Biblio

A good website quality is needed to meet user satisfaction. The value of the benefits of the web will be felt by many users if the web has very good quality. The ease of accessing the website is a reflection of the good quality of the website. The positive image of the web owner can be seen from the quality of the website. When doing research on the website of the Ministry of Agriculture, Directorate General of Food Crops, the researcher found several pages that did not meet the website category which were said to be of good quality. Based on these findings, the authors are interested in analyzing user satisfaction with the website to measure the quality of the website of the Ministry of Agriculture, Directorate General of Food Crops using the PIECES method (Performance, Information, Economy, Control/Security, Efficiency, Service). The results of the study indicate that the level of user satisfaction with the website has been indicated as SATISFIED on each indicator, however, in measuring the quality of the website using YSlow (the GTMetrix tools, Pingdom Website Speed Tools), and (Web of Trust) WOT found many deficiencies such as loading the website takes a long time, there are some pages that cannot be found (page not found) and so on. Therefore, the authors provide several recommendations for better website development.

In this study, we conducted a survey of those who have used E-Government Services (civil servants, employees of public institutions, and the public) to empirically identify the factors affecting the continuous use intention E-Government Services, and conducted an empirical analysis using SPSS and Smart PLS with 284 valid samples except for dual, error and poor answers. Based on the success model of the information system (IS access model), we set independent variables which were divided into quality factors (service quality, system quality, information quality) and risk factors (personal information and security), and perceived ease of use and reliability, which are the main variables based on the technology acceptance model (TAM) that best describes the parameter group, were established as useful parameters. In addition, we design the research model by setting user satisfaction and the continuous use intention as dependent variables, conducted the study about how affecting factors influence to the acceptance factors through 14 hypotheses.The study found that 12 from 14 hypotheses were adopted and 2 were rejected. Looking at the results derived, it was analyzed that, firstly, 3 quality factors all affect perceived ease of use in relation to the quality of service, system quality, information quality which are perceived ease of use of E-Government Services. Second, in relation to the quality of service quality, system quality, information quality and perceived usefulness which are the quality factors of E-Government Services, the quality of service and information quality affect perceived usefulness, but system quality does not affect perceived usefulness. Third, it was analyzed that both factors influence reliability in the relationship between Privacy and security and trust which are risk factors. Fourth, the relationship between perceived ease of use and perceived usefulness has shown that perceived ease of use does not affect perceived usefulness. Finally, the relationship between user value factors (perceptual usability, perceived usefulness and trust) and user satisfaction and the continuous use intention was analyzed that user value factors affect user satisfaction while user satisfaction affects the continuous use intention. This study can be meaningful in that it theoretically presented the factors influencing the continued acceptance of e-government services through precedent research, presented the variables and measurement items verified through the empirical analysis process, and verified the causal relationship between the variables. The e-government service can contribute to the implementation of e-government in line with the era of the 4th Industrial Revolution by using it as a reference to the establishment of policies to improve the quality of people's lives and provide convenient services to the people.

Mobile cloud computing has the features of resource constraints, openness, and uncertainty which leads to the high uncertainty on its quality of service (QoS) provision and serious security risks. Therefore, when faced with complex service requirements, an efficient and reliable service composition approach is extremely important. In addition, preference learning is also a key factor to improve user experiences. In order to address them, this paper introduces a three-layered trust-enabled service composition model for the mobile cloud computing systems. Based on the fuzzy comprehensive evaluation method, we design a novel and integrated trust management model. Service brokers are equipped with a learning module enabling them to better analyze customers' service preferences, especially in cases when the details of a service request are not totally disclosed. Because traditional methods cannot totally reflect the autonomous collaboration between the mobile cloud entities, a prototype system based on the multi-agent platform JADE is implemented to evaluate the efficiency of the proposed strategies. The experimental results show that our approach improves the transaction success rate and user satisfaction.

Voice-controlled intelligent personal assistants, such as Cortana, Google Now, Siri and Alexa, are increasingly becoming a part of users' daily lives, especially on mobile devices. They introduce a significant change in information access, not only by introducing voice control and touch gestures but also by enabling dialogues where the context is preserved. This raises the need for evaluation of their effectiveness in assisting users with their tasks. However, in order to understand which type of user interactions reflect different degrees of user satisfaction we need explicit judgements. In this paper, we describe a user study that was designed to measure user satisfaction over a range of typical scenarios of use: controlling a device, web search, and structured search dialogue. Using this data, we study how user satisfaction varied with different usage scenarios and what signals can be used for modeling satisfaction in the different scenarios. We find that the notion of satisfaction varies across different scenarios, and show that, in some scenarios (e.g. making a phone call), task completion is very important while for others (e.g. planning a night out), the amount of effort spent is key. We also study how the nature and complexity of the task at hand affects user satisfaction, and find that preserving the conversation context is essential and that overall task-level satisfaction cannot be reduced to query-level satisfaction alone. Finally, we shed light on the relative effectiveness and usefulness of voice-controlled intelligent agents, explaining their increasing popularity and uptake relative to the traditional query-response interaction.