Reviewerly/exHarmony huggingface dataset:
Literasi Digital Bijak Bermedia Sosial Di Desa Kaliangkrik

Wise literacy in social media is a critical aspect in dealing with the complexity of online interactions in the digital era. A deep understanding of social media-platform use and the ability to critically evaluate information is at the core of this literacy. Individuals who have wise social media literacy can filter out inaccurate information, understand the social, cultural and political impacts of the content they consume or share. The importance of wise social media literacy also involves responding to disinformation, where individuals can effectively avoid the spread of fake or manipulative news. Ethical aspects of communication are also a focus, with this literacy teaching individuals to promote healthy dialogue and respect diversity of opinion, forming a more positive and inclusive online environment. This research aims to find out how the pattern of community service is a manifestation of the tridharma of higher education related to aspects of community service. In implementing the community service program that has been prepared previously, the method used is increasing knowledge by means of counseling or socialization with the aim of providing understanding and wise skills in digital literacy from the extension team. Apart from that, wise social media literacy also considers online security and privacy risks. Users need to be able to manage and protect their personal information, avoid threats such as fraud, and carefully guard their digital identity. This is not only an individual skill, but also a contribution to the sustainability and security of the global digital environment. By mastering social media literacy, individuals can better navigate the complexities of social media, participate positively, and make informed and wise decisions in using these platforms. Overall, smart social media literacy is an important foundation for forming individuals who are able to interact wisely in an ever-growing digital world. By combining an understanding of content, communication skills, and awareness of security risks, wise social media literacy helps shape an intelligent, ethical, and empowered online society.
Understanding Analytical Exposition Text Writing with an SFL Approach

This research aims to explore the ability of eleventh-grade students to create analytical exposition texts based on their generic structure and language features, using a descriptive qualitative research approach. The study focuses on comparing model texts with students' writing to describe the types of Systemic Functional Linguistics (SFL) approaches employed and analyze the transitivity in writing analytical exposition. The participants of this study are eleventh-grade students selected based on a teacher's recommendation. The researcher reports the natural phenomena without applying any treatments that could influence the results. The primary objective is to understand the student’s ability to produce analytical exposition texts without intervention. The data collection involves analyzing sentences in the form of students' analytical exposition text assignments provided by the teacher. The researcher examines the clarity of ideas and evaluates the grammatical and generic structure present in the students' writing. This research utilizes a descriptive qualitative approach to capture and describe the natural phenomenon of students' analytical exposition text writing. The findings contribute to understanding the students' proficiency in creating analytical exposition student texts, as well as identifying areas that require further attention in instructional practices.
Code Smell Detection and Software Refactoring Research: A Systematic Literature Review

Today we are experiencing rapid enhancements in software systems and their development. The software industry's demand for tools and techniques for software development, especially automatic and less time-consuming, is increasing daily. Software refactoring and code smell detection are now expanded from code-level changes to the architecture, model, and requirements restructuring. We are moving from an object-oriented paradigm towards cloud computing, web development and mobile application development and so much more. Therefore, code smell and refactoring techniques are talk of the town in various research communities in their objectives. In this paper we will study the existing tools and techniques, research progress by doing a systematic literature review in the field of code smell detection and software refactoring’s. We will also classify the existing research techniques, identify the trends in code smell detection and refactoring and try to highlight the gaps in the area for researchers.
Comunidades criativas na Covid-19: Um olhar para a tecnologia como meio de articulação de soluções habilitantes

This article reflects on the importance of design today, especially with regard to social aspects.In view of this, emphasis is placed on the impact of technological transformations -through Web 2.0 -as a mobilizer of economic, political and social transformations, enabling both positive and negative effects.Evidencing the beneficial aspects of the online universe, it is observed that technological advances can help in the development of creative solutions and drivers of change, even more so in crisis contexts.Taking these factors into account, it was decided to study the period of the Covid-19 pandemic, which was one of the main health crises of the century, and it was possible to conclude that online platforms were a motivating means in the maintenance and development of Creative Communities that sought innovative solutions to problems faced at that time.
Efektivitas Model Pembelajaran Quantum Teaching Terhadap Keterampilan Menulis Cerita Dongeng Siswa Kelas III SDN Kecil To’pae Kabupaten Enrekang

This research aims to determine the effectiveness of using the Quantum Teaching model on the fairy tale writing skills of class III students at SDN Kecil Topae, Enrekang Regency. This research is pre-experimental researchin the form of One Group Pretest-Posttest research. The population of this research is class III students at SDN Kecil To’pae in Enrekang Regency which consists of one class, namely 9 students. The research instrument used was a fairy tale writing test. The data obtained was then analyzed using descriptive statistical data analysis and inferential statistical data analysis. The result of this research show that the pretest result show that the average student learning score is 58,3 with categories, very high 0%, high 33,33%, medium 33,33%, low 33,33% and very low 0%. And the average score for posttest learning outcomes after using Quantum Teaching is 84,44 with categories very high 66,66%, high 33,33%, medium 0%, low 0%, very low 0%. These variations show that there is a significant influence of using the effectiveness Quantum Teaching learning model on fairy tale writing skills. Based on the description above, it can be concluded that the Quantum Teaching learning model is effectively used in learning to write fairy tales in class III students at SDN Kecil To’pae, Enrekang Regency.
Sistem Informasi Akuntansi Penjualan Tunai Dan Penerimaan Kas Berbasis Multiuser Pada Toko Harnova Tanggungharjo

In the modern and instant era of globalization, companies are required to be able to compete in improving performance and be able to produce appropriate reports. In a trading company, sales are the main activity to generate profit. Good sales and recording procedures and in accordance with company needs can be carried out with a sales accounting system. Sales themselves are divided into two, namely cash sales and credit sales. In this study, the intended sales accounting system is the cash sales accounting system.This research was conducted at the Harnova Tanggungharjo Store, where the Harnova Store is a company engaged in the sale of clothes. Cash sales and cash receipts are very important in an agency, because cash is an important asset. In recording sales and cash receipts, this agency still uses manuals. A computer is a tool that can store data, process data and provide useful information for companies to advance their companies.This study designs a system that can help companies calculate sales and cash receipts. With the cash sales information system and cash receipts, it is expected to be able to carry out procurement, planning and sales supervision very well. besides that it can also produce reports that are precise, accurate and efficient. The software that I use is Microsoft Visual Basic 6.0 with SQL Server 2000 database
Web-Based Tourism And Culture Information System Using Google Api At The Blora Regency Tourism And Culture Office

With the increasingly rapid development of computer technology, internet media is a very effective means of conveying information. Through the internet, various kinds of information from various fields can be obtained quickly. The internet has become an important part as a forum or promotional medium. With the advantages of the internet, the author tries to provide information about the existence of tourism and culture in Blora so that the people of Blora city in particular and people outside the city of Blora in general know it easily and save time. The design of this system was made through several stages. The supporting software used is Apache, Macromedia Dreamweaver MX and PHP as server side-scripting and the final result of this research is a website that provides information about Tourism and Culture of Blora Regency.
ANALYSIS OF THE INFLUENCE OF PSYCHOSOCIAL FACTORS ON JOB SATISFACTION OF TEACHERS

Labor protection and health of people is a state task, therefore, in accordance with Russian legislation, everyone has the right to work in conditions that meet safety and hygiene requirements. The Constitution of the Russian Federation guarantees not only care for the life and health of workers, but also establishes the right to time intended for rest. The dynamic pace of modern life dictates its own conditions and requires high levels of mental and physical strength from people in different professions. In our opinion, pedagogical activity is especially filled with tense situations. In particular, the work of educators, which is associated with daily communication with children, their parents, work colleagues and management. A wide range of communication, relationships in a team, a variety of tasks and the intensity of work have a significant impact on the emotional state of teachers. Constant stress at work can lead to depression, poor health, low satisfaction with the profession and a formal attitude towards work, which is unacceptable when working with children. The purpose of the work is to analyze the psychosocial risks of preschool education that influence job satisfaction.
The landscape of cyber security education and training programmes: The case of France

This chapter delves into the provision of cyber security education and training programmes in France. It focuses on examining the characteristics of the education and training programmes that lead to entry-level jobs in the cyber security field. Particular attention is given to strategies and initiatives aimed at diversifying enrolment, especially in bringing more females into cyber security field. The chapter also highlights efforts to increase employers' involvement in the design and delivery of cyber security learning opportunities, and to give visibility to cyber security in education and training programmes.
Optimizing Treatment of Herbal Plant Using SOPHERBAL Android Application Fordward Chaining Method

The utilization of traditional herbal medicine among the inhabitants of Lombok is notably prevalent yet frequently hindered by a lack of comprehension regarding the efficacy of herbal remedies for specific ailments. Addressing this challenge, this study proposes the development of an Android application called ”sopherbal,” aimed at delivering personalized herbal plant recommendations via easily accessible mobile devices. Employing forward chaining methodology, the application identifies optimal herbal remedies based on ailment type, processing techniques, usage instructions, and recommended dosage and treatment duration. Notably, while effective in this context, the forward chaining approach entails certain trade-offs and hurdles. Previous research indicates that forward chaining facilitatesaccurate recommendation generation, and it may be constrained by its reliance on predefined rules and limited adaptability to complex, evolving scenarios. Despite these challenges, the ”sopherbal” application, featuring 50 Sasak medicinal plants curated for 15 common ailments, achieved an 86% validation rate, affirming its efficacy in bridging the gap between traditional herbal knowledge and modern healthcare needs.
Exploratory Analysis of Different Types of Adjectives for Sentiment Classification

Online websites available on the internet, Amazon, provide a platform for users to share their valuable opinions. Users’ reviews are available in thousands, and extracting useful information from these reviews manually is a crucial task for managers, companies, and users. Reviews are written in natural language, and to extract useful information from the reviews, there is a need for an automatic technique known as sentiment analysis. Researchers have used polarity features like nouns, adjectives, verbs, and adverbs to mine sentiment using one feature or combination. The studies showed that adjectives remain the most prominent feature. However, previous research has not evaluated many types on a comprehensive dataset. This research focuses on the identification of different kinds of adjectives in a given text, the identification of the best type and the classification of different kinds as positive, negative, and neutral. Understanding the nuanced impact of various adjectives in sentiment classification is crucial for developing more accurate and context-aware natural language processing models, essential for applications ranging from sentiment analysis to customer reviews. We comprehensively evaluate different types of adjectives on machine learning algorithms. The experimental results are performed on an annotated dataset of 58,258 office product reviews collected from Amazon. Out of these evaluated adjectives, opinion adjectives have the highest precision of 0.931 on the Naïve Bayes classifier and show the best sentiments.
Nexus Between Technology, Education, Income, and Social Capital in Top 10 Terrorism Affected Countries: The Leading Role of Corruption

There is a strong correlation between the expansion of institutions in nations with advanced educational systems and an increase in the frequency and severity of terrorist attacks. This trend remains substantial even after accounting for factors like per capita income, political stability, unemployment, inequality, and urbanization. This is when the frequency and severity of terrorist attacks appear to be at their highest. Therefore, this study analyzes the impacts of terrorism on education in the top 10 terrorist countries between 2010 and 2020. This study considers the determinants of education (EDU): GDP per capita, terrorism, social capital, technology and physical capital. The study employs FMOLS estimation and the DOLS test to check the results of variables in this study. The effect of GDP per capita, social capital, and physical capital significantly positively impact education in this model. However, terrorism and technology have a negative impact on education. Moreover, the moderate effect of terrorism on social capital, technology and physical capital is negatively related to education. On behalf of the results, this study proposes how a country can maximize education.
Corruption in Arab countries: a grease or sand in the wheel of economic growth? a panel smooth transition regression approach

The relationship between corruption and economic growth has long been dealt with in the literature. Yet, no consensus has been drawn about the way how corruption might affect economic growth. This paper aims at revisiting the relationship between corruption and growth in the context of Arab countries using a panel threshold model with smooth transition (PSTR). The study covers 14 Arab countries over a period from 2007 to 2017. Our results show that the institutional quality variable divide the sample into two regimes. In the first regime (low institutional quality), reducing corruption risk hinders economic growth. The second regime (high institutional quality) stipulates that a lower risk of corruption will have a positive effect on economic growth. The results on a country basis reveal two heterogenous groups and one homogenous group in terms of hydrocarbons endowment: (1) Algeria, Egypt, Jordan, Lebanon Sudan ,Syria and UEA are in favor of “grease in the wheels” hypothesis, (2) Bahrain, Kuwait, Morocco and Tunisia demonstrate “the sand in the wheel” hypothesis and (3) Oman, Saudi Arabia and Qatar showed a strong support toward “the sand in the wheel” hypothesis.&#x0D;
DocFlow: A Visual Analytics System for Question-Based Document Retrieval and Categorization

A systematic review (SR) is essential with up-to-date research evidence to support clinical decisions and practices. However, the growing literature volume makes it challenging for SR reviewers and clinicians to discover useful information efficiently. Many human-in-the-loop information retrieval approaches (HIR) have been proposed to rank documents semantically similar to users' queries and provide interactive visualizations to facilitate document retrieval. Given that the queries are mainly composed of keywords and keyphrases retrieving documents that are semantically similar to a query does not necessarily respond to the clinician's need. Clinicians still have to review many documents to find the solution. The problem motivates us to develop a visual analytics system, DocFlow, to facilitate information-seeking. One of the features of our DocFlow is accepting natural language questions. The detailed description enables retrieving documents that can answer users' questions. Additionally, clinicians often categorize documents based on their backgrounds and with different purposes (e.g., populations, treatments). Since the criteria are unknown and cannot be pre-defined in advance, existing methods can only achieve categorization by considering the entire information in documents. In contrast, by locating answers in each document, our DocFlow can intelligently categorize documents based on users' questions. The second feature of our DocFlow is a flexible interface where users can arrange a sequence of questions to customize their rules for document retrieval and categorization. The two features of this visual analytics system support a flexible information-seeking process. The case studies and the feedback from domain experts demonstrate the usefulness and effectiveness of our DocFlow.
WRIST: Wideband, Real-Time, Spectro-Temporal RF Identification System Using Deep Learning

RF emissions' detection, classification, and spectro-temporal localization are essential not only for understanding, managing, and protecting the radio frequency resources, but also for countering today's security threats such as jammers. Achieving this goal for wideband, real-time operation remains challenging. In this paper, we present WRIST, a Wideband, Real-time, Spectro-Temporal RF Identification system. WRIST can detect, classify, and precisely locate RF emissions in time and frequency using RF samples of 100 MHz spectrum in real-time. The system leverages an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">one-stage object detection</i> Deep Learning framework, and transfer learning to a multi-channel visual-based spectral representation. Towards developing WRIST, we devised an iterative training approach which leverages synthesized and augmented RF data to efficiently build a large dataset with high-quality labels. WRIST achieves over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$99 \%$</tex-math></inline-formula> class detection accuracy, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$94 \%$</tex-math></inline-formula> emission precision and recall, with less than 0.08 bandwidth and time offset ratios in a large anechoic chamber over-the-air environment. In the extremely congested in-the-wild environment, WRIST still achieves over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$80 \%$</tex-math></inline-formula> precision and recall. WRIST currently supports five 2.4 GHz technologies (Bluetooth, Lightbridge, Wi-Fi, XPD, and ZigBee) and is easily extendable to others. We are making our curated dataset available to the whole community. It comprises over 10 million labelled RF emissions from off-the-shelf wireless radios spanning the five classes of technologies.
The importance Markov chain

The Importance Markov chain is a novel algorithm bridging the gap between rejection sampling and importance sampling, moving from one to the other through a tuning parameter. Based on a modified sample of an instrumental Markov chain targeting an instrumental distribution (typically via a MCMC kernel), the Importance Markov chain produces an extended Markov chain where the marginal distribution of the first component converges to the target distribution. For example, when targeting a multimodal distribution, the instrumental distribution can be chosen as a tempered version of the target which allows the algorithm to explore its modes more efficiently. We obtain a Law of Large Numbers and a Central Limit Theorem as well as geometric ergodicity for this extended kernel under mild assumptions on the instrumental kernel. Computationally, the algorithm is easy to implement and preexisting librairies can be used to sample from the instrumental distribution.
A Scalable Method for Readable Tree Layouts

Large tree structures are ubiquitous and real-world relational datasets often have information associated with nodes (e.g., labels or other attributes) and edges (e.g., weights or distances) that need to be communicated to the viewers. Yet, scalable, easy to read tree layouts are difficult to achieve. We consider tree layouts to be readable if they meet some basic requirements: node labels should not overlap, edges should not cross, edge lengths should be preserved, and the output should be compact. There are many algorithms for drawing trees, although very few take node labels or edge lengths into account, and none optimizes all requirements above. With this in mind, we propose a new scalable method for readable tree layouts. The algorithm guarantees that the layout has no edge crossings and no label overlaps, and optimizes one of the remaining aspects: desired edge lengths and compactness. We evaluate the performance of the new algorithm by comparison with related earlier approaches using several real-world datasets, ranging from a few thousand nodes to hundreds of thousands of nodes. Tree layout algorithms can be used to visualize large general graphs, by extracting a hierarchy of progressively larger trees. We illustrate this functionality by presenting several map-like visualizations generated by the new tree layout algorithm.