Reviewerly/exHarmony huggingface dataset:
PENINGKATAN AKURASI PREDIKSI PENGADAAN BAHAN BAKU PRODUKSI DENGAN MENGGUNAKAN METODE NEURAL NETWORK

Forecasting or prediction in production activities is an activity that aims to predict everything related to production, supply, demand, and use of technology in an industry. In the end, this prediction is often used by companies and operational management to make plans related to their business activities in certain periods. As a tool for measuring the level of predictions that are close to good accuracy which can be used as a reference for calculating a business process in the future, companies also need an accurate and tested measuring tool based on the type of estimate itself. The NEURAL NETWORK method with backpropagation calculates a pattern based on the history of several periods that have occurred. This method is often used to obtain prediction accuracy in forecasting activities. Inaccurate packaging stock inventory forecasting to support production needs causes the inventory space to exceed capacity and the production process is disrupted, so the selection of an appropriate forecasting method is needed. The use of the NEURAL NETWORK method with backpropagation to increase the accuracy of the prediction of the procurement of packaged goods in this study is very suitable. Results of Data Training with input data for begin stock, consumption, incoming, and safety stock and target data is the stock order yields the best MSE value of 0.03603642 on the number of neurons 11 with an epoch value of 1000 and a maximum error limit of 6, so that the test data resulted in the accuracy of the MAPE value of 0.52%.
Empowering Identity among English Teachers in the 4.0 Industrial Revolution: Perspectives from Tomini Bay

This paper discusses the issue of foreign English language teachers in the Tomini Bay area in Indonesia. Utilizing several theories such as the theory of empowerment and agency as well as teachers' identity development, this qualitative research presents a study with the interview data from 10 teachers who live and teach in the Tomini Bay area. The data were analyzed by coding the interview materials into several main areas of interest. From this, several themes emerged for discussion that seemed to be influential and contribute to understanding teachers and their experiences in the language teaching context. The study reveals that teachers' views of their remuneration, their views of teaching in this technology era and pandemic situation, and their views of local potential teaching resources are significantly different from teachers who are classified as 'empowered identity' than those who are not in the category. However, the necessity of government intervention in English language teaching success in their area emerges as a crucial factor viewed by all the 10 teachers' recollections. It is hoped that this paper discussion can reveal factors that should be considered in a model offered to develop EFL teachers and their identity development in the Tomini Bay area, which later affects the success of English teaching in the surroundings and subsequently impacts English language teaching success in Indonesia.
Understanding the effects of negative (and positive) pointwise mutual information on word vectors

Despite the recent popularity of contextual word embeddings, static word embeddings still dominate lexical semantic tasks, making their study of continued relevance. A widely adopted family of such static word embeddings is derived by explicitly factorising the Pointwise Mutual Information (PMI) weighting of the co-occurrence matrix. As unobserved co-occurrences lead PMI to negative infinity, a common workaround is to clip negative PMI at 0. However, it is unclear what information is lost by collapsing negative PMI values to 0. To answer this question, we isolate and study the effects of negative (and positive) PMI on the semantics and geometry of models adopting factorisation of different PMI matrices. Word and sentence-level evaluations show that only accounting for positive PMI in the factorisation strongly captures both semantics and syntax, whereas using only negative PMI captures little of semantics but a surprising amount of syntactic information. Results also reveal that incorporating negative PMI induces stronger rank invariance of vector norms and directions, as well as improved rare word representations.
SOE classification according to orientation and size

In Bulgaria, Chile, France, Greece, the Netherlands, Peru and Sweden, all SOEs are classified as commercially oriented (i.e. they operate in open market competition, and must be profitable and efficient), regardless of the nature of their objectives. However, in Greece, SOEs which may serve a public policy are funded in part or in whole from the state budget. Information is not available for Australia, Austria, the Slovak Republic and Spain.
Performances of Crypto, Market Indexes, and Gold Before and During the COVID-19 Pandemic: A Comparative Analysis

Research aims: This study aims to investigate empirical evidence of a comparison of investment instruments, including Bitcoin, Indonesia Composite Index (ICI), and gold, before and during the COVID-19 pandemic.Design/Methodology/Approach: Analytical methods employed comparison study using secondary data. The Microsoft Excel program was utilized to calculate formulas for each variable. Then, data were statistically processed using the SPSS application, i.e., independent sample test, testing for differences. The sample used in this study was the closing price of Bitcoin, the price of the ICI, and the price of gold, with monthly data from the beginning of January 2018 to the end of December 2021, to demonstrate a significant difference between the risks of Bitcoin, ICI, and gold before and during the COVID-19 pandemic.Research findings: The hypothesis test results revealed that before the COVID-19 pandemic, the investment risk of ICI and gold was the lowest, with a significance level of 0.000 (0.0000.05) on a different t-test at a 5% significance level. Thus, there was a significant difference in investment risk between ICI and gold. Meanwhile, during the COVID-19 pandemic, the risk of investing between Bitcoin and the ICI was the lowest, with a significance level of risk of was 0.000 (0.000 0.05) on different tests at the significance levels of 5%. In short, there was a big difference in investment risk between Bitcoin and the ICI.Theoretical contribution/Originality: This study provides additional literature on decision-making, especially on risk.
Lampung Language Subjects in Various Curriculum Contexts and Learning Paradigm

Lampung language as one of the subjects that are in local content taught in educational units has experienced a dynamic development. One of the components developed in the element of education is the curriculum. The curriculum is a reference for the implementation of the teaching and learning process in all educational units for all subjects. Lampung language is one of the regional languages in Indonesia and has been taught by the local government of Lampung Province since 1975. The focus of teaching the Lampung language is on linguistic elements in which there is literacy, culture, and literature. The development of the learning paradigm that is attached to each curriculum becomes a reference that every educator needs to study so that the learning mission can be achieved optimally. The research method used in this research is descriptive qualitative. The purpose of qualitative description descriptive is research that is used to examine natural objects to describe, describe, explain, explain, and answer in more detail the problems to be studied. For the Lampung language subject, the implementation has elements of specific learning and teaching principles. It consists of, the context of language learning, language skills, strategies to grow language acquisition, and language skills. So whatever the curriculum development and learning paradigm, Lampung language learning still puts forward the four principles of language learning and teaching.
Transformations in the Translation of Hard and Soft News Reports into Arabic

This study examines local transformations as a translation strategy of the news report genre from English into Arabic. It analyzes the frequency of deletion, substitution, addition, and reorganization to identify any relation between applying these transformations and news topics. This is achieved via a textual analysis of a parallel corpus of 60 texts of hard and soft news reports in English and Arabic derived from two sources: the Reuters (news agency) and BBC (news broadcaster) websites. Results show that deletion is by far the most frequently used transformation in both soft and hard news. Transformation frequencies are discussed in relation to the structural elements of news reports. .
Pupil Detection Using Hybrid Vision Transformer

Pupil detection is an indispensable part of the process of eye-tracking. Due of the limitation of existing methods on pupil image quality, we propose a pupil detection method using vision transformer with a hybrid structure. We first extract the local features of the image with CNN, and then obtain the global dependence through the encoder of the transformer, to excavate more accurate information on pupil position. We trained and tested the proposed model on 10 600 images from three publicly available datasets and compared with other pupil detection models. The analysis of the outcomes demonstrated that the hybrid vision transformer was superior to these comparison approaches in terms of accuracy and robustness in locating the pupil position. It achieved a detection rate of more than 90% for pupils within a 5-pixel error in all evaluated datasets.
A meta-design research project to enhance the user experience of university's digital services ecosystem

Digitalisation is essential in contemporary institutions.Politecnico di Milano started to re-think its digital services to design an application that could help students manage every aspect of their daily university life, starting from their own goals and unmet needs, while considering the complexity of the university system.The Meta-Design approach was adopted to redefine a public university's digital services, assuring the users' centrality in the research and design process.Meta-Design is a circular and reflective method that enables the designer to continuously provide innovative solutions, updating the product to the ever-changing user needs.This methodology is on the basis of User Experience practice.This paper demonstrates how Meta-Design and its pillars -'user research', 'market analysis', and finally 'technology investigation'led to the ideation of an innovative and proactive concept for a mobile app where students are the protagonists.
Analysis of Facial Expression Recognition Using LBP and Haar-Cascade Classifier

Facial expression recognition is the main factor in human communication that helps us to understand the intension of other emotions.This paper is going to relate human emotions such as anger, happiness, neutral, sad, surprise, disgust.In order to recognize facial expressions from the machines we employed some techniques called local binary pattern (LBP) for face recognition, the algorithm used here is local binary pattern histogram (LBPH), and for detection of face Haar-cascade classifier is used.With this work, the expression of the respective image will be reported, and it will also notify time taken for training an image.A small change in facial expressions signifies lighting, orientation and background.Here the LBP technique is intended only for the purpose of extracting features and Haarcascade classifier is being utilized for the extracted features from LBP.The dataset is used for the purpose of testing and training of the images.
Camera-on/camera-off: Visibility in the design studio

What constitutes, defines or bounds the 'studio' in architecture education when it is wholly online?The design studio contributes to a very particular spatial construct in proximal teaching, one that has been challenged during the pandemic as educators have adopted distance and online learning and teaching.This paper presents a brief history of the design studio in architectural education and speculates about three dimensions of visibility therein.It contextualises the design studio against the broader higher education experiences of teaching online during the Covid-19 pandemic, in particular so-called 'Zoom anxiety' and 'Zoom fatigue' experienced by teachers and students.The paper explores how the visibility of teacher and student in the studio conspire in the reproduction of inequity and precarity in higher education, while also raising questions about students' agency in disabling their cameras in online teaching.
Hybrid Project-Based Learning course approach from face-to-face and remote experiences.

The Covid-19 pandemic challenged students and educators who quickly migrated face-to-face courses to a remote context. Given this challenge, this paper documents the experience of a Project-Based Learning course originally proposed to a face-to-face and adjusted to the remote context. It is a wearable computing course centralizing on mixed reality technologies and user studies evaluation. The adopted methodology is student-centered based on PjBL practices, emphasizing the Human-Computer interaction subject was applied six times, three times face-to-face, and three times remotely between 2019 and 2021. This paper describes the educator's experiences, learnings, and directions for the arrangement of other PjBL courses.
Factors Influencing Job Satisfaction of Nurses in Cardiac Center, Hail, KSA

Background: The present healthcare organizational landscape is experiencing a myriad of issues that have resulted in more and more nurses quitting. Job satisfaction is defined as the employees' feelings and behaviors towards their job. The healthcare system of Saudi Arabia is composed of considerable numbers of expatriate nurses from different countries, bringing about diversity. Compared to the past data, there has been an increment in the rate of nurses quitting, meaning a reduction in job satisfaction. This study determines the factors influencing job satisfaction among nurses working in Cardiac Center Hail in Saudi Arabia. Methods: The study utilized a retrospective study based on prospective data collection focusing on the nursing staff's responses to the staff satisfaction survey in Cardiac Center Hail (CCH). The convenience sampling technique of data collection was adopted since it is incredibly prompt, economical, fast, less sophisticated, and easy to research. This method is random and hence eliminates bias in the research. The data collection process utilized inclusion criteria to ensure high quality and reliable data s obtained. Results: It can be observed the job satisfaction in the Cardiac Center Hail is average since the highest percentage of job satisfaction scores ranges between being average and very good for most of the influencing factors. The most dissatisfying factor in the institution was the food supply, followed by the communication system, transportation, and working hours. Conclusion: This information is critical for utilization by policymaking in developing long-term sustainable strategies for promoting a higher retention rate of nurses through offering favorable conditions to promote health care quality deliverance. . Improvements include allocating allowances, reducing the workload on the nurses by maintaining the required shift time, compensate on overtime, improve the communication system, food should be properly cooked, fresh, and balanced, reduce congestion in accommodation &amp; provide appropriate accessories, and establish proper and reliable transport system.
PELATIHAN TUNE UP SEPEDA MOTOR SEBAGAI PENINGKATAN KOMPETENSI PRAKTIKAL SISWA PADA WILAYAH ULAPAN (UBUD, TEGALALANG, DAN PAYANGAN) UNTUK MENDUKUNG KAWASAN STRATEGIS PARIWISATA NASIONAL (KSPN)

This Community Service Activity Motorcycle Tune Up Training aims to improve the practical competence of students at SMKN 1 Tegalalang so that they can tune up motorcycles effectively, efficiently and safely, including: checking, maintaining, repairing and adjusting motorcycle parts/systems according to the Tune Up procedure, and has an outcome in the form of increasing scientific competence, especially regarding engine parts, electrical parts, and motorcycle chassis parts. The method of this activity is to conduct training for students in grades 10, 11, and 12 of the Automotive Department at SMKN 1 Tegalalang. Training in the form of providing materials and practice in the field with a percentage of 30% for material and 70% for practice. The basis of doing Tune Up on a motorcycle is that every motorcycle that is operated, will eventually experience a situation where the parts of the motorcycle (engine, transmission, frame, etc.) experience fatigue and wear and tear, thereby reducing its performance, including: engine power decline, slow acceleration, wasteful fuel and the possibility of continuing/spreading damage to other component damage and to support the national tourism strategic area (KSPN) especially the ULAPAN area (Ubud, Tegalalang and Payangan) in order to increase the economic factors of the region. This activity was carried out in collaboration with the Bali Land Transportation Polytechnic with SMKN 1 Tegalalang. The result of this Community Service activity is an increase in the practical competence of SMKN 1 Tegalalang students so that later they can be used as provisions to set up a workshop business (MSME level) or work
With or without emoji? The effect of emoji on risk perception and preventive behaviors in health information

For nearly a decade, emoji have been widely used as a substitute for nonverbal clues in computer mediated communication (CMC), especially in social media.Although the use of emoji in health communication via social media is becoming pervasive, the influences of using emoji in health information on information receivers' perceptions and behavior has not been fully studied.In order to discover these influences, this study collected 210 responses as a set of evaluation of self-statement questionnaires online during the COVID-19 period in Taiwan in 2021.It adopted a 2 (information with emoji vs. without emoji) X 2 (official vs. unofficial sources of information) between-subject design to examine and respond to the research questions.The results verified the enhancement effect of the use of emoji in health information and the moderation effect of the information source.In this emoji condition, health information leads to a higher level of risk perception at receivers.It also enhances the receivers' preventive behavior intention.This experiment revealed an interaction effect between emoji and information source on preventive behavioral intention, namely that emoji work better on health information issued by unofficial organizations.The results provide indications and suggestions for how and when to use emoji effectively to design and deliver health information.
THE EFFECTIVENESS OF USING CLUSTERING TECHNIQUE TOWARD WRITING PROCEDURE TEXT

This research was conducted to measure the effectiveness of cluster techniques in writing text procedures from students as students of Roudlotun Nasyiin Mojokerto. The researcher uses quasi experimental research for design. This design involves two classes as research subjects, the experimental class and the control class. These classes have similar abilities in English achievement. The researcher gave experimental treatment in treatment class and the researcher gave control treatment in control class. After doing the treatments in each class, the researcher gave post-test. The post-test scores in each class will be compared to measure the impact of doing these treatments. There are two variables in this research, independent variable and dependent variable. Independent variable is clustering technique and dependent variable is writing achievement. This treatment is given during some meeting before taking the data. The research result students’ ability in writing after taught by using clustering technique was very good. In short, clustering technique was an appropriate strategy to write a text, especially procedure text. The writing students’ ability taught by using non- clustering technique was lower than the students were taught by using clustering technique. The result of t-test was 7,153. After got the score, the researcher compared it with t- table (df = n1 + n2 – 2 = 72 ; significance 5% = 0.05). The value of t-table was 1.666. It signed that Ha was accepted and H0 was refused.
THE IMPLEMENTATION OF AUTONOMOUS ONLINE LEARNING TO ENHANCE ACADEMIC WRITING COMPETENCE DURING COVID-19 PANDEMIC

Autonomous learning during covid-19 pandemic situation becomes the best strategy to perform an effective learning process. Particularly, autonomous learning in academic writing course requires great deals of students’ willingness to manage their time and ability. This paper is a content analysis which aims to analyze the implementation of autonomous learning strategy. Descriptive qualitative method was used to investigate and describe how 20 higher education students managed their time and ability as well as to find out the obstacles. In collecting the data, the researchers used questionnaire and interview. Students had implemented autonomous learning in various ways. They practicedwriting independently by completing the tasks and assignments given by the lecturer. They also used internet to find sources such as online translator, education websites, and explanation videos on YouTube. Some obstacles were occurred during autonomous online Academic Writing due to some reasons; such as; 1) poor internet connection, 2) lack of competence in understanding academic writing materials through online learning which needs more effort such as creating group discussion among classmates, 3) weakness in building keywords when they tried to search terms used in Academic Writing course.
Business analytics for social goods

A recommender system employs an information filtering technology aiming to recommend items that are likely to be of interest to users, based on user behavior, rating feedback of items, or item characteristics. The cold-start problem occurs when the recommender system has difficulties in drawing any recommendations due to lack of information. In this paper, we focus on the item cold-start problem. When new items are added to the catalogue, they can easily be overlooked because no feedback information is accessible for recommending them to users, impeding the promotion of new products online. We propose a hybrid recommender system, called ALFNCF (Attribute Latent Features with Neural Collaborative Filtering), which combines the advantages of collaborative filtering, content-based filtering, and neural network technologies, to address the item cold-start issue. Like collaborative filtering, ALFNCF considers the interaction between users with similar behavior and items with similar feedback, while it also takes into account the influence of user’s and item’s attributes on individual behaviors. As in content-based filtering, attribute information is used in ALFNCF to establish links between new and old items. ALFNCF not only can retain the linear interactions between users and items, but also can learn the non-linear interactions by neural network units. Through the training on users’ past rating feedback information for old items, ALFNCF can predict the user’s ratings for new items. Experimental results show that our proposed method is effective and superior to other methods in the promotion of new items.