Reviewerly/exHarmony huggingface dataset:
A STUDY ON TEACHERS’ STRATEGIES IN MINIMIZING STUDENTS’ SPEAKING ANXIETY AT 11th GRADE SMAN 2 TEMBILAHAN

The problem of this research was students’ speaking anxiety seems high. Therefore, the purpose of this research is to know “what teachers’ strategy in minimizing students’ speaking anxiety at the second grade of SMAN 2 Tembilahan are”. This research was descriptive quantitative research. The researcher was distributing questionnaires and interviewing two English teachers as samples to know their strategies in reducing students' speaking anxiety. The sample was taken by using total sampling because there are only two English teachers there. After collecting the data, the researcher found that teachers use many teaching activities to help students' anxiety problems. They used many teaching activities, such as small group work, pair work, simulations, and structure exercises. Besides, the teachers also motivate students to be positive thinking in learning English.
The Impact of the TPS System Application on Increasing Higher Education Institutions Performance Efficiency Case study: Luminus Technical University College

This study aimed to examine the extent to which the TPS model can be applied and used to improve and increase Luminus Technical University College's performance efficiency as one of Jordanian higher education institutions. To achieve this goal, a questionnaire was prepared according to study objectives and hypotheses. The study population consisted of academics, managers, departments heads, and technicians at Luminus Technical University College. A random sample consisting of 150 respondents was selected. The study used the descriptive-analytical approach. The study concluded that there is a possibility to implement the TPS model to improve performance efficiency at Luminus Technical University College. The study recommended that Jordanian higher education institutions have to pay attention to using and implementing the TPS model due to its impact on improving performance efficiency at Luminus Technical University College and similar colleges in the Jordanian higher education environment.
Stampel Flash Bagi UMKM Percetakan

UMKM need to increase their productivity through technology upgrades, so that the production process becomes more effective and efficient. This community service partner is UMKM printing "Giga" with the aim of this service activity is to increase partner productivity through the application of technology, namely upgrading one of the products, namely wood stamps into flash stamps. The problems faced by partners are the low management of business management and the unpreparedness of resources in facing technological changes so that businesses are managed conventionally and traditionally. The method of this service activity is to use technology guidance, training on making flash samples and mentoring business management. The output of this activity is sample flash products, increased income, as well as national seminars and publications through scientific articles in the form of dedication proceedings or journals.
THE EFFECT OF COLLABORATIVE WRITING TECHNIQUE ON STUDENTS WRITING ABILITY AT THE EIGHTH GRADE OF SMP NEGERI 8 PEMATANGSIANTAR

Writing is the difficult skill to master that is why exercise regularly is needed. The objective of this study is to figure out the improvement on students to write descriptive through collaborative writing technique. This experimental research was carried out in SMP Negeri 8 Pematangsiantar in the academic year of 2019/2020. The research design of this study is classroom action research with quantitative approach. The population of this study is all students grade eight at junior high school, they are 296 students were divided into ten classes. And as a sample of this study consist of 25% from the population were VIII-4 as the experimental group and VIII-7 as the control group. Each group consists of 32 students. The experimental group was treated by using Collaborative Writing Technique, while the control group was treated by using Direct Instruction. The finding of this research are the score pre-test in control group are 1376 where the mean is 43 and in experimental group 1529 where the mean is 47.78. The mean score of different in control group is 23.21. and the t-test is 5.10. The standard deviation of the data in control group is 11.70 and the effect size in teaching writing descriptive text in control group is 1.98. It means that the students ability is low. The students’ score post-test in control group are 2119 where the mean is 66.21 and in experimental group are 2409 where the mean is 75.28. The mean score of different in experimental group is 27.5 and t-test for experimental group is 5.27. The standard deviation of the data in experimental group is 13.29 and the effect size in experimental group is 2.35. It means that the students ability is high.The data analysis shows the following findings: (1) Collaborative Writing Technique is more effective than Direct Instruction in teaching writing; (2) students with high creativity have better writing ability than those having low creativity; (3) there is an interaction between teaching techniques and creativity in teaching writing.
Integrated Unified Crime Information Management System

Crime detection, investigation and prosecution are usually carried out by the various law enforcement agencies saddled with such responsibilities. In this study, an integrated web based unified system was developed and implemented for the five (5) agencies (Nigerian Police Force, National Drug Law Enforcement Agency, Economic Financial Crime Commission, Independent Corrupt Practices Commission, Department of State Services) to enhance domiciliation of crime data into one system for effective information sharing among the five agencies. The methodology adopted for the system design is Object Oriented Analysis and Design Methodology (OOADM) and the tools used are HTML, CSS, JavaScript, MySQL. The result obtained shows that with the integration of the five agencies, accurate records of suspects and victims were timely shared by the various agencies. There is also an effective collaboration among the various agencies in crime detection, investigation and prosecution of suspects.
Large area quantitative EDS mapping for automated mineralogy using ZEISS Mineralogic

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Pengembangan Aplikasi E-Form Daftar Seleksi Bahan Perpustakaan di Perpustakaan Nasional RI

Library material selection is one of the main tasks performed by librarians at National Library of Indonesia in the implementation of library collection development. Compilation of library material selection list, especially foreign monographs, performed by librarians often results in diverse format, incomplete fill in bibliography description, inaccurate pricing, less effective and efficient in the process. It is caused by no standard format in compiling of foreign monographs library material selection list assigned as reference for librarians. This research uses software engineering approach to produce e-form application prototype of library material selection list. Data is collected by interview with stakeholders. Development of e-form application of library materials selection list was designed according topredefined standard format. This research has succeeded in developing application that can improve effectiveness and efficiency in compiling library material selection list, therefore the next workflow, acquisiton of library collection in National Library of Indonesia, can be achieved quickly, precisely, and accurately.
Developing a Digital Technology System to Address COVID-19 Health Needs in Guatemala: A Scientific Diaspora Case Study

Scientific diasporas are organized groups of professionals who work together to contribute to their country of origin. Since the start of the COVID-19 pandemic in 2020, scientific diasporas around the world have focused their efforts to support the public health response in their countries of origin. As the first cases of COVID-19 were reported in Guatemala in March of 2020, a team of four Guatemalan nationals, residing abroad and in-country, started collaborating to tackle COVID-19 misinformation and issues with healthcare services navigation. Their collaboration was facilitated by FUNDEGUA, a Guatemalan nonprofit, which provided a legal framework to establish partnerships and fundraise. The team created a digital technological system called ALMA (Asistente de Logística Médica Automatizada in Spanish). A female character named ALMA was created to personify the digital information services, through social media profiles, an interactive website, a free national multilingual call center, and an artificial intelligence-based chatbot. More members joined the nascent interdisciplinary diaspora through professional/personal references or social media. ALMA provided a platform for Guatemalan nationals to contribute with their skillset to their country during a global crisis through flexible schedules and short- or long-term involvement. As the team grew, the services for query resolution and information dissemination expanded as well. The ALMA initiative shows that scientific diasporas can provide an avenue for professionals to contribute to Guatemala, regardless of their residence and job commitments.
Use of Multilayer LSTM Neural Network in the Process of Printed Texts Recognition

The purpose of the article is to study, analyze and consider general problems and prospects for the development of printed text recognition systems based on the use of neural networks. The research methodology consists in methods of semantic analysis of this subject area’s basic concepts (recognition systems of printed texts). Approaches to the development and operation of recognition systems based on neural networks are considered. The scientific novelty of the research is the development of its own approach to text recognition based on neural networks, the results of which were used in the development of its own system of print recognition. Conclusions. The paper considers the well-known views on pattern recognition on the example of printed texts and analyzes modern approaches to the use of neural networks and their training. Taking into account the results of the analysis, the authors decided to develop a system for recognizing the languages of printed texts using learning neural networks.
PROJECT-BASED LEARNING PADA RANCANGAN PENGELOLAAN PERSEDIAAN DI TFME POLITEKNIK NEGERI BATAM

The purpose of this study is to provide a design for inventory management at the Teaching Factory Manufacture Electronics (TFME) Batam State Polytechnic with a Project-Based Learning (PBL) review. In addition, this study also applies inventory recording in the second basic financial accounting course (AKD2). This study uses qualitative methods with exploratory and descriptive research classifications. The method of collecting data in this research is by direct interviews with the informants. Researchers also made direct observations in the field and collected the necessary data from the main data sources. The results of this study indicate the importance of managing inventory in TFME, one way of managing inventory is by making an inventory card. The inventory card design that has been made is expected to be able to control inventory and the inventory card is designed to be very easy to use, for the use of an inventory card, consistency is needed from all parties involved &#x0D;
A Compliance Mechanism for Planning in Privacy Domain Using Policies

As more and more applications relying on the use and processing of personal data grow, privacy protection is becoming increasingly important. With the enforcement of the GDPR, such applications must guarantee compliance with the obligations set forth. Integrating a compliance checking mechanism with AI methods is helpful to fulfill this requirement. Toward this end, we investigate the GDPR automatic compliance checking using a planning system including personal data and an agent with actions that process data. We propose a modular framework that is capable to generate possible plans (sequence of data processing) to satisfy a given goal state, check the compliance of the plan with GDPR regulatory constraints, and provide explanation of missing obligations in case of a non-compliant. We use Answer Set Programming(ASP) and event calculus formalism to model the planning problem and make use of SPECIAL policy language as an existing work to translate GDPR requirements into ASP.
THE STUDENTS “ERRORS IN PRONUNCIATION OF THEENGLISH CONSONANTS AT THE ELEVENTH GRADE OF SMA SWASTA ERLANGGA PEMATANGSIANTAR

The purpose of this research is to find out the students’ Errors in Pronunciation the English Consonants at class XI grade of SMA Swasta Erlangga Pematangsiantar. This research was conducted at SMA Swasta Erlangga Pematangsiantar. The researcher used qualitative approach with content analysis method. Then, population in this research is the eleventh grade students of SMA Swasta Pematangsiantar that consisted of 2 classrooms which consists of 30 students. The result of this research was the researcher’s found the students’ Errors in Pronunciation of the English consonants namely: The english consonants /d/, /t∫/, /j/, /t/, /s/, /ƞ/, /l/, and /r/. The English consonants errors /d/ is 60 (15,38%), /t∫/ is 50 (12,82%), /j/ is 52 (13,33%), /t/ is 92 (23,58%), /s/ is 47 (12,05%), /ƞ/ is 45 (11,53%), /l/ is 39 (10%), and /r/ is 5 (1,28%). Based on the data analysis that the dominant errors in pronunciation the English consonants is /t/ 92 (23,58%), it could be happen because the students did not read seriously, they have little desire to learn English, they don’t have confidence, they get bored easily, and the students are afraid to be wrong
IMPROVING THE STUDENTS’ READING COMPREHENSION BY USING COMIC STRIPS AT SMA MUHAMMADIYAH-7 SERBELAWAN GRADE XI

This Research entitled improving the students’ reading comprehension by using comic strips at SMA MUHAMMADIYAH-7 Serbelawan. It concerned with the problem: Does comic strips effective to improve students’ reading comprehension through narrative text at the eleventh grade of SMA MUHAMMADIYAH-7 Serbelawan?. To answer the research problem, some theories are used: Kligner, Vaughn &amp; Boardman (2007), to Patel and Jain (2008), Snow (2002), Arikunto(2009,2010). Reading is basic skills which should be studied are speaking, listening, reading and writing and a process of looking at series of written symbols and getting meaning from them. Comic strips is some series of drawing that tell a story and drawings interrelated panels to display brief humor or form a narrative often serialized with text in balloons and captions and with the comic strips can improve reading comprehension of students in English. This research is designed into quantitative research by following experimental design of control class and experimental class. The population is 216 students and the sample is taken by using cluster sampling technique so that the sample is 72 students. The research subject is XI IPA1 as experimental class and XI IPA2 as control class of SMA MUHAMMADIYAH-7 Serbelawan. Research instrument is multiple choices. The data analysis is started from scoring the students’ answer sheet, tabulating students’ pre-test and post-test scores, calculating the standard deviation pre-test and post-test scores. Based on the data analysis, it was found before the treatment of using comic strips, value pre-test was 1904 and mean (average) was 52,88 in post-test get value was 2132 and mean (average) was 59,22 and the standard deviation pre-test was 10,20 and post-test was 10,01. get value pre-test was 1972 and mean (average) was 54,78 in post-test value was 3004 and mean (average) was 83,45 and the standard deviation pre-test was 6,91 and post-test was 6,93. Using comic strips effective in improvingstudents’ reading comprehension through narrative text at the eleventh grade of SMA MUHAMMADIYAH-7 Serbelawan. The t-table value is on the amount sample (n) 72 subtracted 2 then the number of sample will be 70 which the value of t-table was 1,99. Then, result was df(degree of freedom) =70. So, the t-test result was than 5,73&gt; 4,22 &gt;1,99. It can be concluded that result of experimental class more of control class result that the researcher was accepted
An Extensive Result Analysis of Extracting Movement Patterns Using Fuzzy and Neuro-Fuzzy Methods

Several applications, including vehicle navigation, fleet management, animal tracking, and mobile phone tracking, create significant amounts of data about movement. To keep up with the ever-increasing amounts of movement, these apps need more assistance. Data it is essential to know how a thing travels in both space and time in order to understand it construction of a model for the object's movement. Objects of all shapes and sizes are constantly changing. In flux, as do their relative inclinations. The capacity to rationally evaluate shifting ideologies Thus, the movement of things across time is critical. Descriptions of a creature's motions it is necessary to provide explanations of the patterns that an item displays throughout time and place. With every step, several different patterns may be seen in the item, some of which are repeated but not exactly. Like a scavenger animal or a delivery vehicle navigating the streets of a metropolis. Even Despite the fact that their movement patterns aren't identical, they're not wholly unlike either. Even if the routes of the moving items are quite similar, they may visit the same places. Over time in different settings. Fuzzy techniques are discussed in this study.
Movie Recommendations Based on Emotions Using Web Scraping

Abstract: A recommender system help the users to get personalized recommendations, helps users to take correct decisions in their online transactions, increase sales and redefine the users web browsing experience. The purpose of this project is to recommend a list of movies for a user based on a specific emotion to suit his/her needs and desires. This recommendation system can be achieved through web scraping. Web Scraping is an automatic method to obtain and extract content and large amounts of data from websites. This recommendation system can also provide insights to current movie trends and latest people’s favorites.
implementation of referral system in postpartum hemorrhage cases by midwife

Postpartum hemorrhage (PPP) is the most significant contributor to maternal mortality worldwide, accounting for 50-75% of all emergency cases that occur during childbirth. Research on the causes, knowledge, prevention, and factors that influence the incidence of postpartum hemorrhage has been carried out previously. However, research on the referral system in postpartum hemorrhage cases done by midwives has not primarily been explored. PRISMA results showed that there were 95 articles obtained from three databases. Article selection was carried out based on predetermined criteria for inclusion and exclusion. This research has acquired five related articles. The seven articles obtained were analyzed for their critical appraisal using the Joanna Briggs Institute (JBI). This study aims to identify the in-depth literature obtained through various sources with various research methods related to the topic, which is the implementation of the referral system in primary postpartum hemorrhage done by midwives of health centers. Therefore, identifying gaps from the existing articles or synthesizing evidence through different studies can be done. Then sources of evidence that provide reference information and research on postpartum bleeding can be found.
Fake Review Detection on Using Machine Learning on Online Product Selling Platform

Abstract: The increasing popularity of online review systems motivates malevolent intent in competing sellers and service providers to manipulate consumers by fabricating product/service reviews. Immoral actors use Sybil accounts, Bot farms, and purchase authentic accounts to promote products and vilify competitors. Facing the continuous advancement of review spamming techniques, more research work is been carried out to assess the approaches explored to date to combat fake reviews, and regroup to define new ones. Fake reviews detection attracts many researchers’ attention due to the negative impacts on the society. Most existing fake reviews detection approaches mainly focus on semantic analysis of review’s contents. This project is aimed at fake review detection in online platform, to prevent damage due to deceptive reviews.We propose a Novel Fake Reviews Detection based on Logistic Regression technique
An Efficient Book Reading Mechanism using Deep Learning

Abstract: The importance of reading books and novels has evolved notably with the advancement of information and technology. The relationship among characters in a novel tells an important part of the story. Great novels usually have large and complex character relationship networks due to the number of characters and story complexity. However, with the fast-changing world, people do not get time to read complete books and novels. So, identifying and categorizing the important part of the books, we plan to propose an efficient mechanism based on neural networks, semantic analysis and deep learning which will enable readers to instantly get information about their favourite books.
Identifying Spam Activity on Public Facebook Pages

Since their emergence, online social networks (OSNs) keep gaining popularity. However, many related problems have also arisen, such as the use of fake accounts for malicious activities. In this paper, we focus on identifying spammers among users that are active on public Facebook pages. We are specifically interested in identifying groups of spammers sharing similar URLs. For this purpose, we built an initial dataset based on all the content that has been posted upon feed posts on a set of public Facebook pages with high numbers of subscribers. We assumed that such public pages, with hundreds of thousands of subscribers and revolving around a common attractive topic, make an ideal ground for spamming activity. Our first contribution in this paper is a reliable methodology that helps in identifying potential spammer and non-spammer accounts that are likely to be tagged as, respectively, spammers/non-spammers upon manual verification. For that aim, we used a set of features characterizing spam activity with a coring method. This methodology, combined with manual human validation, successfully allowed us to build a dataset of spammers and non-spammers. Our second contribution is the analysis of the identified spammer accounts. We found that these accounts do not display any community-like behavior as they rarely interact with each other, and are slightly more active than non-spammers during late-night hours, while slightly less active during daytime hours. Finally, our third contribution is the proposal of a clustering approach that successfully detected 16 groups of spammers in the form of clusters of spam accounts sharing similar URLs.