Reviewerly/exHarmony huggingface dataset:
Enhanced TextRank using weighted word embedding for text summarization

&lt;p&gt;&lt;span lang="EN-US"&gt;The length of a news article may influence people’s interest to read the article. In this case, text summarization can help to create a shorter representative version of an article to reduce people’s read time. This paper proposes to use weighted word embedding based on Word2Vec, FastText, and bidirectional encoder representations from transformers (BERT) models to enhance the TextRank summarization algorithm. The use of weighted word embedding is aimed to create better sentence representation, in order to produce more accurate summaries. The results show that using (unweighted) word embedding significantly improves the performance of the TextRank algorithm, with the best performance gained by the summarization system using BERT word embedding. When each word embedding is weighed using term frequency-inverse document frequency (TF-IDF), the performance for all systems using unweighted word embedding further significantly improve, with the biggest improvement achieved by the systems using Word2Vec (with 6.80% to 12.92% increase) and FastText (with 7.04% to 12.78% increase). Overall, our systems using weighted word embedding can outperform the TextRank method by up to 17.33% in ROUGE-1 and 30.01% in ROUGE-2. This demonstrates the effectiveness of weighted word embedding in the TextRank algorithm for text summarization.&lt;/span&gt;&lt;/p&gt;
METACOGNITIVE STRATEGIES AND MOTIVATION OF STUDENT LEARNING

Relevance of the proposed issue has been determined by determined by the importance of understanding a personality of the student as a subject of their own self-regulated learning. There has been a scientific need to characterize the concept of self-regulated learning, analyse the features of the use of metacognitive strategies in the learning activities of students. In the article, the author has theoretically analysed the psychological features of use of metacognitive strategies in motivating the learning activity of students. For empirical evaluation of the levels of the educational strategies use and the direction of student motivation, we have used the questionnaires “Learning Strategies” (by S. Kostromina, T. Dvornikova) and “Scales of Academic Motivation” (by T. Gordeeva, O. Sychev, E. Osin). Theoretical analysis and empirical research have shown a positive correlation between the use of metacognitive strategies and student motivation. As a result of analysing the correlations between metacognitive strategies and motivation, we have drawn the conclusion that learning activities interest students in the presence of intrinsic motivation, and is accompanied by emotional experiences in the use of appropriate metacognitive strategies. The methodological recommendations aimed at the effective application of the motivating strategies of students, as well as the formation of their appropriate learning motivation have been developed.
COPING STRATEGIES AS A MECHANISM OF SELF-REGULATION IN THE EDUCATIONAL ACTIVITIES OF STUDENTS

The article conducts a theoretical study of the concepts of "self-regulation" and "coping strategies", and uses scientific approaches to the definitions of these concepts from Ukrainian and foreign works. The role of emotional intelligence in increasing the effectiveness of coping strategies as self-regulation mechanisms of students during educational activities is highlighted. The results of an empirical study of the peculiarities of personal self-regulation are presented, taking into account the gender differences of the respondents. The peculiarities of the choice of destructive or constructive coping strategies have been revealed. The results of the study on correlations between personal self-regulation in the form of action orientation and state orientation, coping strategies and components of emotional intelligence are presented, which gives grounds for drawing conclusions about the interdependence of these concepts. The summarized results expand the theoretical and empirical basis for the further development of emotional intelligence in order to increase the effectiveness of students' coping strategies in the stressful conditions of educational activities during martial law.
Comparative analysis of Mamdani, Larsen and Tsukamoto methods of fuzzy inference system for students’ academic performance evaluation

Over the last few years, the use of the fuzzy logic technique for evaluating performance in the teaching-learning process is growing rapidly. In this research work, three different fuzzy inference methods: Mamdani fuzzy inference method, Larsen fuzzy inference method and Tsukamoto fuzzy inference method have been proposed for students' academic performance appraisal for multi-input variables. To obtain a degree of satisfaction, the Triangular membership function is used. The results of experiments showed the best fuzzy inference method among Mamdani, Larsen and Tsukamoto. We have also compared the results with the existing statistical method.
Aggregating Users&amp;rsquo; Online Opinions Attributes and News Influence for Cryptocurrencies Reputation Generation

Reputation generation systems are decision-making tools used in different domains including e-commerce, tourism, social media events, etc. Such systems generate a numerical reputation score by analyzing and mining massive amounts of various types of user data, including textual opinions, social interactions, shared images, etc. Over the past few years, users have been sharing millions of tweets related to cryptocurrencies. Yet, no system in the literature was designed to handle the unique features of this domain with the goal of automatically generating reputation and supporting investors&amp;rsquo; and users&amp;rsquo; decision-making. Therefore, we propose the first financially oriented reputation system that generates a single numerical value from user-generated content on Twitter toward cryptocurrencies. The system processes the textual opinions by applying a sentiment polarity extractor based on the fine-tuned auto-regressive language model named XLNet. Also, the system proposes a technique to enhance sentiment identification by detecting sarcastic opinions through examining the contrast of sentiment between the textual content, images, and emojis. Furthermore, other features are considered, such as the popularity of the opinions based on the social network interactions (likes and shares), the intensity of the entity&amp;rsquo;s demand within the opinions, and news influence on the entity. A survey experiment has been conducted by gathering numerical scores from 827 Twitter users interested in cryptocurrencies. Each selected user assigns 3 numerical assessment scores toward three cryptocurrencies. The average of those scores is considered ground truth. The experiment results show the efficacy of our model in generating a reliable numerical reputation value compared with the ground truth, which proves that the proposed system may be applied in practice as a trusted decision-making tool.
Frieze Group in Generating Traditional Cloth Motifs of the East Nusa Tenggara Province

Ethnomathematics studies the relationship between mathematics and culture. Indonesia has many traditional cultures. One of them is traditional cloth. The traditional cloth from East Nusa Tenggara (NTT) province is called tenun ikat. Since the motif of tenun ikat consists of symmetrical and repeated patterns, it can be generated using Frieze groups. The Frieze groups are the plane symmetry groups of patterns whose subgroups of translations are isomorphic to Z. There are seven groups in the Frieze groups, i.e., F_1, F_2, F_3, F_4, F_5, F_6, and F_7. Translation, reflection, rotation, and glide reflection are the transformation used in the Frieze groups. In this paper, Frieze groups are used to generate digital tenun ikat motifs from the basic pattern. Since one piece of original tenun ikat may consist of some basic patterns, the basic patterns are identified first, and then each of them is generated into the desired pattern, according to the suitable Frieze groups. Furthermore, a GUI Matlab program is developed to generate the Frieze groups. Three motifs of tenun ikat are presented to demonstrate the implementation of Frieze groups. With the Frieze group, users can generate other patterns from a basic pattern, so users can generate new motifs of tenun ikat without leaving the cultural characteristics of NTT province.
Penerapan Algoritma K-Nearest Neighbor Untuk Klasifikasi Rumah Layak Atau Tidak Layak Huni (Studi Kasus: Desa Bulu Kecamatan Kraksaan Kabupaten Probolinggo)

The house is a need that must be met, in addition to food and clothing needs, as well as an indicator of community welfare, to create a safe, comfortable and healthy living environment. The government provides social rehabilitation assistance to the community for uninhabitable houses by helping to buy building materials so they can rehabilitate homes that are not proper. In Bulu Village there are still many places to live that are categorized as uninhabitable houses. This is because of the community's income factor and limited knowledge about the function of the house, as well as facilities and infrastructure that make it increasingly difficult to realize livable dwellings. This research uses the K-Nearest Neighbor algorithm for the classification of decent or uninhabitable homes which aims to provide convenience in determining prospective recipients of social rehabilitation assistance for uninhabitable houses with accurate results and minimizing mistargeting. The results of this study are an average accuracy of 96.25% with a standard deviation of 5.73% in the 7th model test using 10-fold cross-validation with odd k and validation and evaluation of results with the confusion matrix getting an accuracy value of 100%, the precision value is 100%, the recall value is 100%, and the f-measure value is 100% with k = 13.
APPLICATION OF BROWN AND LEVINSON’S MODEL ON JOE BIDEN’S VICTORY SPEECH: A CASE ON POLITENESS STRATEGY

This research discussed about politeness strategies in Joe Biden’s victory speech. The researcher used theory of Brown and Levinson (1987). This theory to analyzed the types of politeness strategy and the dominant types in Joe Biden victory speech. The source of the data was taken from Joe Biden’s speech in YouTube Its about 15 minutes, 19 seconds. This speech was published at 8 November 2020. The researchers chose Joe Biden’s speech because the researcher found that the types of politeness strategy in this speech. the researcher found 22 data and three types of politeness strategy namely positive politeness 18 (81.8%), negative politeness 1 (4.5%) and off record indirect strategy 3 (13.6%). Positive politeness that found in this speech namely: uses promise, intensifity interest to the hearer, be optimistic, repetition, joke, assume or assert reciprocity, offer, and use rhetorical strategy, negative politeness that found in this speech was use pessimistic and off record indirect strategy namely use metaphors and give hints or directions. The most dominant types in Joe Biden Victory speech was positive politeness strategy. Positive politeness used in the speech so that make good communications between the speaker and the hearer and also make the situations comfortable, relax and make a pleasant situation in doing communication.
SOCIAL CONFLICTS FOUND IN THE LEGENDS OF DAYANG MERINDU AND NAYA SENTIKA AND THEIR IMPLEMENTATIONS IN LITERATURE LEARNING

This research describes the realizations of social conflicts, the function of social conflict, the similarities and differences of Dayang Merindu and Naya Sentika legends, and the implications on literature learning. The research applied a descriptive comparative method supported by an objective approach. Then, the researchers analyzed the data by collecting, reducing, presenting, and concluding the data. The data sources were the legends of Dayang Merindu and Naya Sentika. The research data were social conflict realizations and functions of the legends in the form of text excerpts. The results showed differences in the legends. The legend of Dayang Merindu had three types of conflicts: interpersonal, interest, and inter-social conflicts. The legend of Naya Sentika had four types of conflicts: interpersonal, interest, inter-group, and international conflicts. The similarities of the legends were the social functions of the conflicts. They were two functions: solidarity and communicative functions. The current research results are applicable for literature learning and further reading sources as the realization of literature appreciation.
VARIETY OF ENGLISH LEARNING MEDIA TECHNOLOGY: VOICES FROM NOVICE LEARNERS

The existence of technological media in the learning process has its own roles and challenges in this era of disruption. The purpose of this study is the extent to which the use of technological media supports learning English in junior high schools and the equivalent. The research method used is the survey method. The research was conducted in 36 public and private junior high schools and Madrasah Tsanawiah in Kuningan Regency by collecting data through a Google form questionnaire. The results obtained turned out that of the 59 teachers who filled out the Google form, as many as 86.4% of English teachers used laptops, handphones with infocus, frequently used applications, Whatsapp 28.8%, Power Point 22%, Youtube 32.2%, and E-learning 16.9%. However, 88.1% stated that teachers had not maximized the use of technological media in learning English. On the other hand, from 200 students grade seven (19%), grade eight (40%) and grade nine (41%), there are 54.5% did not use technology media, 37% used laptop, infocus, and Handphone, and 8.5% used laboratorium.
Politically-oriented information inference from text

The inference of politically-oriented information from text data is a popular research topic in Natural Language Processing (NLP) at both text- and author-level. In recent years, studies of this kind have been implemented with the aid of text representations ranging from simple count-based models (e.g., bag-of-words) to sequence-based models built from transformers (e.g., BERT). Despite considerable success, however, we may still ask whether results may be improved further by combining these models with additional text representations. To shed light on this issue, the present work describes a series of experiments to compare a number of strategies for political bias and ideology inference from text data using sequence-based BERT models, syntax-and semantics-driven features, and examines which of these representations (or their combinations) improve overall model accuracy. Results suggest that one particular strategy - namely, the combination of BERT language models with syntactic dependencies - significantly outperforms well-known count- and sequence-based text classifiers alike. In particular, the combined model has been found to improve accuracy across all tasks under consideration, outperforming the SemEval hyperpartisan news detection top-performing system by up to 6%, and outperforming the use of BERT alone by up to 21%, making a potentially strong case for the use of heterogeneous text representations in the present tasks.
TO THE PROBLEM OF SELF-REGULATED LEARNING IN CONDITIONS OF UNCERTAINTY 

The article presents a theoretical study of the problem of applying approaches of self-regulated learning in conditions of uncertainty. Self-regulated learning is a set of skills and strategies that allow learners to manage their learning process, including their thoughts, emotions, and behavior. The use of self-regulated learning practices is emphasized, as these can be particularly useful for students in situations of uncertainty and allow them to take control of their learning as well as to cope more effectively with difficult situations and achieve learning goals. Basically, the use of metacognitive and self-regulatory strategies in the educational process is an important factor in predicting successful learning outcomes in conditions of uncertainty. The analysis of the literature showed that the issue of effective organization of training and independent work of students is not only to form subject knowledge in the learning process but also to teach the ability to learn. To promote self-regulated learning in conditions of uncertainty, pedagogues can provide clear and consistent expectations and feedback on students' progress, encourage students to set their own learning goals and to reflect on their progress towards achieving them, teach students strategies for managing their emotions, provide opportunities for peer feedback, help students to identify their strengths and weaknesses and to develop strategies for addressing areas where they need to improve. By promoting self-regulated learning in these ways, teachers can help students to cope with uncertainty, and to become more effective and confident learners. The perspective of further research is in the analysis and development of a comprehensive study of approaches, principles, methods, techniques, means, and models of the formation of self-regulated learning skills in conditions of uncertainty.
Analysis of code-based digital signature schemes

&lt;span lang="EN-US"&gt;Digital signatures are in high demand because they allow authentication and non-repudiation. Existing digital signature systems, such as digital signature algorithm (DSA), elliptic curve digital signature algorithm (ECDSA), and others, are based on number theory problems such as discrete logarithmic problems and integer factorization problems. These recently used digital signatures are not secure with quantum computers. To protect against quantum computer attacks, many researchers propose digital signature schemes based on error-correcting codes such as linear, Goppa, polar, and so on. We studied 16 distinct papers based on various error-correcting codes and analyzed their various features such as signing and verification efficiency, signature size, public key size, and security against multiple attacks.&lt;/span&gt;
THE ENGLISH TEACHER’S PROFICIENCY IN SOUTH SULAWESI: ITS IMPLICATIONS TO THE TEACHER’S PERFORMANCE

In this article, it referred to the implications of proficiency to the teacher’s performance in the classroom in South Sulawesi. Most of English teachers associate level of language proficiency with greater powerful teaching performance skills. This research was descriptive qualitative research in South Sulawesi, the participants consisted of several qualified teachers aged from 30 – 40, and they have been teaching more than 10 years, all of the participants interviewed felt strong desire about the implications of proficiency. The data were collected from observation, interview and documents and it was analyzed in interpretation to draw inferences and conclusions based on the description data. The result of this research provided a great interpretation of proficiency and its excessive implication for teaching English, the higher level of language proficiency is, the better performance of the teacher is. It is needed to investigate more about the role of language proficiency to determine the teachers’ performance.
THE FACTORS OF STUDENTS’ INVESTMENT IN LEARNING ENGLISH DURING ONLINE LEARNING AT ONE OF SMPN IN MUSI RAWAS

Most of the students decided to invest in learning English was because of the perceived capital that provided them with benefits for their academics as well as their future careers. This study used a qualitative narrative inquiry by using interviews and documentation instruments. This study was included the interviewed with seven participants of ninth grader at one of SMPN in Musi Rawas. This study was aimed to investigate the factors affecting the students’ investment in learning English at one of SMPN in Musi Rawas invested in learning English during online learning. The students invested in learning English was because of From the interviews, the results of this study was indicated that: (1) the most dominant factors affecting the ninth students invested in learning English was family support, the second dominant factor was better English achievement, and the last dominant factor was past experience. This study findings confirmed that the seven students had been put some efforts in their investment in learning English in order to acquire their goals in the present and also future. Then, they also wanted to improve their English language skill. Furthermore, this study may help the students understand about the importance of learning English in the present and also in the future.
EXPLORING TEACHERS’ ABILITY IN DEVELOPING PISA-LIKE READING TASKS

This study is a part of a joint study, aiming to develop a teacher professional development program on training teachers to teach PISA-like reading. The bigger program focuses on a pedagogical intervention that incorporates PISA reading into English and Indonesian subjects based on Systemic Functional Linguistics Genre-Based Approach (SFL GBA) and has been reported in Emilia et al. (2022). Meanwhile, this study centred around the observation of English teachers’ ability to develop PISA-like reading tasks. The intervention is framed within PISA reading (OECD, 2019a,b), and SFL GBA (Halliday Matthiesen, 2014; Derewianka Jones, 2016; Emilia, 2011). The study employed a case study design. The findings show that teachers were able to develop PISA-like reading tasks, evidenced from the collected reading items that follow PISA 2018 cognitive processes and response format (OECD, 2019 a, b). Moreover, teachers’ responses from interviews were likewise positive, indicating their increased awareness of PISA and their ability to design similar reading tasks. It is recommended that the training be conducted in a variety of settings with a larger number of teachers for them to eventually assist Indonesian students in improving their reading literacy as suggested by PISA.
DESCRIPTIVE READING MATERIALS FOR TENTH GRADERS: PALEMBANG TOURIST DESTINATIONS

The purpose of this study was to find out the validity, practicality and potential effect of the developed descriptive reading materials about Palembang tourist destinations for the tenth-graders of vocational high school¬. This study was conducted based on Akker (analysis, design, evaluation, and revision) development research design. The formative evaluation was consisted of self-evaluation, expert review, one-to-one evaluation, small group evaluation, and field trial. Formative evaluation was intended to find out the validity, practicality and potential effect of the product. The average validity score of the developed product was categorized as a very highly valid level. The practicality in one-to-one was at a highly practical level and small group evaluation was at a very high practical level. The reading test material was categorized as effective. It showed that in the reading test students exceeded the passing grade which was 75. In brief, descriptive reading texts of Palembang tourist destinations were able to help students know about tourist destinations. The developed product was appropriate for the tenth-graders of vocational high school, especially for tourism majoring.
Cell Disease Identification Using Enhanced Salp Swarm Algorithm in Machine Learning

Computerized diagnosis of white blood cells cancer diseases for instance Leukemia and Myeloma is a demanding biomedical research area. Our method presents for the first time a new state of the application that assists in diagnosing the white blood cells diseases. We divide these diseases into two types; each type includes similar symptoms a disease that may my method is applied on one of the two diseases category by computing different features. Finally, Random Forest classifier is enforced for final decision. The proposed method aims to early discovery of white blood cells cancer, reduce the misdiagnosis cases in adding up to develop the system learning methodology. Moreover, allowing the experts only to have the final modification on the result obtained from the system. The proposed approach achieved an accuracy of 93% in the first type and 95% in the second type.