Phishing is an attack by cybercriminals to obtain sensitive information such as account IDs, usernames, and passwords through the use of the anonymous structure of the Internet. Although software companies are launching new anti-phishing tools that use blacklists, heuristics, visual methods, and machine learning-based methods, these products cannot prevent all phishing attacks. This research offers an opportunity to increase accuracy in the detection of phishing sites. This study develops a model using machine learning algorithms, specifically the decision tree and the random forest, due to their outperforming the rest of the classifiers and being accredited by researchers in this field to achieve the highest accuracy. The study is based on two phases: the first phase is to measure the accuracy of classifiers on the dataset in the usual way before and after feature selection. The second phase uses the class decomposition approach and measures the accuracy of classifiers in the dataset before feature selection and after feature selection to detect phishing sites. The class decomposition approach is a technique to improve the performance of classifiers by distributing each class into clusters and renaming the examples of each cluster with a new class. This provides a specific metric that more accurately predicts the level of phishing. Testing on a dataset containing 11,055 instances, 4,898 phishing, and 6,157 legitimate, each instance has 30 features. It achieved the highest accuracy in the first phase through the random forest algorithm by 96.9% before feature selection, and after feature selection, it was by 97.1%. In the second phase, the highest accuracy of both the decision tree and random forest classifiers was achieved by 100% with the two and four classes after feature selection. While before feature selection, the random forest algorithm achieved 100% with only the two classes.

Reliable data transfer protocols are algorithmic techniques that guarantee the safe and secure transport of data through networks that could experience data loss or corruption. The performance of the systems and some accounting information systems (AIS) will be negatively impacted if the real-time data is not sent. The main factors that affect the performance of computer networks are the number of users, the hardware and software and the bandwidth. The computer network performance will play a role in the performance of the banks as it is an important component of the bank infrastructure. With the advancement of information technology, network technology, and computer technology, computers have been utilized to aid AIS operations, and AIS has become an unavoidable trend of development. Therefore, the purpose of this study was to investigate Data analysis in computer networks to improve AIS performance in Jordanian banks. A questionnaire was used to obtain the information. Jordanian banks account for the bulk of the participants in the survey. A total of 115 people took part in the study. According to the conclusions of this study, communication technology networks have a statistically significant impact on the growth of Jordanian banks' improved AIS performance.

This research involves developing a model that investigates the impact of perceived values on continuance intention to use Facebook. It also examines the impact of Facebook continuance intention on addiction and the mediating role of security concerns on the relationship between them. A structural equation modeling technique was used to analyse data obtained based on a convenience sample from 296 Facebook users in Jordan. Results showed an acceptable fit of the model. The influence of perceived values on continuance intention was confirmed based on findings. However, no similar significant effect was found for trust. A significant effect of continuance intention on Facebook addiction was found but not for security concerns. The contrasting findings represent a challenge and a possible opportunity for future research and practitioners. The research discusses different theoretical and professional contributions and outlines the implications arising from the research model.

The primary goal of this research is to examine the influence of the Internet of Things on Pharmaceutical Inventory Management in Jordan. The employees of the pharmaceutical companies in Jordan represent the population of the study. Accordingly, the study instrument was distributed to an appropriate sample of 620 employees of pharmaceutical companies in Jordan; the questionnaires used in the analysis were 432. Structural equation modeling (SEM) was used to test the study hypotheses. The study results indicated that all dimensions of the Internet of Things had an influence on inventory management. The greatest influence was for cloud computing. Based to the study findings, pharmaceutical companies in Jordan should provide high-quality Internet coverage in their offices and stores, as well as to invest in Internet of things technologies that allow the company to remotely monitor and control the physical components of the stores, attract employees with knowledge of modern Internet technologies, and provide the necessary training and development for their employees.

The primary objective of this paper is the data analysis of digital interactive art on Jordanian university students using information technology. The study also uses information technology because of the opportunities that technology provides for an interactive nature between the in-novative process, productivity, and high flexibility. The data is collected using a questionnaire, and the majority of the study population is made up of Jordanian university students. Accord-ing to the findings of this study, Digital Interactive Art has a substantial influence on Jordani-an University Students' Information Technology.

The study challenges the previous literature and assumes the digital vision as a proxy of intention among Technological, Organizational, and Environmental (TOE) factors and investigates the influence of TOE factors on cloud accounting adoption among Small and Medium Enterprises (SMEs). Furthermore, the effect of cloud accounting adoption on the organization's performance as measured by the balanced scorecard was evaluated. The data collection strategy employed an online survey of owners and managers using snowball methodology, in which the survey was automatically introduced to the respondents most likely to find relevant. The data was validated prior to SEM analysis. Seven of eight hypotheses were accepted, including the two hypotheses about the impact of the digital vision on cloud accounting adoption and the hypothesis about the impact of cloud accounting adoption on balanced scorecard-measures organizational performance. Despite the importance of the statistically significant factors in the study model, the digital vision was the most affected by the organizational readiness factor. The findings contribute to the TOE model by challenging the previous literature and assumption of digital vision as a proxy of intention among TOE factors. Future studies should use the TOE framework more caution if the intention is assumed to be a mediating variable.

The purpose of this research is to examine the effect of Web Quality (WebQual) on travelers’ online behavioral intentions through examining the mediating role of travelers’ perceived trust in the context of travel agencies in Jordan. Based on the extant literature, a conceptual model was developed. Data was collected through a questionnaire survey which was administered to a convenient sample of 300 participants. Structural equation modeling SEM with smart PLS 3 was implemented as an analytical methodology to process data. The results suggest that WebQual factors are significant in predicting travelers’ behavioral intentions. Moreover, the results demonstrate that perceived trust has a significant impact on travelers’ behavioral intentions and a partial mediation was also found for travelers’ perceived trust on the relationship between WebQual and travelers’ behavioral intentions. Discussion, conclusions, research limitations and areas for future research are all provided.

The effect of contextual factors namely information quality, service quality, system quality, Technological readiness, trust in applications (app) and COVID-19 health anxiety, on the intention and consequently the actual use of Mobile Payment (MP) app was examined in this study. Trust, as mediator to the relationship between technological readiness and intention to use MB-app was examined also. Data were obtained from 740 Jordanian Mobile Banking (MB) app users through an online survey. The relationship between service quality, system quality, information quality, trust in the app, COVID-19 health anxiety, Technological readiness and the intentions to use MB-app and the actual use of MB-app was empirically examined. The results showed a positive relationship between service quality, system quality, information quality, trust in the app and COVID-19 health anxiety, and the intentions to use MB-app, and in turn he actual use of MB-app, and a positive mediation of trust on the relationship between COVID-19 health anxiety and the intentions to use MB-app.

Once the university started using social media more, the researchers started focusing more on how social media applications were being adopted and what motivated it without being limited to classrooms only. There is a need to conduct further research about how the utilization of social media to teach in university affects education. Considering this, delving deeper into the educational outcomes and a research model related to the experiences and results of social media use is the aim of this research. Apart from that, the Technology Acceptance Model (TAM) research that deals with the behavior intention of using social networking media, perceived playfulness, perceived ease of use and perceived usefulness has been used for testing what affects the utilization of social media for online-teaching in higher education of United Arab Emirates. There was an assessment of 580 quantitative responses given by university students whose classroom sessions involved using social media. In order to predict the behavioral intention of a pupil for using social networking media for e-learning in the higher education institutions, it is possible to take some help from the factors such as perceived playful-ness, perceived ease of use and perceived usefulness, as per the partial least squares (PLS) and machine learning evaluation. The suggested model helps teachers to get to know more about how classroom sessions can become more productive through social media usage.

E-learning in knowledge management was examined in this study, specifically on how it assists organizations in improving knowledge transfer and e-learning management, to increase performance and employee knowledge management. In this study, e-learning and knowledge management systems and technology were jointly implemented, and its impact on organizational performance was examined. Organizational management was also explored. The present study investigated the relationship between knowledge management (KM) and innovation performance (IP). The mediating effect of knowledge Management was deeply explored. Randomly selected managers from 57 Jordanian manufacturing companies were the study samples, and there were 470 managers involved in this study, from strategic, tactical, and operational levels. Questionnaires were used to gather data, and the questionnaire items covered the constructs of knowledge management, organizational learning (OL), knowledge-oriented leadership (KOL) and IP. A research model was proposed and was tested using structural equation modeling (SEM). The findings were as follows: KOL positively affected KM; KOL positively affected IP; OL negatively affected IP; KOL positively affected KM; OL positively affected KM; KM positively affected IP and KM mediated the relationship between KOL, OL and IP.