Application creation of Petch Nam Sap community enterprise management system Phetchaburi to create application for Petch Nam Sap community enterprise management system To assess satisfaction with community enterprise management system applications using PHP5 HTML5 CSS3 phpMyAdmin to design databases and image editors as a tool for system development and use questionnaires to assess satisfaction with applications. The samples used in the experiment were Ban Nam Sap community. The application created makes the operation more convenient. Data is stored and managed within community enterprises. Statistics using average percentage research results showed that Petch Nam Sap community enterprise management system application Phetchaburi province generated an average efficiency of 4.64 at the highest level. It helps to manage the information of community enterprises. Evaluation of satisfaction with Petch Nam Sap community enterprise management system application. The average deviation of 0.49 is the highest. It shows that the Application for Petch Nam Sap Community Enterprise Management System It can be used in Phetchaburi.

The purposes of the research were to study 1) entrepreneurial intention of students of Rajamangala University of Technology Phra Nakorn; 2) entrepreneurial characteristics of students of Rajamangala University of Technology Phra Nakorn and 3) predicting power of the students’ entrepreneurial characteristics on their entrepreneurial intention. The population were 375 third- and fourth-year students in every faculty enrolling in the academic year 2020. The research tool was questionnaires. The statistical data analysis was performed by frequency percentage mean and standard deviation. T-test One-way ANOVA Pearson Correlation Coefficient and Multiple Regression Analysis were used to examine hypothesis. The finding of the study: 1) Most of the students taking the questionnaires are female (62.40%) aged 21 years (43.70%) half of them are in the third-year (54.90%) and in the faculty of Business Administration (33.10%). Most of students’ fathers (38.70%) and mothers (45.10%) are business owners. 2) According to the students’ entrepreneurial intention it was at a moderate level (x̄= 3.95 S.D = 0.617). The highest mean score is a great willing for entrepreneurial intention after graduation (x̄ = 4.13 S.D = 0.901).The lowest mean score is no willing for entrepreneurial intention after graduation (x̄ = 3.43 S.D = 1.001). Reasons for entrepreneurial intention are to have their own businesses /or to be independent (81.65%). As for types of businesses they intend to become entrepreneurs of food/ restaurant/ cafeteria/ bakery shop (72.10%). 3) Due to the students’ entrepreneurial characteristics it was at a moderate level (x̄= 4.13 S.D =0.482). The highest mean score is Need for Achievement (x̄ = 4.22 S.D = 0.597). The lowest mean score is Risk Taking (x̄ = 4.02 S.D = 0.597). 4) There were significant differences in entrepreneurial characteristics of students’ sex age learning program fathers’ occupations mothers’ occupations and families’ income at 0.05 while there was no significant differences in entrepreneurial characteristics of students’ college years. 5) Predicting power of the students’ entrepreneurial characteristics on their entrepreneurial intention was .660. Three types of the students’ entrepreneurial characteristic factors on entrepreneurial intention were Autonomy Innovativeness and Risk taking.

The objective of this research was to study information behavior in digital environment of students from Rajamangala University of Technology Phra Nakhon. The sample was 387 undergraduate students from Rajamangala University of Technology Phra Nakhon in the academic year 2019. The research tool was a questionnaire. The results of the research were that the students aimed to find supplementary information for extra work do report and research or project respectively. Students had the process of searching for information in the following order : specify the topic; select or organize the information; survey information and resources; search information link and follow up with new information. Most information behavior of students was searching from the websites such as Google Yahoo and using link points on search engines like Google Yahoo etc. Method for assessing information that students used the most was complete content and reliable information. Method for keeping track of information that students used the most was from social media such as Weblog Facebook YouTube. The information format that students used the most were pictures. And the action after obtaining the information that students used the most was validation and completeness of the content.

The study entitled “Education 4.0: An Evaluation of Students’ Attitudes towards Using Mobile Applications for English Language Learning” a mixed-method research aims to find out what are the students’ attitudes towards the use of mobile assisted in language learning what factors result in the acceptance and the use of mobile applications for English language learning and what are the application features responding to the students’ needs. The participants in this study were selected based on the convenience sampling method. They were undergraduate students studying at the tertiary level from the first-year to the fourth-year in the Faculty of Liberal Arts Rajamangala University of Technology Phra Nakhon in the academic year of 2020. The total number of participants was 131 university students. The research instruments used for data collection was questionnaire which can be divided into four parts as follows: Part 1 general information Part 2 mobile applications used for English language learning Part 3 factors affecting the acceptance and the use of mobile applications for English language learning and Part 4 open-ended questions for additional information and suggestions so as to develop the features of mobile assisted in English language learning responding to the students’ needs. The data obtained from the questionnaire were divided into two types. The quantitative data such as the scores from 4-point Likert scale were analyzed by using descriptive statistics for example frequency percentage mean and standard deviation. In addition to the qualitative data the students’ written opinions were analyzed by using textual analysis word clouds and sentiment analysis of users’ attitudes towards the use of mobile applications for English language learning. Most participants in this study were female university students whose age ranged from 18 to 22 years old. These participants filled in the four rating scale questionnaire: 4 strongly agree 3 agree 2 disagree and 1 strongly disagree to report their attitudes towards the use of mobile applications for English language learning. The results of the study showed that most participants frequently used Youtube and Facebook to develop their vocabulary. The individual factors such as gender age and English language proficiency were not correlated with the acceptance and the use of mobile application for English language learning. The participants also reported that they strongly agreed on the performance expectancy and the perceived usefulness with a low to moderate correlation in each factor. According to the descriptive analysis and textual analysis the results reported that these university students showed positive attitudes towards the use of mobile applications for English language learning because it was easy fast and could access information quickly. One possible explanation for this was their age group. These participants were the members of generation Z who were born with innate digital literacy and the advancement of technology. They were also familiar with social media. However one of the limitations in the study was data analysis since the results of sentimental analysis and textual analysis might be influenced by word segmentation approach. For the content of English the differences between general English and English for Specific Purposes did not result in any decisions on using the mobile application for English language learning.

Nowadays artificial intelligence is being used in a growing variety of applications. Whether in public health the areas of cybersecurity agriculture finance and many others have resulted in the countrys rapid development. In spite of the leap in progress but the problem of thefts increased steadily. According to the statistics collection in 2011 there were 152228 crimes and 92.5% of the property incidents occurred. The injured person will know the cause later and tracking the villain quite difficult development of home intrusion detection devices with Line notifications as a way to proactively alert when such an event occurs. Based on the principle of artificial intelligence to help it.