Reviewerly/exHarmony huggingface dataset:
SPECIFIC FEATURES OF ORGANIZATION OF THE EDUCATIONAL PROCESS OF ADULTS IN THE SYSTEM OF CONTINUING EDUCATION

Introduction. Currently, the system of teacher training continues to actively search for new or- ganizational forms, adjusting the content of the learning process to improve the quality of training. The close attention of scientists is focused on the study of the qualitative organization of the educational process of training teachers for schools. The article is enlighten the research of educational continuing studying which lies in the basis of the system of qualification uprising of educational specialists, the article is enlighten particulars of educational process of specialists which are the mortgage of success in qualifica- tion uprising. The author analyses the education of adults as an integral part of continuing education, factors influencing the attitude of adults to education: the specifics of the motivation of adult learning activities, the nature of the adult's position in learning, the influence of the practical experience of adults in the process of learning. In the article, authors consider the peculiarities of adult education in the system of continuous education. The concept of the results of research of the features of adult learning in the training of teaching staff have been generalized, of the analysis of the process of organization of postgraduate education. The purpose of the article. Based on the study of the system of postgraduate education of teachers to identify features that are inherent in the process of adult learning.The methods of analysis. The theo retical methods of research are used in the article. Results. The article is devoted to the description of the theoretical bases of the research peculiarities of adult education in the system of continuous education of teachers. Originality. The understanding the successful qualification uprising of teachers depends on age and psychological features of a person. Conclusion. It has been proven that adult learning dif- fers significantly from children's education in a clearly perceived need for continuous professional development and growth. It is emphasized that the process of training a specialist-practitioner never ends. The subject who participates in the educational process has a clear goal, is aware of the dependence of its successful achievement on learning, ie on the continuous process of professional development
New Technology Approaches In Exlibris Design: Hologram Case

Today's technological changes have changed the design application methods and the changing demands of the society.This differentiation also affects the aesthetic and formal approaches in exlibris designs.Human creative intelligence and technology fed each other in every period.With this study, software as a reflection of rapidly developing and changing technologies, effects of hologram on exlibris art, usage patterns, application types; Analysis will be examined by data collection method.It is aimed to encourage the reader and the collector with different technology approaches and to contribute in the context of exlibris production that can be made with new technologies.The appropriateness of content and presentation technologies developed for exlibris design will be examined.The functions of hologram, one of the important technological innovations in the field of design, used in graphic design and its usage possibilities for exlibris design will be examined.
The Effect Of Quality Of Document Service To Customer Satisfaction In PT. Mediterranean Shipping

Mediterranean Shipping Company, is one of the major multinational companies in Indonesia, multinational companies can communicate with customers and sell to customers abroad without the need for a lot of physical investment in foreign markets (United Nations Conference On Trade, UNCTAD, 2017), through its market reach so large and with business relationships that are spread everywhere, then this company has a pretty good rating in the international business arena. PT. Mediterranean Shipping Company Indonesia develops its business as a shipping company in the field of International container transportation (export import) and offers various facilities for export to exporters.
Autoregressive Integrated Moving Average (ARIMA) Sebagai Model Peramalan Kasus Demam Berdarah Dengue

ARIMA is a forecasting method time series that does not require a specific data pattern. This study aims to analyze the forecasting of Semarang City DHF cases specifically in the Rowosari Community Health Center. The study used monthly data on DHF cases in the Rowosari Community Health Center in 2016, 2017, and 2019 as many as 36 dengue case data. The best ARIMA model for forecasting is a model that meets the requirements for parameter significance, white noise and has the MAPE (Mean Absolute Percentage Error Smallest) value. The results of the analysis show that the best model for predicting the number of dengue cases in the Rowosari Public Health Center Semarang is the ARIMA model (1,0,0) with a MAPE value of 43.98% and a significance coefficient of 0.353, meaning that this model is suitable and feasible to be used as a forecasting model. DHF cases in the Rowosari Community Health Center in Semarang City.
Penerapan Data Mining untuk Mendukung Pemasaran Produk Pinjaman Bank

Competition in the banking sector requires every bank to compete to make types of credit products that are able to attract customers to want to transact with banks. Marketing with a product centric strategy needs to be combined with a customer centric to keep Customer Relationship Management in good order with customers. Customer identity can be used to realize the concept of a customer centric marketing strategy. This study describes the role of Data Mining on customer data accompanied by the application of Decision Tree techniques with the C4.5 algorithm to identify the most influential fields in predicting loan products.&#x0D; The customer data fields used in this study include total balance, date of birth, occupation, and status. Selection of fields based on the terms and conditions that apply to each type of loan. The results of applying the C4.5 algorithm to customer data in the formation of loan product prediction decision trees show that the work attribute is the dominant attribute (highest Gain value) among the other attributes. Prediction results are validated with Confusion Matrix with an accuracy value for loan product prediction of 82%.&#x0D; The results of this study concluded that the customer database is a source of data in the prediction process of loan products to be offered to customers, which can be used to support the marketing of bank loan products with a customer centric orientation.
FROM FOLK CULTURE TO MATHEMATICS. TRADITIONAL AND INNOVATIVE APPROACHES TO EDUCATION

The next issue of the scientific journal «Volga Region Pedagogical Search» is devoted to the problem of education. In the era of globalization the following problem, is very acute. There is no coincidence that amendments were made to the Law on Education in the Russian Federation. The issue presents the works of researchers from Ulyanovsk, Tambov, Yaroslavl, Lipetsk, St. Petersburg, Yekaterinburg, Orel, Kursk, Saranskk (Republic of Mordovia), Kazan (Republic of Tatarstan). The wide geography indicates the relevance of the stated topic. The authors presented their views on the problem of education.The integrated approach allows you to look at the problem of education in a special way.
How to improve your website ranking on GOOGLE

The article describes the current topic of website optimization and how to improve its position in the ranking in search results.We will discuss in what ways you can achieve higher positions.This article also provides general guidelines for SEO optimization.
Studi Fenomenologi Perilaku Mahasiswa Pengguna Krs Online

Based on the phenomenon of lack of confidence when programming KRS online, the research was conducted to describe the perceptions of students of class 2016 using KRS Online on the Management Information System of Universitas PGRI Madiun related to payment bill information and to show how confident they are to use so that it affects their behavior. The study was conducted on students from 2016 with 7 informants from 3 faculties, namely FKIP, FEB and FT. The method used is qualitative with a phenomenological approach and data collection by means of interviews and participant observation. The results show that student behavior as seen from the perceived usefulness has a relaxed attitude and is not complicated, responsive and fast, willing to use it alone without having to be represented shows that students feel comfortable. Behavior that can be seen from the perception of ease of being confident, more relaxed, cautious, not confused because of clear steps. The perceived convenience and usefulness could be factors that affect the smoothness of UNIPMA’s revenue.
An Approach to Detect Sentence Level Sarcasm Using Deep Learning Techniques

Today is the era of customer self-service, where people use conversation agents (chatbots) to get their query solved in minimum time and cost.Use of conversation Agent gives real time experience to user/customer to get answers very fast.To make this experience more genuine it needs understanding of human emotions and which is the most complex task to perform as facial expression and verbal details are unavailable.Most of data over the internet is in textual format which needs to process to get required answers that is why one of the most popular area in natural language processing is Sentiment analysis which focuses on solving this issue.Sarcasm is critical sentiment which is very difficult to recognize by machines.User express sarcasm to show their anger, disagreement using positive words over internet forums, social media and over shopping sites for reviews about product, services, situation, workplace etc.This paper gives a combined approach by extracting pragmatic features like emoticons, use of hyperbole, punctuations and special words used in sentence to detect sentence level sarcasm using deep learning techniques such as LSTM which will help machine for better understanding of natural language.
Pidginized English Formation by Art Shop Attendants in Seminyak Street

This study aimed at finding out forms of pidginized English which used by the shop attendants in Seminyak. The data was analyzed qualitatively. Population and Sample Techniques was based on the sociolinguistics theory, particularly the theories of Wardhaugh (1986), Holmes (1992), Hudson (1980), Todd (1984), and Quirk and Greenbaum (1985). The method of collecting data used in this data was observation, interview and questionnaire. The data was collected by note taking technique by observing the shop attendance when ever they speak English with foreign customers. The Findings showed that the forms of pidginized Englishused by the shop attendants was positive, negative, and interrogative forms. As for the functions they used expressive, descriptive, argumentative, and signaling function.
DEVELOPING RECOUNT TEXT MATERIALS BASED ON K13 CURRICULUM FOR THE TENTH GRADE STUDENTS OF SENIOR HIGH SCHOOL

This research was aim to develop recount text materials to the tenth grader students of senior high school and find out the effectiveness of the recount text materials. This research was done in SMAN 1 Ponggok. The researcher used Research and Development (R &amp; D) adopted from of Sugiyono’s model (2015:298) to conduct the research. The data collected through interview, questionnaire, documentation, and test. The expert validation which used in this research were; 1) media expert 2) material expert. To try out the product, the researcher used one group pre-test and post-test experimental design. The results of the research showed that the develop of Recount Text Material was effective; it proved by 1) The result of material validation 98.18% and media validation 96.25 %. The average of those two validation is 97,22% that categorized as “very good” by interval 80% &lt; x ≤ 100%. So, the supplementary book of Recount text Material which developed was valid to be implemented in the tenth grader of Senior high school students. 2) It also increase the tenth grade students’ writing achievement that proved by the increase of the students’ of pre test mean score (66.67) to post test mean score (83.83). 3) The students also gave positive responses toward Recount Text Material as reflected from the result of the questionnaire given (85.8%). From that result presented before, it can be concluded that Recount Text Material was effective and increased the tenth grade students’ writing achievement. It means Recount Text Material can be used as a supplementary media for learning English writing.
A Framework to Predict Social Crimes using Twitter Tweets

Now a day's new wave of social media technologies like facebook, blogs, twitter plays an important role in formal and informal communications. In social media like twitter, users share their ideas, thoughts, and news in under 280 characters of text. An increasing amount of data coming from social networks can be used to generate a variety of data patterns for various sorts of investigation like human social behavior, system security, criminology etc. A framework is developed to predict major sorts of social media crimes (Cyber stalking, Cyber bullying, Cyber Hacking, Cyber Harassment, and Cyber Scam) using the data obtained from social media website. The proposed system contains three modules; data (tweet) pre-processing, classifying model builder and prediction. Data is interpreted using statistical models with Python. To create the prediction model, Multinomial Naïve Bayes (MNB), K-Nearest Neighbors (KNN) or Support Vector Machine model (SVM) classifiers can be employed that classify given data into different classes of crime. Further the accuracy of the system at different levels is measured. Resultsshows that each of the three algorithm attain the precision, Recall and F-measure above than 0.9.
Exploring the Non-Medical impacts of Covid-19 using Natural Language Processing

Ongoing COVID-19 Pandemic has resulted into massive damage to various platforms of global economy which has caused disruption to human livelihood.Natural Language Processing has been extensively used in different organizations to categorize sentiments, perform recommendation, summarizing information and topic modelling.This research aims to understand the non-medical impact of COVID-19 on global economy by leveraging the natural language processing methodology.This methodology comprises of text classification which includes topic modelling on unstructured COVID-19 media articles dataset provided by Anacode.Like other Natural Language Processing algorithms, Latent Dirichlet allocation (LDA) and Non-negative matrix factorization (NMF) has been proposed to classify the media articles dataset in order to analyze COVID-19 pandemic impacts in the different sectors of global economy.Model Accuracy was examined based on the coherence and perplexity score which came out to be 0.51 and -10.90 using LDA algorithm.Both the LDA and NMF algorithm identified similar prevalent topics that was impacted by COVID-19 pandemic in multiple sectors of economy.Through intertopic distance map visualization produced by LDA algorithm, it can be reciprocated that general industries which includes children schooling, parental care, and family gatherings had the major impact followed by business sector and the financial industry.
Efektivitas Penerimaan Peserta Didik Baru (PPDB) Pada Jenjang SMA Negeri Kota Cirebon

One of the annual compulsory activities carried out by every school to accept new students, namely the New Student Admission (PPDB), in implementing PPDB it is expected to eliminate schools labeled as favorite schools. The purpose of this study was to analyze the effectiveness of PPDB at the Cirebon City Senior High School. This study used a qualitative method, the research subjects were Class X Students of Cirebon City Senior High School taken by professional sampling with a total of 176 students. While the data analysis technique used in this study is a comparative descriptive analysis technique. The results of the study show the effectiveness of the admission of new students (PPDB) at the Cirebon City Senior High School which is very effective or has fulfilled 8 dimensions including (1) Availability of information systems; (2) The information system is easy to understand; (3) Relevant information system; (4) Useful information systems; (5) Timely information system; (6) Reliable information systems; (7) Accurate information system; and (8) Information systems must be consistent
Developing Training Evaluation Instrument for Teachers of Elementary School and Early Childhood Education in Pekanbaru, Riau

As an attempt to achieve successful learning in classroom, teachers are required to always learn and increase their potential, especially in using teaching aids.However, lack of teaching aids facilities and lack of development of evaluation instrument become main issues faced by teachers.Thus, it is necessary to develop training evaluation instrument for teachers.This research utilized a theoretical development model in instrument standardization activities.There were 30 respondents collected through an online questionnaire which were then analyzed using SPSS version 23.00 for Windows.Results showed that: 1) results of validity and reliability test showed that validity of training evaluation instrument for teachers met valid criteria.Construct validity was tested through factor analysis including material content, material presentation, discussion/question and answer, and group work practices; and 2) reliability of training evaluation instrument for teachers prepared and developed in this research met quite high category as indicated by alpha reliability coefficient of 0.935.
An android app for receiving, storing and exchanging blood pressure data way bluetooth, OCR and gesture input

Telemetry home, mobile technologies, and software application, has a positive effect onthe monitoring and management of some medical control parameters, and help to be more effective in the treatments, measuring blood pressure at home is becoming increasingly use by both clinicians and patients.This work implements a way to obtain information directly from commercial blood pressure devices,using application programming interface, without to have used the proprietary APP of the brand, use of the optical character recognition and the use of gestures using the fingers to write each of the blood pressure values; systole, diastole, pressure, date and time and send these data to a Web-DataBase way SMS message
Provisioning of Optimized Cab Services in Secured Blockchain Framework

Modern online cab booking services such as Ola and Uber are becoming increasingly popular due to ease of use and cost effectiveness.With rising popularity comes the responsibility of providing quality service to the customers.The presented research work illustrates a system that aims to provide maximum customer satisfaction by reducing the waiting time for a cab, improvising on the availability of cabs and providing data security.Availability of the cabs can be improved by reducing the distance between the locations of available cabs and the customers.One of the methods to reduce the distance is the prediction of cab bookings and ensuring availability of the cab service to the potential customer location in advance.The presented paper proposes a prediction mechanism based on a data set of social events happening in a particular region.As social events normally bring masses of participants at a location, the probability of use of cab services increases at that location.A Machine Learning (ML) model is built to predict the number of cab bookings for different areas, based on historical data & the type of participants attending the event.The predicted number of required cabs, current cab locations and event location are then used by the designed system to find the nearest drivers from the event location.The nearest drivers are notified to reach the location beforehand thereby making cabs readily available when the requirement arises.To ensure security of data in the compact system, private Blockchain network is used for data transfer and storage, making it reliable while also maintaining data integrity and confidentiality..
Project management in the digital economy

Project management is currently gaining momentum, as it has proven its effectiveness and efficiency. It is worth noting that in Russia, based on the PMI certificates obtained, the share of project managers is growing, which indicates that the market needs highly qualified specialists in this field. Project management is a special type of management activity based on a complex-system model of collective actions of participants, which allows you to get practical results in various business sectors. The transition to a new format of interaction using digital technologies, the digitalization of the economy, the use of artificial intelligence, the rapid and widespread change of generations in business that have their own characteristics in relation to the forms of work, various abilities to master and apply modern technologies and knowledge, and other factors are currently changing the nature of relationships in the "business management - personnel"system. Thanks to the digitalization of the economy, both new opportunities and new challenges are emerging in project management at the same time. The article examines the main trends in the digitalization of the economy, which generate fundamental changes in project management. Currently, digital technologies that directly affect the effectiveness of project management have been developed, such as artificial intelligence, the Internet of things, wireless communication technologies, digital production, big data, and blockchain. Thus, the conducted research allows us to conclude that for effective project management in the conditions of digitalization of the economy, it is necessary to correctly determine the most effective and timely tools
Adaptive Vocabulary Construction for Frustration Intensity Modelling in Customer Support Dialog Texts

This paper examines emotion intensity prediction in dialogs between clients and customer support representatives occurring on Twitter. We focus on a single emotion type, namely, frustration, modelling the user's level of frustration while attempting to predict frustration intensity on the current and next turn, based on the text of turns coming from both dialog participants. A subset of the Kaggle Customer Support on Twitter dataset was used as the modelling data, annotated with per-turn frustration intensity ratings. We propose to represent dialog turns by binary encoded bags of automatically selected keywords to be subsequently used in a machine learning classifier. To assess the classification quality, we examined two different levels of accuracy imprecision tolerance. Our model achieved a level of accuracy significantly higher than a statistical baseline for prediction of frustration intensity for a current turn. However, we did not find the additional information from customer support turns to help predict frustration intensity of the next turn, and the reason for that is possibly the stability of user’s frustration level over the course of the conversation, in other words, the inability of support’s response to exert much influence to user’s initial frustration level.