Reviewerly/exHarmony huggingface dataset:
STUDENTS’ VIEWS ON THE UTILIZATION OF KINEMASTER APPLICATIONS FOR PICTURE DESCRIBING TECHNIQUE IN ENGLISH FOR TOURISM SUBJECT

The purpose of this research was to determine students' views on the Utilization of KineMaster Applications in Implementing Picture Describing Technique of English for Tourism. The method used is the descriptive verification method with ex post facto and survey approaches. The instrument used was a questionnaire distributed to students of English Department of STKIP La Tansa Mahiro. The results showed in general, it was found that the most of respondents agree that Picture Describing Technique using KineMaster application is very beneficial and relevant to be used in English for Tourism class. This is evidenced by the results of 75% of students agree that Picture Describing Technique using KineMaster application is quite relevant and appropriate to be implemented in English for Tourism, 20% strongly agree and 4,2% disagree
Implementasi STBI “Search Operation” dalam Meningkatkan Literasi Informasi Mahasiswa dalam Pembelajaran Daring

Information literacy ability is very important possessed by students. It is intended that the information needed can be met properly. This article will discuss the implementation of the STBI "Search Operation" to help students find information according to their needs. This also relates to the online learning process. This article uses a qualitative method using descriptive analysis method. The purpose of this article is to assist students in implementing STBI "Search Operations" and provide an understanding of the effects of "Search Operations" in the online learning process and improve student literacy skills.
TEACHER'S EFFORTS TO MOTIVATE STUDENTS TO THE IMPORTANCE OF ENGLISH THROUGH MANAGING ENGLISH LEARNING IN THE CLASS ( A Study at SMA N 5 Tidore Islands and SMA YASMU Sofifi )

TEACHER'S EFFORTS TO MOTIVATE STUDENTS TO THE IMPORTANCE OF ENGLISH THROUGH MANAGING ENGLISH LEARNING IN THE CLASS( A Study at SMA N 5 Tidore Islands and SMA YASMU Sofifi )Hariyanti Djafar 1Lukman Tamhir 2Earth Hijrah University, Tidore , North Malukuhariyantidj@gmail.com AbstractThis study aims to know how the students' motivation of learning English, how is the teacher's way to motivate students to learn English, and how the effect of learning management on students. The method use was descriptive qualitative. Data was collected by doing observation, interviews, documentation, and questions. The results of this study stated that students were motivated to learn English caused by two factors, which are an internal stimulus and external stimulus. A teacher should know first these two things before determining what appropriate method to apply. The good of teacher's learning management would help students learning English. Smart students should not always be allowed to work alone in group assignments. This method makes students with the type of external stimulus even more unmotivated. Keywords: Efforts, Motivation, Managing Class.
Pengaruh Sistem Informasi Akademik (SIKAD) dan Kualitas Pelayanan Terhadap Kepuasan Mahasiswa Pada Universitas Islam Riau

This reaserch was conducted at the Islamic University of Riau in the city Pekanbaru, researchers wanted to see how the level of student satisfaction with the academic information system (SIKAD) and the quality of services provided by the Islamic University of Riau on student satisfaction, especially in the 2018/2019 class, sample size was taken with slovin obtained 394 students from a total population of 27,733 students, while the respondents were 165 students who responded to the questionnaire from the google form, via student email. Along with the current COVID-19 pandemic which has occurred for more than a year until the time this research is conducted in 2021. The analytical tool used in the study is Smart PLS. 3, with evaluation of measurement model and evaluation of structural model. Based on this analysis, it was found that the academic information system (SIKAD) and service quality had an effect on student satisfaction of 93.1%. The test for the feasibility of the model used with the Normed Fit Index (NFI) of 0.841 means that the model that is owned is fit, is in the marginal fit category because it is at a critical value of 0.8 NFI 0.90. Path coefficients to see the magnitude of the effect of exogenous variables on endogenous variables, with the t-statistics method (bootstrapping) both variables have a positive and significant effect.
Examining Cross-lingual Contextual Embeddings with Orthogonal Structural Probes.

State-of-the-art contextual embeddings are obtained from large language models available only for a few languages. For others, we need to learn representations using a multilingual model. There is an ongoing debate on whether multilingual embeddings can be aligned in a space shared across many languages. The novel Orthogonal Structural Probe (Limisiewicz and Marecek, 2021) allows us to answer this question for specific linguistic features and learn a projection based only on mono-lingual annotated datasets. We evaluate syntactic (UD) and lexical (WordNet) structural information encoded inmBERT’s contextual representations for nine diverse languages. We observe that for languages closely related to English, no transformation is needed. The evaluated information is encoded in a shared cross-lingual embedding space. For other languages, it is beneficial to apply orthogonal transformation learned separately for each language. We successfully apply our findings to zero-shot and few-shot cross-lingual parsing.
PEMERIKSAAN MOBILE FORENSIK TERHADAP HANDPHONE SECARA PHYSICAL EXTRACTION DENGAN PERBEDAAN JENIS SOFTWARE

One of the electronic evidence found at the crime scene or related to cases, both criminal and civil, is cellphone evidence. To prove the presence or absence of the perpetrator's involvement with the use of mobile forensic examination techniques by physical extraction through analysis of digital traces in the form of call logs, SMS, phonebooks and other files where the data has been deleted. Several factors affect the physical extraction method, namely the software used. Mobile forensic examination software used to examine electronic evidence such as cellphones in forensic laboratories is Ufed Cellebrite 4 PC and XRY Microsystem. In this study, the level of success of the physical extraction method was investigated on evidence of a Nokia 105 (TA-1174) mobile phone with different software, namely Ufed Cellebrite 4 PC and XRY Micro Systemation. Extraction was carried out using the physical boot loader method on the memory in the Nokia 105 (TA-1174) mobile phone IMEI 1: 353810821569303 IMEI 2: 353810821569306. by using Ufed 4 Pc software and XRY Microsystemation, where the extraction results obtained, especially call logs, SMS and data that have been deleted using XRY Micrososystemation software, have the most complete success rate. This relates to the ability of each software in parsing/dumping and decoding processes.
Using forensic handwriting principles for rapid signature screening

Examination of a signature is a lengthy process conducted under laboratory conditions, requiring precision and caution. When a rapid screening of signatures is required, the basic principles of forensic signature comparison can be adapted. Learning points from signature screening examinations are outlined to aid handwriting experts in carrying out similar procedures.
PENGARUH PENGGUNAAN YOUTUBE TERHADAP HASIL BELAJAR MAHASISWA

The purpose of this study was to determine the effect of using youtube media on student learning outcomes in the even semester 2020/2021 Statistics lectures and to see student responses while using youtube media as a source of learning information during lectures. This research is a quasi-experimental research with 18 students taking the subject of statistics. The design in this study used a one group pretest-posttest design. The instruments used in this study were a matter of learning outcomes tests and student response questionnaires. The data analysis technique used was descriptive statistical analysis and inferential statistical analysis. The data was processed using SPSS 22. Based on the results of inferential statistical analysis using the paired sample t-test, an alpha value of 0.000 &lt;0.05 means that there is an effect of using YouTube media on student learning outcomes. It can be seen that there is a difference in the average learning outcomes before and after using YouTube, which is 54.44. In addition, based on the results of the student response questionnaire, it showed that all aspects contained in the student response questionnaire showed an average of 67.36 good results.
Self-trained Pretrained Language Models for Evidence Detection

Argument role labeling is a fundamental task in Argument Mining research.However, such research often suffers from a lack of largescale datasets labeled for argument roles such as evidence, which is crucial for neural model training.While large pretrained language models have somewhat alleviated the need for massive manually labeled datasets, how much these models can further benefit from self-training techniques hasn't been widely explored in the literature in general and in Argument Mining specifically.In this work, we focus on self-trained language models (particularly BERT) for evidence detection.We provide a thorough investigation on how to utilize pseudo labels effectively in the selftraining scheme.We also assess whether adding pseudo labels from an out-of-domain source can be beneficial.Experiments on sentence level evidence detection show that selftraining can complement pretrained language models to provide performance improvements.
Minimizing Annotation Effort via Max-Volume Spectral Sampling

We address the annotation data bottleneck for sequence classification.Specifically we ask the question: if one has a budget of N annotations, which samples should we select for annotation?The solution we propose looks for diversity in the selected sample, by maximizing the amount of information that is useful for the learning algorithm, or equivalently by minimizing the redundancy of samples in the selection.This is formulated in the context of spectral learning of recurrent functions for sequence classification.Our method represents unlabeled data in the form of a Hankel matrix, and uses the notion of spectral max-volume to find a compact sub-block from which annotation samples are drawn.Experiments on sequence classification confirm that our spectral sampling strategy is in fact efficient and yields good models.
Proses digitalisasi naskah kuno sebagai pelestarian informasi di Museum Bandar Cimanuk Indramayu

Introduction. One of the most valuable cultural heritage of the Indonesian nation's ancestors is the ancient manuscript. Ancient manuscripts can be found in every region in Indonesia, especially Indramayu. Most of the ancient manuscripts found in Indramayu have been kept at the Bandar Cimanuk Museum, Indramayu. Most of the ancient manuscripts in the Bandar Cimanuk Museum, Indramayu, are written by hand or in the original form before printing. Digitalization is the process of transferring document media from printed, audio, and video forms. Equipment used in digitizing activities includes software and hardware. In digitizing ancient manuscripts, there are 2 stages that must be followed, pre-digitization and organizing.Data Collection Methods. Using a qualitative methods and descriptive approach with a case study category. Data Analysis. The survey data were descriptively analysed by using 3 steps there are reduction, presentation and conclutsin . Result and Discussion.The result of the process of digitizing an ancient manuscript is an ancient manuscript in digital format. The results show that after the ancient manuscripts in the museum have been digitized, they can provide information according to the needs of the manuscript users and can preserve the information contained in the ancient manuscripts found at the Bandar Cimanuk Museum, Indramayu.Conclusion. Based on the results that have been found in digitizing ancient manuscripts at the Bandar Cimanuk Museum, Indramayu, there are a number of stages that must be carried out, namely the pre-digitalization stage and the organizing stage.
On Public Key Cryptosystem Based On The Word Problem In A Group

One of the classical problems in mathematics is the word problem in a group. The difficulty and complexity for solving this problem is used in most of the cryptosystems. For a fixed set of elements S = {S1, … , Sn} in group G, a word in S is any expression of the sort … where the exponents are positive or negative integers, and . The word problem in a group G with respect to a subset S = {S1, … , Sn} is the question of telling whether two words in S are equal. It is known that in general the word problem is undecidable, meaning that there is no algorithm to solve it. In this paper, we introduce a cryptosystem based on the word problem in a group G.
K-Medoids Algorithm Analysis in Grouping Students' Level of Understanding of Subjects

Analysis of the teaching and learning process needs to be done as feedback on the understanding of the material for students. One of the obstacles faced by schools is that there is no method of how this feedback can be done so that student achievement is uneven. Student achievement in subjects can be seen from the results of the scores on the report cards obtained by students after taking the final semester exam. Due to the uneven achievement of students, it is necessary to make a method so that feedback analysis can be carried out on the level of student understanding of the subject. Is data mining with clustering techniques using the K-Medoids algorithm. With this algorithm, students' understanding of subjects with high potential can be grouped with high brightness average results
Hierarchical Fuzzy Signature and Neuro-Fuzzy Hybrid System for QMS Control

Recently, the Quality Management System (QMS) control supports organizations managers identifying the best practices to upgrade the efficiency and effectiveness. This control has become a successful tool to improve the organization decision-making process. However, QMS encloses several performance indicators inputs that necessitate to be managed. In fact, it may include as inputs, customers requirements, quality policies, standard procedures and many other criteria. Hence, to provide the control of QMS problem insurance, two approaches are investigated which are Hierarchical Fuzzy Signature (HFS) and NeuroFuzzy Hierarchical Hybrid system (NFHH), respectively. These approaches are applied in the case of an industrial company operating in the electromechanical sector. This company has to be creative, agile, responsive and especially ready for fierce competition. Then, the obtained results are compared to Adaptive Neural Fuzzy Inference and Neural Network Systems, regarding the learning phase. Consequently, all of them help the company to assess its overall performance. However, NFHH reaches the best accuracy, reduces the number of neurons and uses the parameters that keep the universal approximated property of neural networks and fuzzy systems. Keywords—Quality management system, Fuzzy logic, Neuro-Fuzzy, hierarchical structure, fuzzy signature
Using the Quizizz Application in the Vocabulary Building Course: Problems and Solutions

Abstract: The writing of this article is based on the experience of the author/researcher as a lecturer withtheaimofknowingtheresultsofusingtheQuizizzapplicationintheVocabularyBuildingcourse for English Literature students at Al-Ghifari University. Students make quizzes based on Vocabulary Building course materials. The quiz that has been created is then uploaded to the Quizizz page/application.Then,studentswillgetalinktotakethequiz.Thequizlinkissharedwithallstudents intheVocabularyBuildingonlineclass.StudentswhoattendonlineclassesintheVocabularyBuilding coursearerequiredtoparticipateinthequiz.Aftertakingthequiz,ananalysiswasconductedregarding the activities that had been carried out. The research method used is descriptive qualitative research methods. The data obtained for this research is through participant observation and interviews. Based on the results of observations and interviews, various responses were revealed when using the Quizziz application which could be obstacles andsolutions.Keywords: Quizzes, Quizizz application, Vocabulary Building course
Multilingual Epidemic Event Extraction : From simple Classification methods to Open Information Extraction (OIE) and Ontology

There is an incredible amount of information available in the form of textual documents due to the growth of information sources.In order to get the information into an actionable way, it is common to use information extraction and more specifically the event extraction, it became crucial in various domains even in public health.In this paper, We address the problem of the epidemic event extraction in potentially any language, so that we tested different corpora on an existed multilingual system for tele-epidemiology: the Data Analysis for Information Extraction in any Language (DANIEL) system.We focused on the influence of the number of documents on the performance of the system, on average results show that it is able to achieve a precision and recall around 82% but when we resorted to the evaluation by event by checking whether it has been really detected or not, results are not satisfactory according to this paper's evaluation.Our idea is to propose a system that uses an ontology which includes information in different languages and covers specific epidemiological concepts, it is also based on the multilingual open information extraction for the relation extraction step to reduce the expert intervention and to restrict the content for each text.We describe a methodology of five main stages: Preprocessing, relation extraction, named entity recognition (NER), event recognition and the matching between the information extracted and the ontology.
Inducing Transformer's Compositional Generalization Ability via Auxiliary Sequence Prediction Tasks

Systematic compositionality is an essential mechanism in human language, allowing the recombination of known parts to create novel expressions. However, existing neural models have been shown to lack this basic ability in learning symbolic structures. Motivated by the failure of a Transformer model on the SCAN compositionality challenge (Lake and Baroni, 2018), which requires parsing a command into actions, we propose two auxiliary sequence prediction tasks as additional training supervision. These automatically-generated sequences are more representative of the underlying compositional symbolic structures of the input data. During inference, the model jointly predicts the next action and the next tokens in the auxiliary sequences at each step. Experiments on the SCAN dataset show that our method encourages the Transformer to understand compositional structures of the command, improving its accuracy on multiple challenging splits from ≤ 10% to 100%. With only 418 (5%) training instances, our approach still achieves 97.8% accuracy on the MCD1 split. Therefore, we argue that compositionality can be induced in Transformers given minimal but proper guidance. We also show that a better result is achieved using less contextualized vectors as the attention’s query, providing insights into architecture choices in achieving systematic compositionality. Finally, we show positive generalization results on the grounded-SCAN task (Ruis et al., 2020).
Penerapan Strategi Total Physical Response, Bernyanyi, Dan Permainan Edukatif Pada Pembelajaran Bahasa Arab Untuk Anak Usia Dini

Early childhood is an individual figure that is in the age range of 0-7 years where at this time is often referred to as the Golden Age. At this time adults play a very important role that provides stimulation in developing aspects of development. Therefore, the right start-up is needed so that children feel happy so that they can receive good learning. The research approach used in this research is a qualitative approach. The type of research is Library Research research. And this study uses descriptive qualitative analysis. There are several strategies that can be used, including by applying the TPR (Total physical response) learning model, which focuses on introducing them to Arabic vocabulary through speech and action. Furthermore, there is a method of singing that is very liked by all children so that they do not feel bored in doing an activity. And lastly by applying educational game methods that students hope to no longer feel bored with Learning Arabic. The purpose of this research is to find the right and relevant strategies in learning Arabic. The Results of the implementation of this strategy are able to stimulate early childhood in acquiring a second language, namely Arabic.
Social semiotics of Mẻn Brayut text: systemic functional linguistics perspective

Mẻn Brayut text is one of Balinese texts develops in Balinese communities. The text is represented in spoken and written text held by Balinese communities. Even more, the text is supported with the statue of Mẻn Brayut found in number of temples in Bali. However, the message conveyed through the text has not been understood yet by most Balinese people. This phenomenon makes the text be interpreted differently. This is because the text has social semiotic conveyed through nonverbal language. Therefore, this research focused on social context embedded in the text of Mẻn Brayut to solve the differences interpretation. The theory used to explore used to analyze the problems is Systemic Functional Linguistics proposed by Halliday. The data were taken from written text (Suwija, 2019). The research used qualitative method since the theory is used as guidance of data collection. The data were collected based on field, tenor, and mode. The result of the result showed that the text described seriousness and sincerity of mother develops the children without having profit orientation, but she emphasizes in profound love. More abstractly, text of Mẻn Brayut represented in statue accompanied by many children placed in number of temples in Bali is interpreted as the propound God’s love for all human.
Neuralizing Regular Expressions for Slot Filling.

Neural models and symbolic rules such as regular expressions have their respective merits and weaknesses. In this paper, we study the integration of the two approaches for the slot filling task by converting regular expressions into neural networks. Specifically, we first convert regular expressions into a special form of finite-state transducers, then unfold its approximate inference algorithm as a bidirectional recurrent neural model that performs slot filling via sequence labeling. Experimental results show that our model has superior zero-shot and few-shot performance and stays competitive when there are sufficient training data.
The Influence of WhatsApp Texting on Spelling System of Students at Intermediate Level

The purpose of the study is to see how WhatsApp text messaging affects students' informal writing.Students' spelling systems have grown erroneous as a result of the widespread usage of WhatsApp texting.The research is based on numbers.To conduct a survey, a closed-ended questionnaire was created.The data was obtained from 50 students at Punjab College Bahawalpur and then statistically analysed.To show the findings, tables and graphs were created.Crispin Thurlow's (2003) theoretical framework was employed in the present study, which followed the paradigm he proposed in his book "Generation Txt?"The Sociolinguistics of Young People's Text-Messaging."The study highlights students' excessive usage of WhatsApp Messenger, which leads to a state of duality in which they are on the edge of breaching Standard English norms.