Reviewerly/exHarmony huggingface dataset:
MALAY LANGUAGE IN STIE BINA KARYA

Endangered language has a close meaning to language shift. The situation when the number of that language user is getting less. Endangered language is when the children of a family do not acquire their "mother tongue" any longer. Although, they live in the location where the language comes from. For example, the Malay tribe in Tebing Tinggi. Tebing Tinggi is inhabited by three significant tribes, Batak, Javanese, and Malay. Moreover, Tebing Tinggi was surrounded by the coastal area. Serdang Bedagai and Batu Bara were the Malay tribe that dominated this area. Sekolah Tinggi Ilmu Ekonomi Bina Karya (STIE) Bina Karya is an institute placed in Tebing Tinggi. Most of its students come from the local area, and those areas, Serdang Bedagai and Batu Bara area are Malay people. However, they were rarely found uttering the Malay language when talking at the campus. This qualitative research will see the language endangered in the Malay language in STIE Bina Karya students. This study took twenty-nine Malay students as the informants in STIE Bina Karya. By distributing the open-ended questionnaire, then analyzing it using the thematic analysis. After analyzing the data, the Malay language in STIE Bina Karya was invulnerable and severely endangered. The most factors come from 1) the small number of users, 2) bilingualism dominates the communication, 5) parents do not play an important role in teaching their generation the minority language(linguistic suicide).
THE CORRELATION BETWEEN PRONUNCIATION AND LISTENING ACHIEVEMENT OF ENGLISH EDUCATION STUDY PROGRAM STUDENTS OF TRIDINANTI UNIVERSITY

The objective of this study was to find out whether or not there was a significant correlation between pronunciation and listening achievement of English education study program students of Tridinanti University and how much pronunciation contributed to listening achievement of English study program students of Tridinanti University.In this study, the researchers used correlation analysis.The population of this study was all English education study program students of Tridinanti University.The researchers used purposive sampling, and the sample was 53 students taken from the 3 rd , 5 th , 7 th , and 9 th semester.Pronunciation and listening achievement tests were used as the instruments.The finding showed that the pearson correlation coefficient was 0,086.It means that p-value (0.539) was higher than 0.85 which indicated that there was very low correlation between pronunciation and listening achievement of English education study program students of Tridinanti University.The regression analysis revealed that the significance value (ρ) was 0.284.It was higher than alpha value (α) 0.05 which indicated that students" pronunciation gave a positive contribution toward their listening achievement and the value of R Square was 0.022.It could be concluded that students" pronunciation contributed as much as 2.2 % toward their listening achievement.
Principles of Humanities and Methodological Features of Humanitarian Knowledge in the Information Society

The article is devoted to the analysis of the specifics of humanitarian knowledge and cognition. The relevance of this study is due to the special role of education in the life of modern society, guided by the principles and values of the post-industrial era. The main tasks of the humanities at the present stage of the development of the information society are identified. The trans-disciplinary and meta-disciplinary approaches to humanitarian knowledge and education are considered as the fundamental methodological foundations of the modern stage of development of the humanities. Fundamental methodological changes in certain branches of humanitarian knowledge are identified as a response to globalization, information, and systemic changes in society. Conclusions are drawn about the status of humanitarian knowledge at the stage of permanent innovation and digitalization of society, about the interest in expert assessments confirming the reliability and assurance of knowledge and the results of its use, about the constructive possibilities of optimal integration of digital and humanitarian technologies.
Divide &amp; Conquer Imitation Learning

When cast into the Deep Reinforcement Learning framework, many robotics tasks require solving a long horizon and sparse reward problem, where learning algorithms struggle. In such context, Imitation Learning (IL) can be a powerful approach to bootstrap the learning process. However, most IL methods require several expert demonstrations which can be prohibitively difficult to acquire. Only a handful of IL algorithms have shown efficiency in the context of an extreme low expert data regime where a single expert demonstration is available. In this paper, we present a novel algorithm designed to imitate complex robotic tasks from the states of an expert trajectory. Based on a sequential inductive bias, our method divides the complex task into smaller skills. The skills are learned into a goal-conditioned policy that is able to solve each skill individually and chain skills to solve the entire task. We show that our method imitates a non-holonomic navigation task and scales to a complex simulated robotic manipulation task with very high sample efficiency.
Using T –Chart Technique To Improve Students’ Reading Comprehension

This research aimed to describe the use of T –chart Technique to improve students’ reading comprehension. This Classroom Action Research was conducted at the first grade students of MA NW PUTRI NARMADA with 27 students where the all of students are female. This research focus on the students reading comprehension. It consists of two cycles which is in the cycle consisting of planning, action, observation, reflecting. The data gathering used multiple choice and analyzed the data are using qualitative and quantitative approach, in the first cycle wasn’t improve students reading comprehension where the mean score of pre-test was 61 with the percentage 14% and the post-test was 69 with the percentage 33%, the result of the second cycles where the mean score of pre-test was 70 with the percentage 44% and the mean score of post-test was 86 with percentage 85%. The result of students’ achievement in cycles II with passing scores in the first were 33% (not good) and the second test were 85% (very good) indicated the target of 75 of the minimum criteria has been achieved. Based on the result of the study, it can be concluded that the use of T –chart technique to improve students’ reading comprehension at MA NW PUTRI NARMADA in academic year 2018/2019 are success
Accelerating Evolutionary Neural Architecture Search for Remaining Useful Life Prediction

Deep neural networks (DNNs) obtained remarkable achievements in remaining useful life (RUL) prediction of industrial components. The architectures of these DNNs are usually determined empirically, usually with the goal of minimizing prediction error without considering the time needed for training. However, such a design process is time-consuming as it is essentially based on trial-and-error. Moreover, this process may be inappropriate in those industrial applications where the DNN model should take into account not only the prediction accuracy but also the training computational cost. To address this challenge, we present a neural architecture search (NAS) technique based on an evolutionary algorithm (EA) that explores the combinatorial parameter space of a one-dimensional convolutional neural network (1-D CNN) to search for the best architectures in terms of a trade-off between RUL prediction error and number of trainable parameters. In particular, a novel way to accelerate the NAS is introduced in this paper. We successfully shorten the lengthy training process by making use of two techniques, namely architecture score without training and extrapolation of learning curves. We test our method on a recent benchmark dataset, the N-CMAPSS, on which we search for trade-off solutions (in terms of prediction error vs. number of trainable parameters) using NAS. The results show that our method considerably reduces the training time (and, as a consequence, the total time of the evolutionary search), yet successfully discovers architectures compromising the two objectives.
Using Electronic Platforms in Encouraging Students Towards English Language Acquisition

Electronic learning has broadened the concept of learning by moving beyond traditional methods and moving towards an environment rich in multiple sources. Electronic learning contributes to the provision of interactive materials, programs and functional curricula that benefit those who want to learn English according to their needs, goals, levels and circumstances. This paper aims to identify the effectiveness of using electronic platforms in encouraging students towards English language acquisition. A descriptive method is used to find out the study results. The researcher points out that electronic platform provides individualized learning opportunities in parallel to all students who learn English as a second language. It is realized that using these electronic means and modern technology will increase students' use of English through exchanging views with their peers, joining educational and cultural linguistic forums, and organizing meetings with other students using English. The study also clarifies that electronic platforms in their different kinds are useful and significant learning devices.
Optimalisasi Fungsi Media Sosial Sebagai Sarana Publikasi Home Learning

This study aims to analyze the optimization of social media functions as a means of home learning publications in PAUD Istiqlal Jakarta. This research is a qualitative study with content analysis based on website, data in this research was obtained from the official website of Madrasah Istiqlal Jakarta which is located in www.web.mij.sch.id. Social media data was obtained from Instagram (@kelompokbermainistiqlal, @ra_istiqlal), Facebook and Youtube (Istiqlal Jakarta Play Group, Raudhatul Athfal Istiqlal). The results showed that the management of social media platforms such as Instagram, Facebook and Youtube as a function of publications started from (1) publications of theme submissions every week, (2) publications during the online learning process, (3) publication of reports on the results of learning activities at home from parents, and (4) publications of workshop activities / seminars online. In conclusion, social media flatform becomes an important means utilized by PAUD Istiqlal Jakarta in an effort to convey information and publications about home learning. This is also done in order to maintain communication and improve the quality of distance learning (PJJ) between teachers, students and parents. &#x0D; &#x0D; Keywords: Social Media, Home Learning, PAUD Istiqlal
Youtube-Grammetry: A Novel Approach to Producing a 3D Model from High-Quality Aerial Video for Disaster Monitoring Impact

On December 4, 2021, Mount Semeru of Indonesia erupted. Many aerial videos captured the impact of the event and uploaded them to YouTube. The availability of public videos on YouTube become a motivation for this research since there is no official data about the actual size and wide of the impact. Stakeholders need to understand the complete figure of the impact of eruption for disaster recovery as well as for further education of future generations.
أثر المناخ التنظيمي في أداء موظفي الموارد البشرية في شركات التأمين الأردنية = The Impact of the Organizational Climate on the Performance of Human Resources Employees in Jordanian Insurance Companies

المناخ التنظيمي | أبعاد المناخ التنظيمي | إدارة الموارد البشرية | أبعاد إدارة الموارد البشرية | شركات التأمين الأردنية | Organizational Climate | Dimensions of Organizational Climate | Human Resources Management | Dimensions of Human Resources Management | Jordanian Insurance Companies
Drivers and barrios in using augmented reality in renovation projects - literature review

Reducing the emissions of greenhouse gases is of utter importance for the mitigation of climate change mitigation. In Sweden, the building and service sector is responsible for 21% of total greenhouse gas. Renovating existing buildings, more specifically those which were constructed before 1980, can significantly contribute to the reduction in energy consumption and emissions of greenhouse gases. Because the majority of these buildings are in need for renovation. But the energy renovation and energy efficiency-related maintenance rate in Sweden is very low due to lack of technical drawings and documentation of information about material specifications and structure systems. Adoption of augmented reality technologies can be beneficial as these technologies present digital information in the context of the physical environment. However, the level of adoption of these technologies in renovation and maintenance projects is still very low. This paper expands the technology acceptance model to evaluate determinants of users’ acceptance of augmented reality technologies in renovation and maintenance projects.
Exploring Influential Factors on Online Groceries Shopping Purchase Intentions Among Customers in Jabodetabek Area

This study applied a qualitative approach to investigate the underlying influences on consumers’ online grocery shopping from the intention generation phase to intention execution phase in the perspectives of purchase intention and the intention–behaviour gap (IBG). Research data were derived from semi-structured in-depth interviews with 10 consumers and analyzed using grounded theory. The findings identified factors that influenced intentions and the IBG in the process of consumers’ online grocery shopping. Specifically, these findings reported that perceived usefulness, perceived ease of use, perceived risk of COVID-19, social influence, and enjoyable shopping experiences were identified as major drivers for generating consumers’ online purchase intentions. Difficulty in transaction, late delivery, incomplete information, bad packaging, and difficulty with site navigation were factors triggering the gap between online grocery purchase intentions and behaviours These findings will help stakeholders build future policy and suitable strategies to better promote online grocery shopping in the Jabodetabek context.
The Practical Research of Mixed Reality for Photographic Darkroom Education

With the continuous development and progress of science and technology, the field of mixed reality applications has involved scientific research, medicine, entertainment, education, information dissemination, and people’s daily lives; This paper will focus on the application of mixed reality in the field of education and teaching, relying on the characteristics of mixed reality technology. This article will use the combination of mixed reality and smart glasses to fully consider the characteristics of photography darkroom teaching, design and produce a mixed reality photography darkroom teaching software, and explore the feasibility of the application of mixed reality in teaching. This paper will use literature research methods, practical research methods, and survey methods as the main methods of research topics to determine the importance, feasibility, and necessity of the relevant theories studied in this paper. The application of mixed reality technology in photography darkroom teaching can not only solve many problems in the existing darkroom teaching methods, but also develop and expand students’ Independent learning ability. It is concluded from this that mixed reality teaching software has the feasibility of sustainable development, which brings particular application value to the development and research of other education and art discipline software.
Graph Convolutional Networks (GCN)-Based Lightweight Detection Model for Dangerous Driving Behavior

Real-time detection and identification of dangerous driving behaviors is an effective measure to reduce traffic accidents. Due to the high network delay, limited communication bandwidth, and weak computing power, lightweight detection models that can run on edge devices have been widely investigated and attracted considerable attention. In recent years, the Graph Convolutional Network (GCN), which models the human skeleton as a spatiotemporal graph, has achieved remarkable performance, due to its powerful capability of modeling non-Euclidean structure data. However, there are disadvantages such as the single way of extracting information, high model complexity, and inability to integrate environmental information. Therefore, we propose a lightweight dangerous driving behavior detection model based on GCN. First, two local information extraction modules are designed to extract skeleton information features. Meanwhile, we propose a multi-information fusion behavior recognition model of “people $$ {+} $$ objects” by capturing the motion information of related object. Finally, the method based on Singular Value Decomposition (SVD) rank reduction is used to compress the model to improve the speed of recognizing an action sample under sufficient detection accuracy. The proposed model respectively achieves 96% and 86.3% accuracy on the x-view benchmark of NTU-RGBD dataset and the homemade Locomotive Driver Dataset, which attains the state-of-the-art performance.
The Implementation of Finite State Automata Concept in Data Integration Services Submission

The submission of Data Integration Services on regional apparatus in the DKI Jakarta Provincial Government is still processed manually. The data user proposes data integration services by attaching a data analysis requirement document addressed to the Data Producer and a copy to the data guardian. The Problems of manual submitting services are the difficulty of tracking the integration status, filling out the application data analysis form is inappropriate and incomplete, the data integration submission letter is not properly archived, and the results of the coordination betwen users and data producers are not properly documented.This study aims to design an application for submitting data integration services by applying the concept of Finite State Automata which is expected to provide convenience and benefits for data users in data integration submission, facilitate data producers in verifying data integration submission and facilitate the Department of Communication, Informatics, and Statistics of DKI Jakarta as data guardian in providing data integration services for Regional Apparatus in the DKI Jakarta Provincial Government.
Analisis Motivasi Belajar Matematika Secara Daring Pada Siswa Kelas XI SMA Negeri 1 Polokarto

The objective of this study is to analyze the motivation to learn mathematics online on class XI SMA Negeri 1 Polokarto. The method is descriptive qualitative research. The subject is class XI SMA Negeri 1 Polokarto. The data collection technique is questionnaire about online mathematics learning motivation. The results of the analysis in this study indicate that students are mostly motivated by learning mathematics online. This can be seen from the objective indicator of intrinsic orientation which has a percentage of 90.93% and the goal of extrinsic orientation which has a percentage of 73.14%.
Leveraging Multiple Representations of Topic Models for Knowledge Discovery

Topic models are often useful in categorization of related documents in information retrieval and knowledge discovery systems, especially for large datasets. Interpreting the output of these models remains an ongoing challenge for the research community. The typical practice in the application of topic models is to tune the parameters of a chosen model for a target dataset and select the model with the best output based on a given metric. We present a novel perspective on topic analysis by presenting a process for combining output from multiple models with different theoretical underpinnings. We show that this results in our ability to tackle novel tasks such as semantic characterization of content that cannot be carried out by using single models. One example task is to characterize the differences between topics or documents in terms of their purpose and also importance with respect to the underlying output of the discovery algorithm. To show the potential benefit of leveraging multiple models we present an algorithm to map the term-space of Latent Dirichlet Allocation (LDA) to the neural document-embedding space of doc2vec. We also show that by utilizing both models in parallel and analyzing the resulting document distributions using the Normalized Pointwise Mutual Information (NPMI) metric we can gain insight into the purpose and importance of topics across models. This approach moves beyond topic identification to a richer characterization of the information and provides a better understanding of the complex relationships between these typically competing techniques.
STRUCTURAL-COMPONENT CHARACTERISTICS OF THE PROSPECTIVE TEACHER’S READINESS TO FOSTER THE ENTREPRENEURIAL ATTITUDE OF JUNIOR SCHOOL STUDENTS

The aim of the paper is to present science-based approaches to structuring entrepreneurship, entrepreneurial activity, entrepreneurial competence of future experts, given which the structural components of the future teacher’s readiness to promote entrepreneurial spirit in junior school students are determined. To achieve the objective, the following research methods were used in the paper: analysis of the academic literature with regard to the issue of concern; interpretation and analytical method, synthesis, systematization, generalization. The focus is on scholarly studies that present evidence-based approaches to structuring entrepreneurship, entrepreneurial competence of the experts to-be, and entrepreneurship readiness, which are significant through the lens of the discussed issue. It is mentioned in the article that preparation of future teacher to be ready to foster the entrepreneurial attitude of junior school students is a systematic process during which the students acquire theoretical foundations of professional training based on interdisciplinary integration of knowledge, practical skills, develop ways of thinking, entrepreneurial qualities, moral and ethical values, necessary for teacher’s professional activities regarding the development of entrepreneurial attitude of junior school students. When structuring the concept of «future teacher’s readiness to foster the entrepreneurial attitude of junior school students» we consider it as a strong personal and professional feature, founded on the conscious entrepreneurial activity of students and the result of training. From this perspective, we highlight and describe the following components of the prospective teacher’s readiness to promote entrepreneurial spirit in junior school students in terms of analysis of the academic and educational literature: goal-incentive, contentknowledge, activity-reflexive. The selected components will provide the basis for defining the criteria of future teacher’s readiness to foster the entrepreneurial attitude of junior school students, conducting monitoring research on the issue under consideration.