Reviewerly/exHarmony huggingface dataset:
Digital Skills And Digital Literacy: New Trends In Vocational Training Emotional State Of Teaching Personnel In Times Of Pandemic

Regarding academic paradigms of the teaching process, educational administration, including governance, the COVID-19 outbreak has impacted the government education institutions. Educators' conflict self-efficacy as well as job dedication are crucial for investigation in light of this approaching paradigm change. The studies demonstrated that conflict self-efficacy substantially impacted public focuses on teachers' job involvement as during COVID-19 outbreak. Educators' job dedication is positively predicted by their ability to handle ambiguity throughout this period. In addition, the information revealed a high level of conflict self-efficacy in concepts of intervention, prevention, accomplishment, and confusion governance, as well as a significant impact on work dedication among instructors of devotion to the classroom, dedication to pupils, responsibility to educators, as well as dedication to the job role. The study's outcomes also revealed a relationship between crisis self-efficacy and teachers' job dedication during the epidemic. This research establishes a theoretical foundation for a more comprehensive assessment of teacher digital competence (TDC). Furthermore, it discusses the term digital literacy and skill and how it affects teachers’ emotional state. It also states the emerging trends in the field of digital education in the time of COVID outbreak.
The Implementation Usage of Youtube Media on Listening Ability of English Students During the Covid-19 Pandemic

This research is motivated by learning English listening for students during the covid-19 pandemic which has not been carried out properly because students' understanding of listening skills is still lacking. The teaching and learning process during the pandemic is increasingly difficult for students to experience, resulting in disruption of the teaching and learning process. This also reduces the activeness of students in participating in listening learning. The learning media used are also still less effective, moreover the learning techniques used are still less varied. The purpose of this study was to determine the implementation of the use of Youtube media on the English listening skills of HKBP Nommensen Pematangsiantar University students during the covid-19 pandemic. The research method used is a quasi-experiment without a control class. The steps that will be carried out in this research are; 1) Conducting Pre Test; 2) Doing treatment using Youtube media; 3) Do a Post Test, then conclude. Learning outcomes can be seen how the differences in the increase in learning outcomes in the pretest and posttest can be seen. In the experimental class there was an increase in classical learning outcomes of 72,3287%. Conclusion from the research Overall, the implementation of the use of YouTube can be designed to be an effective learning medium for Transactional Listening tasks.
Covid-19 Pandemic and Online Fraud: Malaysian Experience

The main objective of this study is to examine how the Covid-19 outbreak has affected online fraud in Malaysia.In particular, this study aims to provide a conceptual discussion as well as a comparison analysis of online fraud patterns prior to and during the Covid-19 outbreak.This study uses police recorded online fraud data to provide comparison between pre and during the Covid-19 pandemic.This study period is 2018-2019 and 2020-2021.Results indicate that most online fraud categories increased dramatically during the Covid-19 outbreak.In particular, the number of online frauds associated with e-commerce and online investment, which are the most common online fraud categories in Malaysia, have seen the largest increasing rates between the two periods.The findings of this study provide preliminary evidences on the increasing of online fraud in the country and can motivate researcher to investigate on the factors that affect such frauds.
Ethical Theoretical Reflections on Social Media: Place of the Human Being in the Digital Space

Raises the problem of ethics in interpersonal relations on the Internet. The ontological difference between digital cyberspace from the real world is emphasized and the corresponding conceptual constructions of modern thinkers are derived. Relevant questions of modern philosophy are substantiated - whether there are some specific ethical relations in cyberspace, which arise directly on the Internet, how they are possible, and how they can be regulated. As a theoretical and methodological basis for answering these questions, presents Levinas’ ideas regarding ethical thinking and the principles of “real” meetings on the Internet: for-the-other , face-to-face , and existent-beyond-Being . In this context, Levinas’ conception of interpersonal and ethical relations in digital reality and the role of the Other in these relations are examined. The idea of the Other as a subject being outside, but for whom the user of the Internet is responsible, is disclosed. This type of responsibility, according to Levinas, is an ethical norm. The article shows the phenomenon of augmented reality as a type of hybrid reality, which is formed with the help of digital technology. Augmented reality superimposes virtual images on the real world so that both parties interact with each other. It is emphasized that in modern social science augmented reality technology is seen as blurring the boundaries of virtual and real, as well as true and false. The concepts of Bill Persky, Nicholas Negroponte, and Marc Prensky on digital communication and the impact of cyberspace on humans are considered. Particular attention is paid to the analysis of the construction of so-called primordial ethical relationships on the Internet. An important place here is occupied by D. Barney’s theory, aimed at studying the impact of the technical characteristics of network technologies on the social interaction of people. His idea of building qualitatively new interpersonal relationships in the digital environment is emphasized. The characteristic of the virtual environment as a space without response and one-way communication is noted. In this regard, the concept of N. Luhmann about the construction employing mass media of a special illusory, symbolic space, which modern man perceives as objective reality, is substantiated. The problem of obtaining truth and objective knowledge-information is derived.
Investigating Faculty Technological and Pedagogical Content Knowledge: The BiPSU Context

One of the components that shape the educational system is the instructor. They do several tasks at school that significantly impact students' character, value system, principles, and the character of the entire population. Because of the teacher's position in the classroom, the need for teacher professionalism, discipline, competence, commitment, and innovation is crucial for teachers to contribute to the country's educational aim of obtaining an exceptional education. Per the recommendations of the Accrediting Agency of Chartered Colleges and Universities in the Philippines, this study surveyed 31 faculty members in the School of Arts and Sciences department. It evaluated their competency in integrating technology into pedagogical content using Johnson's (2001) cross-sectional descriptive design. Using the updated TPACK (Technology, Pedagogical, and Content Knowledge) instrument developed by Valtonen et al. (2017), the study found that liberal arts faculty understand how various technologies can be used in the classroom. They also recognized that incorporating technology into the classroom may change their teaching. A strong relationship was found between teachers' service length, pedagogical knowledge, sex, and technological knowledge. It was suggested that school administrators prioritize program and investment strategies that develop an experienced teaching workforce of high-quality individuals. It is also advised that the faculty of the School of Arts and Sciences engage in activities that optimize Information and Communication Technology (ICT) to increase their content knowledge, professional growth, and professional learning.
IDENTIFYING ENTITY AND ATTRIBUTES USING NLP AND GENERATING ERDIAGRAM

In application development software, we need to model the data which is stored in a database. ER diagrams shows what type of data to be stored in the table or database. ER diagram can express the logical structure of the database graphically. The graphical representation of a system will be more comprehensible and easy to understand. The purpose of this paper is to identify entities and their attributes form user requirements using NLP and to combine requirement gathering technics and create tool for elicit entity and their attributes. In this study, we use NLP and its components for collecting entities and their attributes. The main aim of this paper is that to nd out entities and their attributes in order to generate diagrams such as ERDs. The purpose of this paper is to assist the business analyst and stakeholder to avoiding unnecessary work and complexity during the requirement analysis phase.
Moderating influence of parental engagement on impact of attention span on students’ academic achievement in Senior Secondary School Computer Studies

This study investigated the impacts of attention span and parental engagement on students’ academic achievement in Computer Studies. It also determined the moderating influence of parental engagement on the impact of attention span on learners’ academic achievement. A descriptive research design was adopted. The study population comprised all the SS 2 students offering Computer Studies in public senior secondary schools in Sagamu Local Government Area of Ogun State. Two hundred students were selected randomly from ten randomly selected schools. Attention Span Rating Scale (r=0.78) and Students’ Perceived Parental Engagement Questionnaire (r=0.82), and Computer Studies Achievement Test (r=0.62), were used for data collection. The data collected were analyzed using simple percentages and multiple regression at a 0.05 level of significance. The findings revealed significant impacts of attention span, F(1, 198)= 101.207, p&lt;0.05, and parental engagement, F(1, 198)= 12.346, p&lt;0.05 on students’ academic achievement in Computer Studies. The study also established the joint impact of attention span and parental engagement impacted students’ academic achievement, F(2, 197)= 59.168 p&lt;0.05, but no significant moderating influence of parental engagement on the impact of attention span on students’ academic achievement t(196) = 0.301, p&gt;0.05. It is recommended that teachers adopt active learning strategies for their students. Parents should dissuade their children from the extensive use of mobile technologies, which could dwindle their attention span.&#x0D;
Digital Currencies, Cryptocurrencies and Central Bank Digital Currencies

The history of money reveals a pattern: there has been a trend of money dematerialization over the centuries. The majority of money now circulates in electronic form. Banks, governments, and institutions are analyzing and researching the economic and technical viability of implementing digital money, as well as the implications for monetary and fiscal policy. Digital currencies are essentially e-cash that does not require any specific encryption technologies. The financial system has the potential to be transformed by digital money, and the digital money revolution will take place on a worldwide scale. Cryptocurrencies are digital currencies that encrypt and verify network transactions using cryptography. Cryptocurrencies like Bitcoin could be the future of payment systems or even how we exchange value over the Internet in the coming years. Bitcoin has the potential to be a revolution because it provides people with a new level of sovereignty and, as a result, a new form of freedom, and it represents an alternative to our current financial system. Most central banks, on the other hand, are experimenting with central bank digital currencies (CBDCs). A CBDC is a digital currency that is issued by a central bank and is widely used. Thanks to the enormous labor and attention that central banks are spending to digital currencies, they will soon become a reality. We present and discuss the characteristics of digital currencies and crypto currencies in this study, as well as the digital currencies used by central banks (CBDCs) and open issues.
OPTIMIZATION OF ACADEMIC WRITING THROUGH ZOTERO TRAINING AT THE FACULTY OF ISLAMIC ECONOMICS AND BUSINESS IAIN PALANGKA RAYA

Academic writing at the Faculty of Economics and Islamic Business IAIN Palangka Raya has not been optimal, of course, due to several factors, one of which is that there are still many lecturers who do not understand the importance of citations. teaching to students in academic writing is also weak, even citations in academic works of both lecturers and students are not open source. For this reason, the activity or solution that will be carried out is in the form of training. The method used in this training program is to use service learning so that lecturers and students are able to improve soft skills in academic writing through the zotero application, which is carried out in 3 stages, namely the preparation stage, the serving stage, and the reflection stage. In the first stage, the team coordinated on optimizing academic writing through the zotero application, designing, formulating academic writing activities through the zotero application, and the team conducting socialization of academic writing using the zotero application. The second stage, the service, is holding academic writing training through the zotero application for lecturers and students. The third stage, reflection. In this stage, the team evaluates academic writing through the zotero application. The results of the implementation of academic writing through the zotero application at FEBI IAIN Palangka Raya are considered to improve performance, quality makes it easier and supports effectiveness in producing academic works that are in accordance with national and international citations that are scientifically and academically recognized. This activity greatly affects the quality of the FEBI IAIN Palangka Raya quality which is required to be able to produce quality academic works and an effective and efficient writing process, so that the goals of the vision and mission of FEBI IAIN Palangka Raya can be achieved.
Analyzing Various Machine Learning Algorithms for Blockchain-Based Fraud Detection

A blockchain network's economics and user confidence can be seriously harmed by fraud. Consensus algorithms like proof of work and proof of stake can verify the legitimacy of a transaction but not the identity of the people who are conducting or verifying it. On a blockchain network, fraud can still occur, as a result of this. One approach to fighting fraud is to make use of machine learning techniques. There are two types of machine learning: supervised and unsupervised. We use a variety of supervised machine learning techniques in this study to distinguish between legitimate and fraudulent purchases. We also compare decision trees, Naive Bayes, logistic regression, multilayer perceptron, and other supervised machine learning techniques in detail for this challenge.
Implementasi Scrapping Data Untuk Sentiment Analysis Pengguna Dompet Digital dengan Menggunakan Algoritma Machine Learning

Analysis of social media is an effective tool for understanding people's attitudes, preferences and opinions. For a company, social media analysis can help companies to make decisions about needs, attitudes, opinions or trends about potential customers or potential customers. Hootsuite's Wearesocial research results show that out of 150 million Indonesians, 88% are actively using social media. As a result, a lot of information that was once difficult to obtain is now very easy to obtain. With so much data, data collection can be made easier by using an automated data collection system. The use of Machine Learning Algorithm as a method is used to find out how far the level of search from social media data collected is to get accurate results related to changes in behavior, lifestyle, and community activities in dealing with this pandemic. Scraping data is done using Twitter social media data with various hashtags that support opinion mining contained in the community. The results obtained are the analysis of gopay users having a positive sentiment level of 79,6%, negative sentiment of 20,4% from total of 250 data. Meanwhile, Linkaja users have a positive sentiment level of 62,1%, 37,9% negative comments from 250 data comments taken. The test results also carried out a process of calculating the level of accuracy with recall and precision, namely 87% for Gopay and 89% for LinkAja.
CONTEXT-ACTIVITY APPROACH IN THE TEACHING OF THE HIGHER TECHNICAL SCHOOL

International scientific conference "Modern scientific developments in pedagogy and psychology" : conference proceedings (November 3–4, 2022. Riga, the Republic of Latvia). Riga, Latvia : "Baltija Publishing", 2022. 204 pages.
Gesture Phase Segmentation Dataset: An Extension for Development of Gesture Analysis Models

In recent years, experts in theory of gesture have been showing some interest in automating the discovery of gesture information. Such an automation can help them in reducing the inherent subjectivity of gesture studies. Usually, to produce information for linguistic and psycholinguistic studies, the researchers analyze a video of people speaking and gesturing. This annotation task is costly and it is the goal of automation. Such videos compose the datasets that allow the development of automated models capable to carry out part of the analysis of gestures. In this paper, we present a detailed documentation about the Gesture Phase Segmentation Dataset, publicized in UCI Machine Learning Repository, and an extension of such dataset. Such dataset is especially prepared to be used in the development of models capable to carry out the segmentation of gestures in their phases. The extended dataset is composed by nine videos of three people gesturing and telling stories. The data was captured with Microsoft Kinect Sensor and they are represented by spatial coordinates and temporal information (velocity and acceleration). The data are labeled following four phase of gesture (preparation, stroke, hold and retraction) and rest positions.
Deep Anomaly Net: Detecting Moving Object Abnormal Activity Using Tensor Flow

Sparse secret writing, primarily based on abnormal detection, has shown promising performance, key features being feature learning, subtle illustrations, and vocabulary learning. propose a replacement neural network for anomaly detection called AnomalyNet by deep feature learning, sparse representation, and dictionary learning in 3 collaborative neural processing units. In particular, to obtain higher functions, form the motion fusion block in the middle of the function transfer block to enjoy the benefits of eliminating background noise, motion capture, and eliminating information deficit. In addition, to deal with some of the shortcomings (such as non-adaptive updating) of existing sparse coding optimizers and to take advantage of the advantages of neural network (such as parallel computation), design a unique continuous neural network, which will be told as a thin illustration of a docent dictionary by proposing a consistent iterative rule of hard threshold (adaptive ISTA) and the reformulation of adaptive ISTA as a substitute for long-term memory (LSTM). As far as we know, this may be one of the first works to link the `1-solvers and LSTM and offer new insights into LSTM and model-based refinement (or so-called differential programming), but primarily in the form of detection-based sparse secret writing anomaly. In-depth, experiments show the progressive performance of our technique in the task of detecting abnormal events.
Transformation Requirement Pattern for Capturing Data-Intensive Applications Requirements

A business analyst typically encounters activities and features that they have previously worked on as they move from project to project. Interestingly, despite the fact that these tasks are identical, analysts typically begin to work on them from scratch. Recreating the wheel leads to fundamental problems like neglecting the flaws in requirement analysis. Therefore, the analyst must begin implementing the strategy of requirement reuse through requirements patterns to ensure higher quality requirements with far less ambiguous parts and in a brief time. The focus of building a requirement pattern for transformation requirements of software-intensive systems ensures that critical information is not overlooked. It also enhances the effectiveness of business analysts. Although there is a plethora of research on requirements patterns in the studies, the studies did not focus on the requirement patterns for software-intensive systems. This research paper focuses mainly on the interactions of data-intensive systems namely transition requirements and a Transformation Requirement Pattern (TFReqPat) template is generated to capture the transitions requirements. It also analyses the anatomy of TFReqPat which is a guideline for capturing the data-intensive applications transition requirements. As a case study, a requirement pattern catalog with a systematic example of requirements for a banking application is presented. Furthermore, an empirical investigation was conducted to study participant’s perceptions of requirement patterns in general and in particular in order to evaluate the proposed TFReqPat. The statistical analysis reveals that the TFReqPat is more appropriate, efficient, and successful for software-intensive systems than the conventional reuse strategy.
في تعلم اللغة العربية لغير الناطقين بها في لومبوك الشرقية (Muatan Lokal) تطوير نموذج التعلم القائم على المحتوى المحلي

This article tries to find the best solution of the low reading interest of Arabic texts of students (non-native speakers) at MTs Raudhatul Azhar Masbagik Timur, which has an impact on students' ability to read Arabic texts. One of the mainly problems is that teaching materials are less relevant to the local context. Therefore, this study aims to develop a local content-based learning model that is adapted to the existing learning materials in schools. Learning materials with the theme of local content will be able to grow-up students' interest in reading Arabic texts because what is presented in the form of regional uniqueness and potential. By using the research and development method of Bord and Gall model, based on the development needs that researchers carried out, this stage was simplified into 7 stages, namely: Potential and Problems, Information Gathering, Product Design, Design Validation, Design Improvement, Product Trial, and Product Revision.&#x0D; The results of this research are in the form of teaching materials “Bacaan bahasa Arab berbasis muatan lokal untuk Madrasah Tsanawiyah kelas IX” has been validated by 2 experts, namely material experts and design experts (media). After validation, the next stage was revision based on suggestions from experts, then tested on 34 students at MTs Raudhatul Azhar Masbagik Timur with a student satisfaction test result of 83,8%. From the datas, the average pre-test is 47,79 and the post-test is 60,59. It shows that post-test biggest than pre-test. It means that there is a difference in the average student learning before and after treatment. And this study shows that the use of a local content-based learning model can improve the Arabic reading ability of class IX students of MTs Raudhatul Azhar Masbagik Timur in the 2021/2022 AD academic year.
ASPECTS OF ACTIVITIES OF TEACHERS IN THE PERIOD OF ADAPTATION OF FIRST GRADE STUDENTS TO THE CONDITIONS OF TRAINING IN THE NEW UKRAINIAN SCHOOL

International scientific conference "Modern scientific developments in pedagogy and psychology" : conference proceedings (November 3–4, 2022. Riga, the Republic of Latvia). Riga, Latvia : "Baltija Publishing", 2022. 204 pages.