Reviewerly/exHarmony huggingface dataset:
A THEORETICAL MODEL OF THE SYSTEM DEVELOPING READINESS OF TRANSPORT UNIVERSITY STUDENTS FOR INNOVATIVE PROFESSIONAL ACTIVITY

The article summarizes the results of the research on building a theoretical model of the system developing readiness of transport university students for innovative professional activity. The suggested theoretical model consists of nine interrelated links, each with its own functional focus, its own local purpose, didactic significance, theoretical and practice value. The original link of the theoretical model is goal setting, which means developing readiness of transport university students for innovative professional activity. The second link reflects the structure and content of the concept of students’ readiness for innovative professional activity. The third link presents the information didactic basis of developing readiness of transport university students for innovative professional activity. The competence practice-oriented technology of developing readiness of transport university students for innovative professional activity is provided by link four. The elements of this technology include students’ activity to carry out practice-oriented term papers and degree qualification projects, their activities for the performance of work under industrial practice programs in enterprises as well as conducting practice-oriented research work. The criterium diagnostic apparatus is presented by link five comprising the following components: the criteria to evaluate students’ readiness for innovative professional activity, the test package for identifying the levels of students’ readiness for innovative professional activity, the methods of conducting summative and formative assessments for identifying the levels of students’ readiness for innovative professional activity. Link six is the control procedure; link seven shows the results of students’ readiness for innovative professional activity; link eight is self-correction, and the educational process correction is presented by link nine. The practical significance of the suggested theoretical model can be formulated as follows: it is used as an algorithm in the consistent and continuous implementation of all the interrelated phases of the study allowing to identify the role of each structural link of the model and its influence on the outcome; moreover, it will promote an imaginative and holistic view of the process of developing students’ readiness for innovative professional activity as a holistic and purposeful system.
Analytical capabilities of the Grand-2000 high-resolution spectrometer

The analytical characteristics of the new Grand-2000 high-resolution spectrometer with BLPP-4000 photodetectors were evaluated. The device was tested as part of the Grand-Potok complex, which consists of a spectrometer and an electric arc facility and is designed to analyze powder samples continuously brought into the plasma atomizer (free-burning arc in air). The characteristics of the new spectrometer were compared with those of the Grand spectrometer, which is widely employed in analytical laboratories. It is shown that the use of the Grand-2000 spectrometer to determine the concentration of elements in geological and industrial powder samples does not lead to an obvious improvement in the results. The threefold increase in the spectral resolution of the new spectrometer reduces spectral influences from interfering elements, but the relative systematic error both decreases and increases for different samples. This may indicate the influence of unaccounted-for factors, for example, non-optimal spectra processing algorithms for this device. The results obtained suggest good prospects for the use of the Grand-2000 spectrometer to determine the concentration of elements in samples with a complex spectrum, but they also indicate the need for further studies to determine the optimal parameters for processing spectra. In addition, the Grand-2000 spectrometer can be used to supplement and refine the existing database of the wavelengths of spectral lines.
SENTIMENT ANALYSIS OF THE LARGE PRIEST OF FPI’S RETURN USING SUPPORT VECTOR MACHINE WITH OVERSAMPLING METHOD

At the end of 2020, Habib Rizieq's return to Indonesia drew criticism from the public for causing crowds during the Covid-19 pandemic. News and opinions about Habib Rizieq fill internet platforms, including Twitter. The researcher wants to classify the opinion text data of Habib Rizieq's return from Twitter into positive and negative sentiments using the Support Vector Machine method. Opinion data comes from Twitter, so the data is analyzed by text mining through the preprocessing stage. The SVM classification of unbalanced data between positive and negative classes resulted in 95.06% accuracy with a negative class precision value of 84% and better than 72% recall, in the positive class the precision value was 96% less than 2% of recall 98%. While the SVM classification with the oversampling method gets 100% accuracy, precision, and recall. The results of positive sentiments are known that the public will always support and want freedom for Rizieq, for negative sentiments it is known that many people are disappointed with Rizieq regarding the lies of his swab test results.
Utilization Learning Media Based Animation in the Teaching of Children’s Literature Subject

A animation is a medium.Media to change something, from an imagination, an idea, a concept, to a visual, until finally giving an influence to the world is not only a barrier in the world of animation.One of the courses in the Indonesian Language and Literature Education Study Program is Teaching of Children's Literature.The purpose of this study is to describe the effectiveness of animation-based learning media in the Teaching of Children's Literature course in the Indonesian Language and Literature Education Study Program.The population in this study were all students of the Indonesian Language Education Study Program class of 2020 and the sample was 32 students.This research uses quantitative descriptive research method.Based on the results of research that has been done, it is shown that animation-based learning media is effectively used.Student learning outcomes before using animation-based learning media in children's literature teaching courses get an average value of 70.38 with a standard deviation of 12.33 and a standard error of 2.7 .After using media-based learning animation m endapatkan average value of 82.09 with a standard deviation of 8.56 and a standard error of 1.57 .For this reason, the use of animation-based learning media is effectively used in the Teaching of Children's Literature course in the Indonesian Language and Literature Education Study Program.
Appreciative Learning for Immersive Reward System in Education Game Development

Game replayability is very important in serious game to maximize the understanding for the learning content. The replayability is the result from the gameplay experience. Games have the advantage of providing a fun experience, and immersion is a vital element in game design to produce the experience. However, the design of immersion in games is often not well conceptualized so that it does not produce the expected experience. This study uses Appreciative Learning based reward system, which focuses on positive things such as peak achievements, opportunities, exploration of potential and optimism for the future. The reward activity consists of four stages, namely Discovery, Dream, Design and Destiny. Reward personalization is done by regulating reward behavior using artificial intelligence which runs in all four stages. Appreciative Learning will be used to design immersive experiences consisting of sensory, imaginary and challenge-based immersion, which are the three main elements of immersive games. Intelligent agent behavior is modeled using the Finite State Machine. This study produces an immersive reward design that is applied to the concept of Appreciative Learning in designing a serious game.
Performance Study Of Uncertainty Based Feature Selection Method On Detection Of Chronic Kidney Disease With SVM Classification

Chronic Kidney Disease (CKD) is a disorder that impairs kidney function. Early signs of CKD patients are very difficult until they lose 25% of their kidney function. Therefore, early detection and effective treatment are needed to reduce the mortality rate of CKD sufferers. In this study, the authors diagnose the CKD dataset using the Support Vector Machine (SVM) classification method to obtain accurate diagnostic results. The authors propose a comparison of the result on applying the feature selec- tion method to get the best feature candidates in improving the classification result. The testing process compares the Symmetrical Uncertainty (SU) and Multivariate Symmetrical Uncertainty (MSU) feature selection method and the SVM method as a classification method. Several experimental scenarios were carried out using the SU and MSU feature selection methods using the CKD dataset. From the results of the tests carried out, it shows that using the MSU feature selection method with 80%: 20% data split produces nine important features with an accuracy value of 0.9, sensi- tivity 0.84, specification 1.0, and when viewed on the ROC graph, the MSU method graph shows the true positive value is higher than the false positive value. So the classification using the MSU feature selection method is better than the SU feature selection method by 90% accuracy
Implementation Of K-Nearest Neighbor - Certainty Factor For Expert System Detection Of Idiopathic Thrombocytopenic Purpura

Idiopathic Thrombocytopenic Purpura (ITP) is an autoimmune disorder. ITP can occur in children and adults. This disease can be fatal because the platelet count is low due to the destruction of excessive platelets so that it can interfere with vital organs and bleeding occurs. The lack of knowledge of ordinary people about ITP disease, so many people assume that bruises and nosebleeds on the body are caused by fatigue. For that, we need a system that can imitate the expertise of an expert in diagnosing this disease based on the symptoms felt. The method used to support the expert system is the K-Nearest Neighbor and Certainty Factor methods which are a combination of 2 methods, where the classification results from the K-Nearest Neighbor method will be given a certainty value by the Certainty Factor method so as to produce a prediction. The results of combining the two methods can produce certainty in the diagnosis. Based on the test results using 3 test scenarios using parameter values k=3, k=5, k=7 and the results obtained the highest accuracy value with parameter value k=7 obtained an accuracy rate of 90,9%.
Efektivitas Peran Pustakawan Sebagai Mitra Pemustaka Menemukan Sumber Pustaka untuk Penelitian

The purpose of this study is to describe the effectiveness of the role of librarians as friends in finding library sources for research. The design is a mixed method with the Triangulation Design procedure: Validating Quantitative Data Model. In this model, researchers will collect quantitative data and qualitative data. The next stage is to carry out further analysis by validating the results of quantitative analysis using qualitative results. The population in the study were all lecturers at Lambung Mangkurat University. The sample to determine the effectiveness of the role of librarians in research, namely 100 lecturers. Data were collected by filling out a questionnaire to answer all problem formulations. Also supported by interviewing lecturers to validate the results of filling out a questionnaire about the role of the librarian as a place to find library sources for research. The results of this study is that 54.49% of researchers agree that librarians are effective as friends in finding sources of literature for research. 33.91% of researchers strongly agree. While a small proportion of researchers, namely 0.87% and 0.58%, respectively, stated that they disagreed and disagreed with the statement. The conclusion of this research was the librarian's role has been effective as a friend in finding library resources for research
MPFANet: Semantic Segmentation Using Multiple Path Feature Aggregation

Image segmentation is the process of simplifying the analysis of the meaning or the front to say the process of dividing the image into a set of multiple pixels.The multiple path feature aggregation (MPFA) method proposed in this paper aims to extract various information of an object, and uses conventional pyramid pooling or the extraction of various sized features.This information can be combined with different regional features to obtain the overall feature information.We split four paths to extract numerous local features, and the results showed that the mean intersection over union (mIOU) is 81.6% for the validation data from the PASCAL VOC 2012 dataset, and a better performance than the existing DeepLab model was demonstrated.
Causal event extraction using causal event element-oriented neural network

Causal event extraction plays an important role in natural language processing (NLP) such as question answering, decision making and event prediction. Previous work extracts causal events using template-matching methods, machine-learning methods, or deep-learning methods. However, these methods ignore the guiding role of specific causal patterns on causal event extraction. In this paper, we propose causal event element-oriented neural network CEEONN to extract causal events. Firstly, we construct causal event element knowledge base CEEKB from domain casual text. Then we construct a neural network by incorporating both the entire sentence and associated causal patterns into a better semantic representation. With domain-based CEEKB, the proposed CEEONN can be better guided to identify specific causal patterns. Experiments show that CEEONN achieves competitive results compared with previous work.
Mandarin Language Learning with Gamification Method

The rapid economic and industrial development in China over the past few decades has made Mandarin more in demand as a business and cultural language, and now Mandarin is the second most popular international language. Therefore, learning Mandarin is something that is quite important in this era of globalization. However, to learn Mandarin is not an easy thing because Mandarin is a language that is quite difficult to master. So that it can reduce motivation to continue learning and in the end decide to stop learning Mandarin. Based on these problems, in this study, we will design and develop a mandarin learning application with the gamification method using the Octalysis framework to increase motivation in learning Mandarin. and will measure the level of behavioral intention to use and user immersion towards the application using the Hedonic Motivation System Adoption Model (HMSAM). The tests have been conducted and prove that gamification can increase the user's motivation to continue learning Mandarin. This is shown based on the evaluation conducted, the user states strongly agrees that the application that has been designed and built can improve the behavioral aspect of intention to use, this is indicated by the percentage value obtained by 82.47%. And agree that the application can cause immersion aspects when using the application, this is indicated by the percentage value obtained by 79.56%.
Peningkatan Pengetahuan KESGILUT pada Anak Berkebutuhan Khusus melalui Aplikasi Teledentistry

The parents of special needs children (SNC) problem in West Sumatra is the poor oral health of SNC, due to a lack of oral and dental health maintenance knowledge. The teledentistry application “SpecialSmile” is the solution offered. The aim is to improve oral health knowledge remotely. The method is carried out by preparing educational content in scientific articles or audiovisuals form. Program evaluation was collected by filling out a questionnaire containing 10 questions about oral health knowledge, before and after using this application. Data analysis was done descriptively. The results obtained from 49 users, before using the application only 22.95% of parents had good knowledge and after using the application there was an increase of 80.33% of parents who had good knowledge regarding oral health maintenance among SNC. This program concludes that remote education using the SpecialSmile application can increase the knowledge of ABK parents about maintaining SNC's oral health
Determination of Accuracy at Backpropagation Method in Prediction Crude Oil Prices

We analyzed the performance of the artificial neural network with the backpropagation method in predicting crude oil prices in this paper, including the case of crude oil price predictions. The training results obtained that the MSE value was 0.00099762 with 135 Epoch, in the network testing the MSE value was 0.093336. Meanwhile, the predicted value is determined by the target value with a contribution of 99% with a significant effect. Thus the accuracy level is determined by the target value and the predicted value. The accuracy of the system is obtained for 83,6%.
STEM PROJECTS AS AN EFFECTIVE MEANS OF FORMING STUDENTS’ KEY SKILLS OF THE XXI CENTURY

The article substantiates the possibilities of developing promising skills of the XXI century, in particular soft skills, as a set of non-specialized, super-professional skills, which, unlike specialized, are not related to a specific field of professional activity. The leading means of developing such skills are STEM-projects, which combine the basic elements of research, project activities and take into account the external requirements of a particular activity. The analysis detected that common skills that were relevant 5 years ago and were envisaged for today, were such as interaction with people, integrated problem solving, creativity, critical thinking, the ability to form own opinions and make decisions, the ability to listen and ask, flexibility of mind (the ability to quickly switch from one thought to another) and emotional intelligence. In most scientific papers, the key soft skills include creative thinking, information management, emotional intelligence, the ability to form own opinions and make decisions, presentation skills. Based on this, the emphasis is on changes in the formation of soft skills and their development. At the theoretical level, methods of developing key skills include trainings, seminars, mastering models of successful behavior, finding feedback, learning from the experience of others, identifying models of successful behavior of people with a high degree of development of certain competencies. The development of soft skills requires special methods that focus on critical thinking; creativity; organizational skills; team working; emotional intelligence; problem assessment and decision making; ability to interact effectively; cognitive flexibility; versatile development of individuality; formation of a holistic scientific worldview of students; formation of a holistic scientific worldview of students; formation of a personality capable of independently choosing and making responsible decisions; education of students' respect for work, providing conditions for life and professional self-realization, formation of readiness of a conscious choice and mastering of the future profession. It is proved that the driver of the development of key competencies and skills of the future in students is STEM education in general and STEM projects in particular. The scheme proposed to the participants of the All-Ukrainian online-contest “Teacher of the Year” on the version of science journal “Kolosok”, who competed in the category “STEM teacher”, is highlighted.
The use of font features as a manifestation of the external side of the emotiogenicity of the text

The article describes the graphic features, namely, font combinations that affect the perception and assessment of the text by the recipient. The type of font and its color affects the perception and mental state of a person, because a certain color evokes certain emotions in a person, thus, being a manifestation of the category of text emotiogenicity.
Analyzing Problem Solving Difficulties on Applied Military Operation Research

Operations Research is a scientific discipline that can be used to help make decisions in all fields. In the military field, the application of operations research is very much so that every officer must be able to apply it in carrying out his duties. Indonesian Navy officers received education about operations research, especially the analytic hierarchy process when they attended the Staff and Command College. A total of 20 student officers were examined to find out the difficulties they faced in solving problem solving for the analytic hierarchy process material through written answers to questions and in-depth interviews using Polya's problem-solving steps. The results obtained are that all officers did not experience problems at the time of problem identification. However, almost half of them experienced problems when planning solutions, carrying out calculations and conducting reviews. The recommendation submitted is to use a software application so that the calculations are correct and fast.
Integrated Development Technology of Artificial Intelligence, Big Data and Cloud Computing

In terms of the current development status and future development direction of artificial intelligence, big data and cloud computing, the relationship between the three is inseparable. The essence of the Trinity era is that the development of the future era will focus on the three technologies of artificial intelligence (AI), big data and cloud computing. At the same time, big data has gradually entered people's vision. After the information revolution, the connection between people's daily life and data is becoming more and more close. Many enterprises begin to use the mining and analysis of big data to mine the development trend and business model of enterprises, so as to help enterprises obtain higher operation efficiency and stronger competitive advantage. Starting from reality and combined with the author's work experience, this paper discusses the combination of artificial intelligence, big data and cloud computing.
Design Aspects of Standalone PV System with Two Simulation Tools

The conventional energy sources depleted day by date. Alternate energy requirement is necessitate for our daily life. Our energy demand is met by standalone PV based system. This paper explained the simulation of a standalone photovoltaic power system erected in Mailam with different simulation tools. Solar resources for the design of this system were taken from the National Aeronautics and Space Administration (NASA) Surface Meteorology at a location of 22° 59' S, 14° 29' E with annual average solar radiation of 5.14 kWh/m2/d. PV planner and PV syst simulation tools were used to analyze the design of photovoltaic power system model. The entire model was designed based on an hour-by-hour data depend on energy availability and its demands. A detailed design of standalone PV system with two different simulation tools were presented in this paper.