Reviewerly/exHarmony huggingface dataset:
PROTOTYPE SMART INSTRUMENT UNTUK KLASIFIKASI PENYAKIT HIPERTENSI BERDASARKAN JNC-7

High blood disease or famous to known as hypertension almost 95% the cause is very difficult to know. One way to know the condition of our health is by checking routine to the nearest clinic or hospital. Hypertension is one of the risk factors for dangerous diseases, such as stroke, heart attack, and kidney failure. Hypertension can cause high morbidity (pain) and mortality (death), hypertension is often called silent killer disease. People with Hypertension rarely show early symptoms, and their recognition is usually through screening, or when seeking medical treatment for unrelated health problems. The cause factors of hypertension include weight and height, body fat, and alcohol levels inside of body. To know the condition of body to hypertension need a monitoring system and use tool tensimeter. In this research has been made the means of detecting factor symptoms of hypertension. After the measurements are done by each sensor then the data is processed by Arduino Microcontroller to be processed to computer via serial port (USB). On the computer data that has been sent will be processed using decision tables with databases obtained from experts, the resultin a decision will give classification of hypertension and non-pharmacological management.
School Libraries and Social Networks

After a brief introduction to social networks, considered as one of the key tools of web 2.0, the paper deals with the possible uses of social networks and social network applications by school libraries. Social networks are widely used by students, and the range of tools available (or to be implemented) within social‐networks is steadily growing. Among them, of special interest for school libraries are 'social reading' and content sharing applications. The paper advocates an active use of social network tools and applications by school libraries, and contrasts such an active use with the simple ‘placeholder’ pages usually implemented both by school and by university libraries. Web 2.0, social networks, social reading, school libraries
Penerapan Model Geographically Dan Temporally Weighted Regression Pada Kecelakaan Lalu Lintas

Geographically and temporally weighted regression (GTWR) is a model that is used to deal with instability in data both spatially and temporally and to produce local parameters. In this paper, The GTWR model is used to analyze the factors that are thought to significantly influence the number of traffic accidents in Mempawah Regency. The data used in this study came from 8 districts with the variables used were the number of traffic accidents, the number of population (gender ratio, length of damaged road conditions, and percentage of adolescence. The parameter estimation of the GTWR model was obtained using the weighted least square (WLS) method. The optimal bandwidth selection uses the Cross-Validation (CV) method and the weighting used is the Fixed bisquare function. The results of the analysis show that using the GTWR model, it was found that only the population size variable significantly affected the number of traffic accidents in all locations in Mempawah Regency from 2015 to 2018. The GTWR model was known to be better than the multiple regression model because it produced smaller AIC and RSS values and a larger R-square value.
Information System On Employee Payment At Smk Islam Sabilal Muhtadin With Java And Mysql

Islamic Vocational High School (SMK) Sabilal Muhtadin Is One Of The Private Vocational Schools That Uses Islam As The Main Guideline For Religious Education But In The Process Of Calculating Employee Payrolls, It Is Still Manual Using A Calculator. This Is What Makes SMK Islam Sabilal Muhtadin Also Need A System That Can Manage The Data Contained Therein. This Is What Underlies The Author In Making Java And Mysql-Based Employee Payroll Information Systems. The Research Method Uses A Waterfall And System Design Is Carried Out Using UML (Usecase, Activity And Class Diagram).
Optimasi Klasifikasi Parasit Malaria Dengan Metode LVQ, SVM dan Backpropagation

The use of the classification method affects the accuracy of the test results. The accuracy of the classification method is affected by the number of classes in the image. The number of classes and the amount of data should be considered when making decisions in choosing a classification method. This study used 600 data, which were divided into 510 training data and 90 test data. The number of classes tested is 12 classes with the number of initial features used by 22 features. The characteristics used in the test consist of shape characteristics and texture characteristics. The classification methods used in this study are LVQ, Backpropagation, and SVM. The data has 22 features or attributes that are the result of texture and shape feature extraction. Texture features are energy 0 o , energy 45 o , energy 90 o , energy 135 o , entropy 0 o , entropy 45 o , entropy 90 o , entropy 135 o , contrast 0 o , contrast 45 o , contrast 90 o , contrast 135 o , homogeneity 0 0 , homogeneity 45 o , homogeneity 90 o , homogeneity 135 o , correlation 0 o , Correlation 45 o , correlation 90 o , correlation 135 o , features of área and perimeter shape. The test results using the Backpropagation method obtained 89.7% results, using the LVQ method obtained 77.78% results, and the SVM method obtained 99.1% results.
Two-Way Analysis of Variance

Biostatistics with R provides a straightforward introduction on how to analyse data from the wide field of biological research, including nature protection and global change monitoring. The book is centred around traditional statistical approaches, focusing on those prevailing in research publications. The authors cover t-tests, ANOVA and regression models, but also the advanced methods of generalised linear models and classification and regression trees. Chapters usually start with several useful case examples, describing the structure of typical datasets and proposing research-related questions. All chapters are supplemented by example datasets, step-by-step R code demonstrating analytical procedures and interpretation of results. The authors also provide examples of how to appropriately describe statistical procedures and results of analyses in research papers. This accessible textbook will serve a broad audience, from students, researchers or professionals looking to improve their everyday statistical practice, to lecturers of introductory undergraduate courses. Additional resources are provided on www.cambridge.org/biostatistics.
SCIENTIFIC TRADITIONS OR OVERTHROW OF AUTHORITIES: WHAT IS THE CHOICE OF THE WORLD?

The authors of this article, wondering about science as a completely unique social phenomenon; o note (consider as a objective reality) the crisis of the foundations of modern science; o offer certain principles for creating a new science - «science from scratch»; o reflect on the role of scientific traditions, the specifics, framework and functions of scientific schools of the past, present and future, and most importantly, on the true meaning of scientific knowledge and the mission of a scientist.
Multilingual Email Zoning

The segmentation of emails into functional zones (also dubbed email zoning) is a relevant preprocessing step for most NLP tasks that deal with emails.However, despite the multilingual character of emails and their applications, previous literature regarding email zoning corpora and systems was developed essentially for English.In this paper, we analyse the existing email zoning corpora and propose a new multilingual benchmark composed of 625 emails in Portuguese, Spanish and French.Moreover, we introduce OKAPI, the first multilingual email segmentation model based on a language agnostic sentence encoder.Besides generalizing well for unseen languages, our model is competitive with current English benchmarks, and reached new state-of-the-art performances for domain adaptation tasks in English.
SooLics (Smart Room for Learns Physics) with Augmented Reality Sound Technology Based on Camera as a Physics Learning Room for Blind Students

A good educational process is one that is able to encompass existing communities, not expection for children with special needs. But the lack of adequate facilities makes them lack of maximum learning. SooLics (Smart Room for Learns Physics) with Augmented Reality Sound Technology based on Camera as a learning room for children with visual blindness is a room specifically designed for children with visual blindness to improve understanding about physics. In contrast to the usual learning room, Augmented Reality Sound Technology is used for visualization of physical matter that has been prepared in the room as a “visual aid” for children with visual blindness. We use Research and Development (R&amp;D) methode which is consists of defining studies (define), the design phase (design), and development. This research uses a camera which is specially designed to be used as a scan media for markers on augmented reality technology that has been prepared and installed in the room and the results are sound about physics matter. This room is designed so that blind children can learns independently.
UPAYA MENINGKATKAN MINAT BELAJAR MATEMATIKA DENGAN METODE COOPERATIVE SCRIPT

The purpose of this study was to determine the appropriate application of the cooperative script method in order to increase the learning interest of the fifth grade students of SD Negeri Prembulan. The results of this study indicate that: (1) In general, the application of the appropriate cooperative script method is effective in increasing interest in learning mathematics, (2) Increasing interest in learning mathematics for fifth grade students of SD Prembulan in pre-cycle by 62.07 in cycle I of 76, 31 in cycle II amounted to 85.39.
Logical model of mobile object control

This paper describes a logical model applied as a soft control tool to mobile objects. The model of the logical spatial situation without uncertainty, i.e., according to the law of excluded middle, is considered as the basis. Nonetheless, the motion rules are derived using an approach applied in constructible mathematics and logic. The approach consists in the finitude of variants of control and analyzing all potential traffic scenarios. The constructible object considered in this paper is the situation’s logical model. The constructible approach consists in considering the model of a typical railway station by the example of which the traffic is analyzed. The situation’s logical model is implemented as a condition for potential traffic. This model is described using mathematical logic with the help of logical variables and rules. The control system in this case makes use of permissible versions of logical designs. The control relies on the feasibility of traffic. The system of control rules is developed on the basis of the logical situation’s model and formed without uncertainty. The article provides an analysis of complementary kinds of traffic.
Virtual Seminar on Coronavirus 2019 for the US-Mexico Border Region: Building Opportunities for Communication and Collaboration

Abstract While the US-Mexico border region has had increasing restrictions due to coronavirus 2019 (COVID-19), the economically and socially integrated region continues to facilitate necessary movement between the two countries. Binational partners representing universities, government, and health delivery worked together to develop a COVID-19 Virtual Seminar for the US-Mexico Border Region, which consisted of weekly sessions in Spanish designed to better facilitate communication and collaborative systems between border states. In total 835 participants registered for the virtual seminar with attendance ranging from 394 in Session 1 to 269 in Session 6. From evaluation surveys (n = 297), organizers observed a large plurality of healthcare professionals, followed by students, researchers, and government employees. The seminar’s contribution to increasing collaborative and communication systems identified major needs in the region surrounding surveillance and monitoring; increased resources for migrant shelters to control outbreaks; an increase in personal protective equipment; tracking binational cases.
DETERMINATION OF EFFECTIVE METHODS AND METHODS OF DELIVERY OF EDUCATION TO STUDENTS

We discussed the problems of choosing effective methods and methods of delivering education to students in the paper. This process is very complex and contains a huge range of interacting variables. Nowadays, there is no adequate theory or process to determine effective methods and methods for delivering education to students. As a rule, it is assumed that individual learning is the default option, because of its superiority, and online learning is used only when circumstances do not allow the use of individual learning. However, online learning has become very common and effective in many contexts. Fully online courses are suitable for some types of students better than others: older, more mature students; students with an already high level of education; part-time students who work or with families. In terms of blended learning, the criteria are less clearly defined than for fully online learning. These courses are more suitable for more experienced students with strong motivation. In general, online students need more self-discipline in learning and more motivation to learn to succeed. This does not mean that other types of students cannot benefit from online learning, but additional efforts must be made to develop and support such students on the Internet. In terms of blended learning, the criteria are less clearly defined than for fully online learning. The advantage for students is to increase flexibility, but they should still live close to the educational institution, since this model means attending classes at the university. In addition, blended learning enables the gradual development of self-learning skills, if it is a focused learning strategy. Research also suggests that self-study skills need to be developed while students are at university. In other words, online learning in the form of blended learning should be deliberately introduced and gradually expanded as students work on the training program, so by the time they graduate, they acquire the skills necessary for self-study, which is critical in the digital age .Based on the study, steps are suggested for choosing the necessary method and method of delivering education to students.
SentiHotel: a sentiment analysis application of hotel services using an optimized neural network

An assessed hotel service is necessary for tourists and everyone who is traveling, however currently it is still difficult to find recommended hotel information. The solution provided in this research is to propose a smart application that has been developed by implementing machine learning in it. The purpose is to build a sentiment review smart application by applying the sentiment analysis hybrid model of the best neural network (NN) algorithm model that has been optimized using genetic algorithms. To get the right model, the research method was carried out with experiments starting from the initial stages of conducting data preprocessing, tokenization, weighting, modeling experiments, and conducting the system evaluation stage to determine the success of the proposed model. The progress of the application development system is by using the prototyping model. SentiHotel is a sentiment application that was successfully built to provide a solution for tourists in assessing a hotel service. The software validation test is carried out using the blackbox method and the results show that the SentHotel application is in accordance with the expected result; all system functions can run properly.
The Role of Factors Influencing Total Factor Productivity in East and West Asia with Emphasis on Human Capital and Oil Rents

The Role of Factors Influencing Total Factor Productivity in East and West Asia with Emphasis on Human Capital and Oil Rents
STRUCTURAL COMPONENTS OF INDEPENDENT WORK AS AN EFFECTIVE PEDAGOGICAL CONDITION FOR THE DEVELOPMENT OF INTELLECTUAL AND CREATIVE ABILITIES OF FUTURE MUSIC TEACHERS

The article examines and substantiates the structural components of independent work as an effective pedagogical condition, which ensures the development of intellectual and creative abilities of future music teachers. The author distinguishes the following key structural components: methodical, musical performance, and field-research. With its particular specialization, each component contributes to the constitution of an integral unity in achieving the development of intellectual and creative abilities. The study substantiates the essence of each of the presented components. It has been proven that the methodical component performs the function of the basic components in the structure of independent work. Methodical training contributes to the effective qualifications process as well as selection of techniques, methods, and exercises to improve professional training. Musical performance is considered as a process that determines the development of intellectual and creative abilities of future music instructors by forming intellectual and creative thinking through the use of different ways of cognitive activities. Also, the musical performances of the future music teachers during independent work involves solving a number of creative tasks. At the same time, you need to use interactive teaching methods that are aimed at optimizing the educational process. The field-research component provides students with artistic creativity as well as pedagogical skills, which contributes to the enrichment of their intellectual potentials and formation of research thinking, as a result, expanding their analytical, intellectual and creative skills. Within the research component, it has been assumed that the formation of research skills contributes not only to the research culture, but also to the highest level of development of intellectual and creative abilities for upcoming music teachers.
Towards Adversarial Genetic Text Generation

Text generation is the task of generating natural language, and producing outputs similar to or better than human texts. Due to deep learning’s recent success in the field of natural language processing, computer generated text has come closer to becoming indistinguishable to human writing. Genetic Algorithms have not been as popular in the field of text generation. We propose a genetic algorithm combined with text classification and clustering models which automatically grade the texts generated by the genetic algorithm. The genetic algorithm is given poorly generated texts from a Markov chain, these texts are then graded by a text classifier and a text clustering model. We then apply crossover to pairs of texts, with emphasis on those that received higher grades. Changes to the grading system and further improvements to the genetic algorithm are to be the focus of future research.
Cultural Understanding In English Language Learning

Language and culture are two things that are interrelated in human life, especially in learning and langage teaching. The objective of this study is to dercribe the understanding of culture in learning English. This research belongs to qualitative research which applies libraries research to collect the data. The introduction of this culture is especially recommended for foreign language learning which places more emphasis on developing communication skills with the target language. The introduction of culture in learning English process can reduce the potential for misunderstandings to occur during the communication process.
Estimation of Shape (α) and Scale (λ) of Two-Parameter Lomax Distribution (LD) using Median Ranks Method

The objective of this paper is to estimate the parameters of Lomax distribution with shape parameter(α) and scale parameter(λ). In this heuristic algorithm, the Median Rank regression method is used to Estimates the parameters of Lomax Distribution. We also computed Average Estimate (AE), Variance (VAR), Mean Absolute Deviation (MAD), Mean Square Error (MSE), Relative Error (RE) and Relative Absolute Bias (RAB) for both the parameters under grouped sample based on 1000 simulations to assess the performance of the estimators.
Personalized Search Engine Using Binary Tree Traversal (BTT) - A Survey

Web pages have an increasing number of been used because thepatron interface of many software programsoftwarestructures. The simplicity of interplay with internet pages is an idealbenefit of the usage of them. However, the character interface also can get extracomplicatedwhilegreatercomplexnet pages are used to construct it. Understanding the complexity of net pages as perceived subjectively with the resource of clients is thereforecrucial to betterlayout this sort ofconsumer interface. Searching is one of thenot unusual placeassignmentachievedon the Internet. Search engines are the essentialtool of the net, from whereinyou willcollectassociatedstatistics and searched in keeping with the favoredkey-word given by the character. The recordson theinternet is developing dramatically. The consumer has to spend extra time with inside theinternetin case youneed to find outthe correctfactsthey may befascinated in. Existing net engines like Google do now no longerundergo in thoughtsuniqueneeds of character and serve eachpatron similarly. For this ambiguous query, some offiles on wonderfulsubjects are decreaselower backby engines like Google. Hence it will becomedifficult for the consumer to get the requiredcontent materialfabric. Moreover it additionally takes extra time in searching a pertinent content materialfabric. In this paper, we are able to survey the numerous algorithms for decreasing complexity in internetweb page navigations.
Criteria for checking the level of skill formation mindful reading in third grade students

The article presents a criterion characteristic with possible criteria, indicators and level indicators for testing the skill of conscious reading in third-grade students.
Implementasi Fuzzy Neural Network untuk Peramalan Penjualan Sepeda Motor

This study discusses the implementation of the Fuzzy Neural Network for forecasting motorcycle sales at Cahaya Sakti Motor.Fuzzy Neural Network is a hybrid system that combines two methods, namely fuzzy logic and artificial neural networks.Fuzzy Neural network method used in this research is a combination of fuzzy logic with the Multi Layer Perceptron approach.This study aims to determine the number of motorcycle sales in 2019 based on sales data from January 2014 to December 2018.Based on the research results, the Fuzzy Neural Network model is suitable for forecasting motorcycle sales, because the MSE value obtained is very small, namely 9.9924e-06 for training data and 0.0560 for testing data.The results of forecasting 2019 motorcycle sales at Cahaya Sakti Motor are 153 units in January, 133 units in February, 114 units in March, 116 units in April, 125 units in May, 157 units in June, 120 units in July, 114 units in August, 122 units in September, 125 units in October, 160 units in November, and 115 units in December.