Reviewerly/exHarmony huggingface dataset:
An Analysis of the Level of Students’ Anxiety on Their Writing Skills

Since English has been a foreign language in Indonesia, many achievements are needed in teaching and learning in school. English as subject material in school has four basic language skills, they are reading, writing, speaking, and listening. In learning English as a foreign language, anxiety is a common issue that hinders the student's learning process, including writing skills. The anxiety experienced by students in writing is called writing anxiety. The aim of this qualitative case study is to find out the level of writing anxiety experienced by students in classX-6 at SMAN 1 Prambon and find out teacher's strategies to help students overcome their writing anxiety. The data were collected through the Second Language Writing Anxiety Inventory (SLWAI) questionnaire by Cheng (2004) and interviews were conducted with students of class X-6 and English teachers. The results show that there is a high level of writing anxiety in class X-6 students, with factors such as low self-confidence, lack of topical knowledge, language difficulties, pressure of perfect work, and pressure of limited time. Meanwhile, the teacher has several strategies to help students overcome their writing anxiety, such as memorizing vocabulary sessions at every meeting, giving random questions to help students develop their ideas, providing writing exercises with layouts and pictures to practice their writing skills, giving motivation in every assessment, doing icebreaking and playing games
Investigating the Utilization of the Song 'Darl+ing' by Seventeen K-Pop Group in Improving English Grammar Skill

Utilizing song as a medium for English language acquisition has emerged as a captivating and enjoyable approach incorporated within the curricula of Junior High School and Senior High School under the 2013 educational framework. This research aims to employ the song "Darl+ing" by Seventeen as a catalyst to reinforce and validate grammatical concepts. Through an intricate analysis of the song's lyrical content, this study endeavors to address two pivotal research inquiries: (1) the delineation of distinct grammatical structures presents within Seventeen's composition "Darl+ing" and (2) an exploration of students' perspectives about the integration of English songs for grammar instruction. Employing a qualitative research methodology, the data for this study was gathered from Senior High School students. Notably, 76% of respondents acknowledged the efficacy of employing the song's lyrics as an engaging pedagogical tool. In this model, the application of "Darl+ing" as an educational stimulus holds the potential to invigorate students' grammar learning experiences. The findings culminate in the observation that Seventeen's song encapsulates diverse grammatical elements, rendering it a captivating subject of study. Hence, leveraging song lyrics as a creative conduit serves as a source of inspiration, fostering students' grammatical proficiency and imbuing the learning process with a sense of enthusiasm. In essence, the researchers underscore the recommendation of song lyrics as an innovative strategy to facilitate a comprehensive grasp of grammatical nuances, particularly within the purview of tense variations
Perancangan Game Edukasi Menebak Lirik Lagu-Lagu Daerah Berbasis Unity 2D untuk Platform Android

The development of information and communication technology has had a significant impact on various aspects of life, including in the field of education. One of the increasingly popular uses of technology is the use of educational games to increase interest in learning and understanding material interactively. This study aims to design an educational game based on Unity 2D with the theme "Guess the Lyrics of Regional Songs" for the Android platform. This research uses a new method (GDLC) which consists of six stages of Initiation, Pre-Production, Production, Testing, Beta and Release
Pengembangan Sistem Informasi Pendaftaran Siswa Sekolah Dasar Secara Online dengan Metode Waterfall

The system used at SDN 01 Tanjung Jabung Timur is currently in the process of admitting new students, which is still done manually. The high interest of prospective new students to register at SDN 01 Tanjung Jabung Timur made the admissions committee have difficulty handling it, resulting in a buildup of registrants at the peak of registration, while the number of committees serving was limited. The purpose of this research is to design a website-based new student registration system for easy access from outside the area of ​​students at SDN 01 Tanjung Jabung Timur and to make it easier for prospective students to register at SDN 01 Tanjung Jabung Timur students. System development is carried out using the waterfall model, because the application is easy and systematic. The program is designed using UML (United Model Language) diagrams such as Use Case Diagrams, Activity Diagrams, and Class Diagrams to design an online registration system. This research resulted in a web-based Admissions information system at SDN 01 Tanjung Jabung Timur which was built using the PHP programming language with the Laravel framework and the PhpMyAdmin database and with this application it also helps the school in managing new student data
Sistem Pakar untuk Mendiagnosa Penyakit Telinga Hidung dan Tenggorokan (THT) menggunakan Metode Forward Chaining

The latest developments in the medical world use computers to help diagnose and prevent and treat a disease. In the concept of tracking in finding solutions with an artificial intelligence approach, there are various methods that can be applied to overcome the problem of uncertainty when the tracking process occurs. One of them is the Forward Chaining method. This study aims to develop an expert system that is used for the diagnosis of Ear, Nose and Throat diseases, where users can self-diagnose based on the symptoms they feel. For that we need a method to overcome these problems. In this study a method for self-diagnosing based on the symptoms he felt in tracking cases was applied to diagnose ENT (Ear, Nose and Throat) diseases. The subject of this study is the tracking process to determine ENT disease with the forward chaining model of reasoning. The research method begins with data analysis, system design, coding using Java programming, system testing with white box and black box tests. From the research conducted to produce a software that is capable of determining disease in ENT by applying the forward chaining method. The system trial results show that this application is feasible and can be used.
Monitoring Ketinggian Air Sebagai Pendeteksi Banjir Menggunakan Notifikasi Telegram Berbasis Internet Of Things

Floods are stagnant water caused by blocked rivers or rainfall. Currently residents estimate the potential for flooding is still done manually, there is no monitoring system for detecting water levels and flood warnings. There is no use of ultrasonic-based technology and telegram information notifications for monitoring water level levels as flood detectors. In this study the authors used data analysis methods consisting of observations, interviews and literature studies. The stages of designing a water level monitoring tool system as a flood detector using the Rapid Application Development (RAD) method consist of Requirements Analysis, Design Workshop (Modeling) and Implementation (Implementation). The purpose of this research is to make a water level monitoring tool as a flood detector using an ultrasonic sensor. Assisting online monitoring of water levels via smartphone telegrams as early information on flooding and increasing citizen awareness to detect water levels. The results of this study are that the water level monitoring tool for flood detection can detect the water level properly and can help minimize losses from the impact of flooding on residents by using this tool. The ultrasonic sensor provides accurate information about the water level distance. The buzzer sounds according to the expected distance and sound intensity. Telegram warning notifications provide monitoring information and water level warnings as flood detectors according to the specified water level settings. The mini water pump pumps standing water and drains the water to a safe place when the ultrasonic sensor detects that the distance has reached the maximum limit.
Sistem Keamanan Perumahan Menggunakan Face Recognition

The residential environment system is a system that can be used to assist security officers and neighborhood residents to carry out environmental monitoring of crimes both coming from outside the environment and from the environment itself. This residential security system application uses the face recognition method carried out by residential security. The security system is an important point, which makes it the most important goal of researchers. Data collection methods used such as, observation, observation and literature study. The results of this study are to create a security system application using android-based facial recognition. The conclusion of this research is that this residential security system application is designed with simple systems and features to make it easier for users or users, with the Face Recognition method it makes it easier for security guards to carry out security for people who come out of housing, and the security system application is an application designed to help community and security officers so as not to lose the motorized vehicles of residential residents
Evaluasi Penggunaan Pada Website Dinas Pendidikan dan Kebudayaan Kabupaten Tebo Menggunakan Usability Testing

The Tebo Regency Education and Culture Office is one of the service agencies in Jambi Province. his task is to assist the Regent in carrying out government affairs in the field of educational development, non-formal education and basic education, and cultural processing. on the website Dinasdikbud.tebokab.go.id there has been a significant reduction in visitors of fifteen thousand. Based on these problems, this research was made to analyze the level of satisfaction using the website using the USABILITY TESTING method. With 6 variables namely: Learnability, Efficiency, Memorability, Information Quality, Error, and Satisfaction. This study obtained respondents as many as 100 respondents. The processing of this research data used IBM SPSS Statistics 26 ver 2 software. The results of this study showed that of the 5 variables of USABILITY TESTING, 2 variables namely Efficiency and Memorability did not have a positive effect, only 3 namely Learnability, Information Quality, and Error which significantly affected Satisfaction using the Tebo District Education and Culture Office website
Penerapan Metode MOOSRA Dalam Rekomendasi Pemilihan Calon Panitia Pemungutan Suara (PPS)

Voting Committee is a committee formed by Regency/Municipal KPU/KIP to carry out General Elections (elections) in other villages or sub-districts. The committee is a group of people appointed or elected to consider or take care of matters assigned to the group. General elections in a village become an activity that must be carried out every year that has been determined, where the community will vote to choose who deserves to be a leader through ballots (Balot). In the general election (Pemilu) a committee is needed to carry out the voting called (PPS). This Voting Committee (PPS) will help the community to carry out the general election process later at every level in accordance with the rules made. To choose the committee an Alternative and certain criteria. In this case the Siregar village head has the opportunity to recommend candidates who will become the voting committee who will serve in the village, but the lack of understanding of knowledge about what criteria must be owned by the voting committee makes it often wrong to recommend PPS candidates, and still manually process data from candidates to be recommended so that it takes a long time. Therefore a system is needed using certain methods to solve these problems, in this case the author uses a Decision Support System with the Multiobjective Optimization method on the Basis of Ratio Analysis (MOOSRA) because it can determine criteria that meet the requirements and deserves to be recommended this method is also considered capable of solving the problem because with this system an appropriate and accurate decision can be taken/drawn. Suara (PPS), which is the first alternative with the name Rohani Butar-Butar, is the best alternative with a total value of 4,812
Penerapan Metode WASPAS Dalam Pemilihan Handphone Gaming Terbaik

Nowadays people cannot be separated from cellphones. Mobile phones are a communication and technology tool that is commonly used to make it easier for users to communicate and do various things, such as playing games. To be able to play games, you need very good cellphone specifications, for example battery life, high RAM, high screen resolution, and a good cellphone processor. So, a decision support system is needed in choosing the best cellphone for playing games so that it can help cellphone users in determining the best gaming cellphone. Therefore, in needing to choose the best gaming cellphone, we can use the WASPAS (Weighted Aggregated Sum Product Assessment) method to get a ranking of the best gaming cellphones.
Persepsi Taruna Terhadap Pembelajaran Menggunakan E-Learning

The pupose of this study determine the perceptions of cadets towards online distance learning methods. This study used descriptive qualitative method. Perception assessment is carried out by referring to 3 components, namely: components of understanding On Line learning, constraints in taking On Line learning, Suggestions for the Quality of Online learning. Data collection was carried out using an online questionnaire through Google Form to 92 diploma III cadets who were participating in distance learning using purposive random sampling technique. The results showed that the results of several components of distance learning that were given to the respondents, on average, supported and rated positively towards online distance learning methods carried out by cadets
Creative Approach of the Differentiated Teaching and Project Method in Early Childhood Education

The Early Childhood Education area and school in general should be the platform for the acquisition of knowledge by all children. Education is needed in which active experiences dominate, ensuring a better moral and intellectual education that leads to the desire to continuously acquire knowledge based on their interests in order to be able to cope with the demands of life on a personal and professional level. This paper attempts to show that a holistic approach to the Arts based on the modern pedagogical practices of Differentiated Teaching and the experiential and child-centered project method can be a main instrument for a pluralistic education space that responds to the wide range of diversity of children. The purpose of this paper is twofold. Firstly, to explore through a literature review the general characteristics of Differentiated Instruction and the Project Method, as well as what the role of the Early Childhood Educator should be. The following is a pedagogical activity that was carried out with children aged 3 to 4 years old in a preschool education center.
Blockchain disruption and decentralized finance: The rise of decentralized business models

Blockchain technology can reduce transaction costs, generate distributed trust, and empower decentralized platforms, potentially becoming a new foundation for decentralized business models. In the financial industry, blockchain technology allows for the rise of decentralized financial services, which tend to be more decentralized, innovative, interoperable, borderless, and transparent. Empowered by blockchain technology, decentralized financial services have the potential to broaden financial inclusion, facilitate open access, encourage permissionless innovation, and create new opportunities for entrepreneurs and innovators. In this article, we assess the benefits of decentralized finance, identify existing business models, and evaluate potential challenges and limits. As a new area of financial technology, decentralized finance may reshape the structure of modern finance and create a new landscape for entrepreneurship and innovation, showcasing the promises and challenges of decentralized business models.
Learning to Paint With Model-Based Deep Reinforcement Learning

We show how to teach machines to paint like human painters, who can use a small number of strokes to create fantastic paintings. By employing a neural renderer in model-based Deep Reinforcement Learning (DRL), our agents learn to determine the position and color of each stroke and make long-term plans to decompose texture-rich images into strokes. Experiments demonstrate that excellent visual effects can be achieved using hundreds of strokes. The training process does not require the experience of human painters or stroke tracking data. The code is available at https://github.com/hzwer/ICCV2019-LearningToPaint.
End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors

End-to-end speaker diarization for an unknown number of speakers is addressed in this paper. Recently proposed end-to-end speaker diarization outperformed conventional clustering-based speaker diarization, but it has one drawback: it is less flexible in terms of the number of speakers. This paper proposes a method for encoder-decoder based attractor calculation (EDA), which first generates a flexible number of attractors from a speech embedding sequence. Then, the generated multiple attractors are multiplied by the speech embedding sequence to produce the same number of speaker activities. The speech embedding sequence is extracted using the conventional self-attentive end-to-end neural speaker diarization (SA-EEND) network. In a two-speaker condition, our method achieved a 2.69 % diarization error rate (DER) on simulated mixtures and a 8.07 % DER on the two-speaker subset of CALLHOME, while vanilla SA-EEND attained 4.56 % and 9.54 %, respectively. In unknown numbers of speakers conditions, our method attained a 15.29 % DER on CALLHOME, while the x-vector-based clustering method achieved a 19.43 % DER.
Few-Shot NLG with Pre-Trained Language Model

Neural-based end-to-end approaches to natural language generation (NLG) from structured data or knowledge are data-hungry, making their adoption for real-world applications difficult with limited data. In this work, we propose the new task of few-shot natural language generation. Motivated by how humans tend to summarize tabular data, we propose a simple yet effective approach and show that it not only demonstrates strong performance but also provides good generalization across domains. The design of the model architecture is based on two aspects: content selection from input data and language modeling to compose coherent sentences, which can be acquired from prior knowledge. With just 200 training examples, across multiple domains, we show that our approach achieves very reasonable performances and outperforms the strongest baseline by an average of over 8.0 BLEU points improvement. Our code and data can be found at https://github.com/czyssrs/Few-Shot-NLG
Joint Speech Recognition and Speaker Diarization via Sequence Transduction

Speech applications dealing with conversations require not only recognizing the spoken words, but also determining who spoke when. The task of assigning words to speakers is typically addressed by merging the outputs of two separate systems, namely, an automatic speech recognition (ASR) system and a speaker diarization (SD) system. The two systems are trained independently with different objective functions. Often the SD systems operate directly on the acoustics and are not constrained to respect word boundaries and this deficiency is overcome in an ad hoc manner. Motivated by recent advances in sequence to sequence learning, we propose a novel approach to tackle the two tasks by a joint ASR and SD system using a recurrent neural network transducer. Our approach utilizes both linguistic and acoustic cues to infer speaker roles, as opposed to typical SD systems, which only use acoustic cues. We evaluated the performance of our approach on a large corpus of medical conversations between physicians and patients. Compared to a competitive conventional baseline, our approach improves word-level diarization error rate from 15.8% to 2.2%.
Combination of Transferable Classification With Multisource Domain Adaptation Based on Evidential Reasoning

In applications of domain adaptation, there may exist multiple source domains, which can provide more or less complementary knowledge for pattern classification in the target domain. In order to improve the classification accuracy, a decision-level combination method is proposed for the multisource domain adaptation based on evidential reasoning. The classification results obtained from different source domains usually have different reliabilities/weights, which are calculated according to domain consistency. Therefore, the multiple classification results are discounted by the corresponding weights under belief functions framework, and then, Dempster's rule is employed to combine these discounted results. In order to reduce errors, a neighborhood-based cautious decision-making rule is developed to make the class decision depending on the combination result. The object is assigned to a singleton class if its neighborhoods can be (almost) correctly classified. Otherwise, it is cautiously committed to the disjunction of several possible classes. By doing this, we can well characterize the partial imprecision of classification and reduce the error risk as well. A unified utility value is defined here to reflect the benefit of such classification. This cautious decision-making rule can achieve the maximum unified utility value because partial imprecision is considered better than an error. Several real data sets are used to test the performance of the proposed method, and the experimental results show that our new method can efficiently improve the classification accuracy with respect to other related combination methods.
Does bitcoin provide hedge to Islamic stock markets for pre- and during COVID-19 outbreak? A comparative analysis with gold

This paper applies the DCC-FIGARCH model to investigate the role of Bitcoin as a hedge and safe haven for Islamic stock markets in comparison with gold. We use daily data for the period January 2010–May 2020, which covers the recent COVID-19 pandemic. Empirical results show that the dynamic correlation between Bitcoin and Islamic stock markets is low and usually negative during major economic and political events suggesting that Bitcoin qualifies as a safe haven against Islamic stock markets downturns. Extending our analysis to portfolio management, findings reveal that the diversification benefits of Bitcoin are most times stable and increase significantly during turbulent periods. Thereby, adding Bitcoin in a portfolio of Islamic stocks reduce the risk of portfolio. Finally, as regards the COVID-19 outbreak period, we find that the hedging strategy involving Bitcoin leads to a higher cost during the crisis. These results provide substantial recommendations for Islamic investors and portfolio managers.