Reviewerly/exHarmony huggingface dataset:
INCIDENTAL WRITING LEARNING ON INSTAGRAM IN INFORMAL SETTING

The purpose of this study was to describe the frequency of incidental writing learning that occurred while using Instagram in an informal setting. The respondents were the secondary vocational school’s students in Padang, Grade 11. The researchers employed a cluster random sampling technique to pick 52 students. The descriptive method was used to design this study. A questionnaire was used to obtain the data. The questionnaire was quite reliable, with a coefficient correlation of 0.87. Expert judgment was used to determine content validity. According to the findings of this study, 73% of respondents experienced incidental writing learning when using Instagram in informal contexts. Based on the findings, it was possible to figure out that the frequency of incidental learning writing in Instagram was classified as sometimes scale.&#x0D; Keywords: social media, incidental writing, informal context
Using Video in Role Playing Technique to Improve the Elementary

Speaking is the earliest skill among other language skills acquired by children and serves as the medium most frequently used in communication. Nevertheless, speaking becomes a difficult skill when performed in public, especially for elementary school. This study aims at describing how the use of video as the media in role playing in teaching speaking to elementary school students can improve their ability in speaking. This is a qualitative study using classroom action research as the design. The subject was the elementary school students at SDI Khaira Ummah Padang, West Sumatra, Indonesia. The selected video was entitled —As a Result of Telling Lies which was played before the students were asked to speak. The data were the students’ oral expression ability collected using tests, interviews, observation and documentation. The results of data analysis show that the students’ speaking ability improves in every cycle.&#x0D; Keywords: Videos, role playing, technique in teaching speaking, elementary school students
The Creative Path of Academician Myroslav Ivanovych Zhaldak in the Informatization of Secondary and Higher Pedagogical Education in Ukraine

The article is about a prominent specialist in the field of informatics and methods of its teaching, the founder of a powerful scientific school and research areas, the author of many textbooks and manuals in mathematics and computer science.The stages of his formation as a scientist.Biographical and bibliographic information about him and his scientific achievements are given.The study highlights "First steps in life", "Beginning of scientific path and management", "Scientific works and educational materials", "Scientific and organizational work and awards", "Formation of the scientific elite of the state", "Main activities of scientific school M. I. Zhaldak".The achievements and main directions of functioning of the scientific school of M. I. Zhaldak are analyzed.The influence of the scientific school on the informatization of secondary and higher pedagogical education of Ukraine is determined.
Formación de docentes en competencias digitales para la evaluación formativa mediante e-rúbricas colaborativas

This study is based on the premise that the teaching profession is one of the professions with the greatest responsibility for educating citizens in digital competence, and as such we should focus on how to train these professionals. We carried out this research during an in-service teacher training programme in Ecuador and based it on the principle that we should train teachers in the same way as we expect them to teach their students. During the training programme, teachers acquire formative assessment skills using digital e-rubrics (teacher and peer assessment) and work in collaboration with other teams of teachers. We analysed the results of applying the same digital rubric to an oral competence exercise involving participating and course teachers, and conducted a correlational research design, obtaining a Cronbach's alpha of 0.953 from the 508 evaluations carried out with the same e-rubric. Based on the results, we present a digital rubric that has been validated to assess the oral presentation of educational projects. Moreover, we analysed the difficulties teachers had when using the rubric, as shown in the assessment of the quality of the resources. Examples of other practices and contexts for training teachers in digital rubric methods are also presented. Finally, we provide a set of web-based rubric tools as possible applications.
A Robot Path Planning Method Based on Synergy Behavior of Cockroach Colony

By studying the biological behavior of cockroaches, a bionic algorithm, Cooperative Learning Cockroach Colony Optimization (CLCCO), is presented in this paper. The aim of CLCCO is to provide an efficient method to solve Robot Path Planning (RPP) problems. The CLCCO algorithm is based on the idea of synergy behavior of cockroach colony and machine learning. With pheromone, the cockroach colony achieves population synergy, which includes the follow and diversion behaviors. The strategy of Fibonacci transformation is used for the cockroach individual to choose the next feasible cell. The technologies of λ-geometry and multi-objective search make the paths searched smoother and greatly improve the algorithm search efficiency. In particular, the CLCCO algorithm requires only two parameters to be set. When CLCCO is applied to real robots, a path compression technique is designed. The simulation results show that the CLCCO algorithm demonstrates high efficiency in mostly tests.
The Influence of Motivation, Self-Potential, and Socio-Economic Conditions on The Interest in Continuing to Higher Education

This study aimed to analyse the influence of motivation, self-potential, and socio-economic condition of parents on the interest in continuing to higher education for class XI students for the 2022/ 2023 academic year at Public High School 1 Baturraden. This research is quantitative research using survey method. The population in this study were 358 students using probability sampling technique using simple random sampling using the Slovin formula which resulted in 189 samples. The method in collecting research data used questionnaires, and the data processing method used multiple linear regression analysis. The results of the study show that: motivation has a positive influence on the interest in continuing to higher education; Self-potential has a positive influence on interest in continuing to higher education; and Socio-economic conditions of parents have a positive influence on the interest in continuing to higher education.
Strategy for Implementing Artificial Based Learning Models in Improving Learning Quality

This research seeks to develop and design solutions for artificial intelligence-based learning models to improve learning quality in higher education. The qualitative technique was used in this study, which was completed in three steps: data collection, analysis, and conclusion. To establish the best approach, this study employs validity testing and a SWOT analysis. this research resulting 10 strategies in the implementation of an Artificial intelligent based learning model, namely: Develop a curriculum in accordance with technological developments in Industry 4.0; Establish or establish a special technology development Lab in the field of artificial intelligence and other fields; Creating and using learning media based on bolted intelligence; Conduct regular evaluations by universities/faculties regarding the use or development of artificial intelligence technology; Conducting outreach regarding the importance of data privacy; Provide training for both students and lecturers on artificial intelligence; Provide socialization about entrepreneurship, especially in the field of artificial intelligence; Designing university regulations related to infrastructure to be able to support the development of artificial intelligence; Provide career and talent consulting assistance for students; provide socialization on professional ethics to students and lecturers.
Development of E-Digital Archives of the Faculty of Economics, Universitas Negeri Semarang

This research aims to develop Static and Inactive Archives at the Faculty of Economics into E-Digital Archives and conduct monitoring and evaluation. This study uses a development model (Research and Development). Monitoring and evaluation is carried out to find out the ease of implementing input and what obstacles are experienced when inputting E-Digital Archives. The results of the study show that the condition of archive management at the Faculty of Economics, especially static archives and inactive archives, is still in the process of being reorganized. The FE Record Center has organized manual archives consisting of cupboard A for accounting and financial records for 2013-2020, cupboard B for student and academic archives, cupboard C for general and personnel archives and mixed archives. For the development of e-digital archives, the results of monitoring and evaluation in the UNNES Digital Archive System show that up to October 31, 2022, 1,452 letters/archives have been uploaded, divided into dynamic, inactive and FE UNNES static archives
Evaluating Sentiment Classification to Specify Polarity by Lexicon-Based and Machine Learning Approaches for COVID-19 Twitter Data Sets

As part of data science, sentiment analysis (SA) applied to social media data is a trending research topic. Identifying positive, negative, or neutral opinions or feelings in the text is the attention of sentiment analysis. In the past few years, Social media platforms have become increasingly popular. In this research, natural language processing (NLP) will be employed to extract useful data and information from unstructured text. .The two methods for sentiment analysis covered in this research are the machine-learning method and the lexicon-based method. The paper examines several lexicon approaches to demonstrate the sentiments from Twitter. To increase classification accuracy, it is necessary to use a reliable method with the highest performance. In this study, classifiers such as Support Vector Machine (SVM) and Naive Bayes (NB) were used together with techniques such as TF-IDF (Term Frequency-Inverse Document Frequency) and BOW (Bag of Words). Each algorithm produces a unique outcome. In order to measure the accuracy of classification, metrics such as Precision, Recall, and F-score are considered. This research shows Support Vector Machine (SVM) with TF-IDF is better than other classifiers with an accuracy of 88%.
A Web Application for Audio to Indian Sign Language Translation using Natural Language Processing and Computer Vision

This research paper presents a web application aimed at bridging the communication gap between individuals using sign language (SL) and those with hearing loss.The project's primary focus is to develop an efficient audio-to-Indian Sign Language (ISL) translator using Python, natural language processing (NLP), and computer vision techniques.The context of the study revolves around the challenges faced by the deaf community in communicating with hearing individuals and the limited availability of audio to sign language conversion systems.The proposed solution leverages the Google Speech API for audio recognition, NLP for text preprocessing, and dictionary-based machine translation to generate ISL graphics.The key findings reveal that the application successfully converts spoken input into text and subsequently translates it into Indian Sign Language graphics, facilitating seamless communication between deaf and hearing individuals.The research highlights the potential impact of technology in empowering the deaf community and enhancing accessibility to information and social interactions.
The Influence of Pull Factors on Inter-organisational Labour Mobility in the Public Sector: The Moderating Role of Transformational Leadership

This study assesses how pull factors affect inter-organisational labour mobility, including the role of transformational leadership as a moderator. With the aid of SmartPLS3.2.7, quantitative data from a survey of 333 employees of government agencies were analysed using Partial least Squares Structural Equation Modeling. The results revealed that both compensation and training and development positively influence inter-organisational labour mobility. Furthermore, results indicated a significant moderating effect of transformational leadership on the influence of compensation on inter-organisational labour mobility, and that transformational leadership moderates the influence of training and development on inter-organisational labour mobility. Consistent with Social Exchange Theory and Herzberg’s Two Factor Theory, the results have revealed the relevance of pull factors in explaining inter-organisational labour mobility. Furthermore, the research has provided human resource managers, all managerial personnel and policymakers with insights into the interaction effect between pull factors and transformational leadership on inter-organisational labour mobility to enhance employee retention. The results suggest that organisations should establish transformational leadership training programs, so as to equip all managerial personnel with the vital employees retention skills. The study has theoretically verified that under the influence of the Social Exchange Theory, transformational leadership can interact with pull variables and diminish their effects on inter-organisational labour mobility in the Tanzanian setting, thus adding new knowledge to the current labour mobility model. The limitations of this study form avenues for further research. For instance, considering the interaction effect of pull and push factors and transformational leadership on inter-organisational labour mobility may generate additional insights.
A Supervised Classification Approach for Detecting Hate Speech in English Tweets

As social concerns about threats of hatred and harassment have grown on the internet, there has been a lot of attention paid to detecting hate speech. This research looks at how well SGD classifiers with hyper-parameter tuning perform at detecting hate speech in tweets. It describes the categorization of English tweets with stochastic gradient descent (SGD) classifiers. The categorization of text documents depends on their content, which is divided into groups based on predefined categories. The Term-Frequency (TF) and Inverse-Document Frequency (IDF) parameters are implemented in the proposed system. A Stochastic Gradient Descent method (SGD) is used to generate classifiers that learn independent features, and performance is assessed using Accuracy and F1-score.
Sentiment and Fuzzy Aware Product Recommendation System Using HOA and FT-DBN in E- Commerce

Objectives: To identify and select the customers' liked products by introducing a new product recommendation system.Methods: This work proposes a new product recommendation system that incorporates a new feature optimization method called Sentiment weighted Horse herd Optimization Algorithm (SHOA) to identify the most suitable words that help perform effective prediction.This work's prediction process is carried out by applying a newly proposed Deep Belief Network incorporating fuzzy temporal features.This work uses two different Amazon datasets.The first dataset contains 51, 00,000 review comments about various products, including books and movies.The second dataset is built with 82,00,000 review comments on Toys and Games.These data sets consider the product id and review rate important features and are used to compare with all other available works through experimental results.Findings:The experiments have been conducted using the Amazon dataset and proved better than other recommendation systems in terms of effectiveness and efficiency through Precision, Recall, Serendipity and nDCG value.Novelty: The introduction of a new DBN with Fuzzy Temporal rules and the newly developed SHOA is novel in this work to recommend suitable products to the customer.
Application of The Role Playing Method in Learning Drama Texts to Improve Writing Skills for Class VIII Junior High School Students

The ability to write drama texts at the junior high school level is still relatively low. This study aims to improve the ability to write drama texts by using the role playing method. The research subjects were 35 students of class VIII at SMPN 2 Bandung in the academic year 2020/2021.This research was conducted using a qualitative descriptive research method. In collecting data, the researcher used test, observation and interview instruments. Before and after the learning treatment, students were given a pretest and posttest. Based on the results of the research conducted, the scores for writing drama texts were obtained with an average pretest of 55.4 and posttest of 81.7. The results of the SPSS analysis showed a significance of 0.000&lt;0.05 so that there was a difference between the learning outcomes before and after the treatment. The results obtained indicate that the application of the role playing method in learning to write drama texts can be increased by a difference of 26.3 in grade VIII junior high school students.
Gang Membership among Malaysian Indian Young Adults

Young people involvement in gang crime is not only a problem in Western countries but also in middle and low-income countries.Globally, gangsterism has become a threat to the wellbeing of young adults.Therefore, the present study aims to explore the issue of gang membership, especially among Indian young adults in Kuala Garing Park, in Rawang.An indepth interview approach was used to identify the demographic profile of the gang members and explore the risk factors that promote gang membership.The present study's findings show that the majority of the respondents were single, male, drug dealers, aged between 23 and 24 years old, and had completed their education up to lower secondary level.The findings also show that the respondents were involved in gangsterism due to various reasons such as peer influence, poor relationships with parents, financial deprivation, and a desire to gain power and esteem in society.Since gangsterism is a sophisticated and multidimensional phenomenon, it is therefore recommended that collaboration and synergy among families, schools, social support groups, and law enforcement agencies are essential to create a comprehensive approach to tackle gangsterism issues.Through early intervention, community engagement, and targeted enforcement we can work towards reducing the allure of gangs and creating safer and healthier communities for everyone.
PRESTASI BELAJAR SISWA DITINJAU DARI INTENSITAS MENGGUNAKAN GADGET DAN MINAT BACA NON E-BOOK

This study aims to determine the effect of the use of gadgets on reading interest in 8th grade students of SMPN 3 Tangerang Banten. The number of subjects in this study were 175 people. The research method in this study is a quantitative method. Based on the results of the analysis of research data using multiple regression techniques, it can be said that the multiple linear regression equation also shows that the variable intensity of using gadgets has a negative influence on learning achievement and interest in reading non-e-book books has a positive influence on learning achievement. This is shown through the regression results Y=87.528-0.049X1+0.007X2. Based on the regression model, the constant (a) is 87,528, meaning that if the intensity of using gadgets (X1) and interest in reading non-e-books (X2) is zero, then learning achievement is 87,528. Then the coefficient value of the intensity of the use of the device is -0.049, meaning that if the intensity of the use of the device has increased by one percent, the learning achievement has decreased by 0.049 percent with the condition that the other independent variables are eligible to remain. While the coefficient of interest in reading non-e-book books is 0.007, meaning that if interest in reading non-e-books has increased by one percent, learning achievement will increase by 0.007 percent with the condition that other variables are feasible. . Keywords: Use of Devices, Interest in Reading e-Books, Learning Achievement, Grade 8
BANK NOTE VALUE CHECKER BASED ON IMAGE RECOGNITION

This research aims to develop a banknote recognition system that can help people with special needs, especially people with visual impairments, in recognizing banknote denominations. This system uses image processing technology and machine learning models by utilizing the Create ML library which is integrated with Apple's operating system. By using the Create ML library, modeling the recognition of banknote nominal values can be made easily and without the need for special knowledge in developing machine learning models. The dataset used in this training comes from images of banknotes that have been previously collected and processed. Machine learning models are trained to recognize important features in images such as pictures, numbers and other signs and associate them with the appropriate denominations of money. The test results show that the model created can recognize banknote denominations with an accuracy rate of 71%. This shows that the use of the nominal recognition model for banknotes that is made can help the blind in identifying the nominal money more accurately and efficiently, thereby increasing the independence and quality of life of visual impaired person
Mapping of Freedom of Information Requests (FOIRs) for the Publication of COVID-19 Vaccine Supply Contracts

Freedom of Information Requests (FOIRs) provide the window of access to COVID-19 vaccine supply contracts in times of crisis, yet for COVID-19 supply contracts, FOIRs have recorded limited success due to barriers which have either been legal, institutional, political or a combination of all of these. Despite State's commitment to freedom of information and open contracting at both the national and international level, the urgency to procure vaccines led many countries to prioritize public health goals over protecting the public's right of access to information. This empirical study examines freedom of information requests related to COVID-19 vaccine supply contracts to understand the legal, political, and instructional strategies that enabled the regime of vaccine secrecy and assesses the human rights implications using a human rights impact assessment (HRIA) framework.
Let's Speak Up! Improving the Public Speaking Ability of Karang Taruna Members of Karang Rejo Village, Stabat District, Langkat Regency

Public speaking is a skill that should be possessed in this digital era. In addition to being used as a public speaking technique, public speaking is also an indicator or requirement for prospective workers in many companies. The results of the situation analysis showed that members of the Karang Rejo village cadets, Stabat district, Langkat regency, had problems in public speaking skills; Minimal public speaking skills, low level of awareness to hone public speaking skills, and limited access and materials to learn public speaking. Responding to this problem, activities in the form of socialization and assistance in improving public speaking skills were applied to members of the Karang Rejo village cadets. This activity has been completed on August 7, 2021 at the Karang Rejo Village Hall, Stabat district, Langkat regency. In the implementation of this activity, the method of lectures, discussions and questions and answers is applied. The results concluded that the members of the Karang Rejo village cadets were very enthusiastic and interested in developing public speaking skills. They also agree that public speaking skills are a very important skill in this era.