion the client data set into various gatherings dependent on this RFM score.

Allied Systems: Data governance challenges and the opioid crisis

This teaching case based on real people and events describe a critical decision point during the nascent stage of entrepreneurial venture called Allied Systems Integration Solutions in May 2019. This data governance case explores the challenges with centralizing client data in an effort to help health practitioners cope with the opioid use crisis. Readers are asked to put themselves into the shoes of the protagonists who must make difficult operational decisions related to these data governance and behaviour management questions. This case is derived from participant observation of eight entrepreneurial mentoring sessions with the protagonist entrepreneurs. Detailed notes of participant observation sessions were maintained and qualitative data were analysed for the purpose of creating this business case. This case is intended for upper year undergraduate, or MBA courses. In particular, it should be used in curricula exploring the complexities of real-world data governance decisions, managing the trade-offs between operational efficiencies and data protection. This case would be most suited to courses in Management Information Systems, Database Management and Operations Management.