Reviewerly/exHarmony huggingface dataset:
The Russian System of Higher Education Is at a Turning Point

The article deals with the problems associated with Russia's withdrawal from the Bologna system. The possible limits and consequences of the transformation of the existing Russian system of higher education into a new one by 2022 are shown, as well as the reaction of the population of various regions of the country to the proposed changes, including changes related to raising the age of conscription.for military service. Based on the structure of income of universities from educational activities and the amount of tuition fees in different regions of Russia, the most probable shifts in the student preparation structure, the distribution of budget places across the country are analyzed. In addition, the readiness of residents of Moscow and St. Petersburg to go to study at universities in other large cities of the country was considered.
Game for Sasak Script Based on Knuth Morris Pratt Algorithm and ADDIE Model

Knowledge of the Sasak script is very few Sasak people are interested in learning it. The writing system of the Sasak script is in danger of becoming extinct, so the local government must carry out literacy education so that the Sasak script does not become extinct from the face of the Lombok earth and must be applied to elementary and junior high schools, not only in the learning and teaching process. Directing children can be done by introducing them to the game-based Sasak baluk olas script. The Sasak script game based on KMP (Knuth Morris Pratt) Algorithm and ADDIE (Analysis, Design, Development, Implementation, Evaluation) which integrates game thinking and game elements has proven helpful in learning new knowledge. For this reason, the purpose of this study is to discuss how to develop applications for the Sasak Baluk Olas script on smartphones based on the Android system. designed based on the famous visual novel concept that combines multimedia elements including audio, animation, graphics, and images to make it more interesting and lively. All of these elements combine with gamification elements such as quizzes, rewards, badges, and feedback to make it a gamification application. Based on all the abilities of the Sasak Baluq Olas script, it can help potential users, especially elementary and junior high school students in Mataram City to increase the level of understanding and awareness of the Sasak script so that it does not become extinct
Implementation Cryptography and Access Control on IoT-Based Warehouse Inventory Management System

Warehousing is a product storage management activity to ensure product availability, so inventory management is needed to oversee the movement of logistics and equipment. Some things need to be considered in the storage process, such as the suitability of the storage location, safe from theft, and safe from physical disturbances. Vulnerabilities can occur when unauthorized users find out information from the database regarding stored goods, so a security mechanism for the warehouse database is needed. In addition, proper identification needs to be made of someone trying to access the database. In this research, a Warehouse Inventory Management System (WIMS) was created by implementing the AES-128 cryptographic algorithm, which was built using ESP32 and Raspberry Pi 3 devices. Time Password (T-OTP). The results show that the built system can overcome inventory problems in conventional warehousing management systems and implement data security using the AES-128 algorithm. The application of two-factor authentication in the form of smartcards and T-OTP shows very good results in testing its accuracy to overcome the vulnerability of unauthorized access to the system database
Optimization of Performance Traditional Back-propagation with Cyclical Rule for Forecasting Model

The traditional Back-propagation algorithm has several weaknesses, including long training times and significant iterations to achieve convergence. This study aims to optimize traditional Back-propagation using the cyclical rule method to cover these weaknesses. Optimization is done by changing the training function and standard Back-propagation parameters using the training function and cyclical rule parameters. After that, a comparison of the two results will be carried out. This study uses quantitative method of time-series data on coronavirus cases sourced from the Worldometer website, then analyzed using three forecasting models with five input layers, one hidden layer (5, 10, and 15 neurons) and one output layer. The results showed that the 5-10-1 model with the training function and cyclical rule parameters and the tansig and purelin activation functions could perform well in optimization, including faster training time and smaller iterations (epochs), MSE training performance, and better tests. Low and high accuracy (92%) with an error rate of 0.01. So it was concluded that the training function and cyclical rule parameters with the tansig and purelin activation functions were able to optimize the traditional Back-propagation method, and the 5-10-1 model could be used for forecasting active cases of the coronavirus in Asia
Infrastructure as Code for Security Automation and Network Infrastructure Monitoring

The Corona Virus (COVID-19) pandemic that has spread throughout the world has created a new work culture, namely working remotely by utilizing existing technology. This has the effect of increasing crime and cyber attacks as more and more devices are connected to the internet for work. Therefore, the priority on security and monitoring of network infrastructure should be increased. The security and monitoring of this infrastructure requires an administrator in its management and configuration. One administrator can manage multiple infrastructures, making the task more difficult and time-consuming. This research implements infrastructure as code for security automation and network infrastructure monitoring including IDS, honeypot, and SIEM. Automation is done using ansible tools to create virtual machines to security configuration and monitoring of network infrastructure automatically. The results obtained are automation processes and blackbox testing is carried out and validation is carried out using a User Acceptance Test to the computer apparatus of the IT Poltek SSN Unit to prove the ease of the automation carried out. Based on the results of the UAT, a score of 154 was obtained in the Agree area with an acceptance rate of 81.05% for the implementation of infrastructure as code for the automation carried out
User Interface and Exprience Gamification-Based E-Learning with Design Science Research Methodology

In 2020, the Islamic Elementary Teacher Working Group (KKG MI) held an E-Learning Training for Islamic Elementary School Teachers in DKI Jakarta about one of the gamification applications, Quizizz. According to observation, many teachers are still perplexed when utilizing the Quizizz program. This is due to the application’s design and different functionalities, which still appear complicated to some teachers who aren’t used to using it. The existing gamification application is also considered not to meet the learning needs at Islamic elementary schools in Jakarta. This study intends to analyze and design User Interface (UI) and User Experience (UX) designs for gamification-based e-learning applications as solutions to the problems found. Data collection begins with an observation and also a literature study, questionnaires, and interviews. For the design, Design Science Research Methodology (DSRM) is used, which consists of six stages: Problem Identification &amp; Motivation, Define the Objective for a Solution, Design &amp; Development, Demonstration, Evaluation and Communication. The results of the evaluation of the gamification-based e-learning design designed with the User Experience Questionnaire (UEQ) and Task Success show that the e-learning design is considered attractive and users can interact with e-learning effectively and easily.
Clustering Couples of Childbearing Age to Get Family Planning Counseling Using K-Means Method

&#x0D; &#x0D; &#x0D; &#x0D; Couples of Childbearing Age (CCA) in the Madiun Regency have increased in the last three years. It caused the population in Madiun to overgrow with the newborn, which implies the economic, social, and environmental aspects. This study aims to cluster villages in Madiun with CCA case studies instead of birth control participants who will give birth and want children to determine the priority of getting Family Planning (in Indonesia, namely Keluarga Berencana/KB) counseling. K-Means clustering is used in this study because it has a linear space of complexity that can be executed quickly and easily. The result of this study is four (4) CCA clusters. CCA cluster 1 is a very high level of giving birth and wanting children, consisting of 7 villages. CCA cluster 2 is a high level of giving birth and wanting children with 119 villages. CCA cluster 3 is a medium level of giving birth and wanting children in 50 villages, and CCA cluster 4 is a low level of giving birth and wanting children, including 34 villages. So, cluster 1, which includes seven villages, is the most prioritized to get Family Planning counseling because it is the CCA cluster with the most birthing rate and wants children. This research obtained a silhouette coefficient of 0.42, which belongs to the medium level.&#x0D; &#x0D; &#x0D; &#x0D;
The Improvement of Artificial Neural Network Accuracy Using Principle Component Analysis Approach

An important problem in a classification system is how to get good accuracy results. A way to increase the accuracy of a classifier system is to improve the number of input data attributes. Improving the number of input data attributes can be done using the Principal Component Analysis (PCA) method. The aim of this research is to reduce the number of input data attributes to increase the accuracy in a mushroom classification system. The research method used in this study started from collecting datasets from Kaggle.com related to mushroom-classification, then the data visualization process was carried out using pie charts then a dimension reduction process was carried out to reduce the number of variables using the PCA method. The next step is the training and testing of the artificial neural network. The architecture of artificial neural network used is backward error propagation with the number of hidden layers as much as 2 layers with the number of cells as many as 3 and 2. The training data used is 80%, while the testing data is 20%. Based on the test results, obtained an accuracy of 100% with 150,000 iterations and using 11 input variables from 22 existing input variables. By adding Principal Component Analysis part of the development that can improve the accuracy and performance of Artificial Neural Networks
Automatic Door Access Model Based on Face Recognition using Convolutional Neural Network

Automatic door access technology by utilizing biometrics such as fingerprints, retinas and facial structures is constantly evolving. The use of masks during the Covid-19 Pandemic and post-pandemic has become an obligation wherever humans are active. The study aimed to create an automated door access model using Convolutional Neural Network (CNN) algorithms and Amazon Rekognition as cloud-based software. The CNN algorithm is applied to classify faces wearing masks or not wearing masks. The CNN architecture model uses sequential, convolution2D, max polling 2D, flatten dan dense. The hardware includes the Raspberry Pi, USB Webcam, Relay, and Magnetic Doorlock. The test results were obtained from the results of the accuracy plot on the Convolutional Neural Network model with an accuracy rate of 99% at an epoch value of 8 with a learning time of 67 seconds.
Soil Survey, the Profession I Embraced: a Few Pages from my Tour Diary

On 2022 World Soil Day (WSD), the author shares his experiences in soil surveys since his early days till date. Soil is the beginning of food, as mentioned in the year 2022 theme for WSD. Soil survey is the beginning of soil research regarding pedology, edaphology, and soil biology. The author delves into his experiences from different states, villages, and landscapes to identify varied soils. He argues about the grouping of soils and their utility in edaphology. Fieldwork, laboratory work, data generation, and dissemination are all critical; soil survey is the foundation of all such research activities. Fieldwork is strenuous, but in the long run, it's rewarding. The tour diary of the author describes the formation of spatially-associated Vertisols, Alfisols and Mollisols; besides, mention of Mollisols (brown forest soils) has been made the Histosols and their considerable capacity to be the hub of organic carbon which could be utilised as a model to combat climate change and global warming using artificial intelligence (AI). This soil database may serve as an essential engine for a negative emission strategy to combat global warming and assist land degradation neutrality (LDN). Starting his career in the Western Ghats, journeying through the tortuous paths of many terrains in the Satpura, Vindhyan, Himalayas, Northeastern regions and the southern Peninsula, the author returns to the same place at the end of his career, in the Western Ghats. He busy in research and continuing has been his quest for science.
Comparison of Memory usage between REST API in Javascript and Golang

Various mobile devices have limited memory, thus it must be used as effectively as possible. As a result, apps that will operate on mobile devices must take memory usage efficiency into account. The REST API, which is typically used to connect several applications that utilize different types of technology so that the applications can be connected, is one sort of technology that is currently commonly used to construct mobile applications. Javascript and Golang are the types of technology used to create the REST API. Undoubtedly, each of these technologies offers a unique performance. Research that can give a broad overview of the variations in the impact of memory resource utilization between Javascript and Golang is therefore required. In this work, two REST APIs are created using Javascript and Golang by researchers utilizing an experimental quantitative methodology. Following that, the memory utilization of the two REST APIs was evaluated using the exact same two types of datasets obtained from console.cloud.google.com. There was a difference in memory consumption between Javascript and Golang after the Wilcoxon test, t-test for paired data, and equivalence test, but the difference was essentially inconsequential (practically insignificant).
GIS Flood Prone Agricultural Land East Java Using Multi-Method Attribute Utility Theory

East Java has various regional conditions. The condition of the area certainly has the potential for disasters that have a significant impact on the agricultural sector. Flood is one of the factors that damage agricultural land. Flood risk management plays an important role in guiding the government in making timely and appropriate decisions for flood rescue and relief. The purpose of this research is a study of flood risk assessment in the agricultural sector in East Java using Multi Attribute Utility Theory. The Multi Attribute Utility Theory is used to solve problems related to spatial planning and disaster management because it is systematic and suitable for solving complex problems such as the agricultural sector. The results showed that the agricultural land areas in East Java with the category of very flood-prone include Bojonegoro, Lamongan, Tuban, and Sidoarjo Regencies. Furthermore, the results of this study were visualized by mapping flood risk using a GIS. This can be used for efforts in flood disaster management. This research is expected to assist policy making at the Department of Agriculture and Food Security in monitoring flood-prone agricultural land in order to minimize the occurrence of flood disasters in the agricultural sector.
The Application of Repeated SMOTE for Multi Class Classification on Imbalanced Data

One of the problems that are often faced by classifier algorithms is related to the problem of imbalanced data. One of the recommended improvement methods at the data level is to balance the number of data in different classes by enlarging the sample to the minority class (oversampling), one of which is called The Synthetic Minority Oversampling Technique (SMOTE). SMOTE is commonly used to balance data consisting of two classes. In this research, SMOTE was used to balance multi-class data. The purpose of this research is to balance multi-class data by applying SMOTE repeatedly. This iterative process needs to be applied if the number of unbalanced data classes is more than two classes, because the one-time SMOTE process is only suitable for binary classification or the number of unbalanced data classes is only one class. To see the performance of iterative SMOTE, the SMOTE datasets were classified using a neural network, k-NN, Nave Bayes, and Random Forest and the performance measures were measured in terms of accuracy, sensitivity, and specificity. The experiment in this research used the Glass Identification dataset which had six classes, and the SMOTE process was repeated five times. The best performance was achieved by the Random Forest classifier method with accuracy = 86.27%, sensitivity = 86.18%, and specificity = 95.82%. The result of experiment present that repeated SMOTE results can increase the performance of classification.
A. P. UMANSKY AND L. R. KYZLASOV: COMMON CAUSE AND DESTINY (BOOK NOTES AND DEDICATORY INSCRIPTIONS)

The professional and personal relationships of A. P. Umansky and L. R. Kyzlasov are shown in the documentary material of the author’s dedicatory inscriptions and the text of the ofcial review published for the frst time.
The Analysis of Foreign Language Teaching Textbook Tasks

Due to the development of modern information technology, the structure of foreign language textbooks is becoming more complex. On the other hand, the learning needs of modern learners are wider than they were before. The rationale of this study is the need for a close analysis of textbook exercises and assignments, which are key units in the implementation of language training programs. Inthe framework of this article, we aim at analyzing the English textbook exercises of General comprehensive school of Mongolia and calculate the results. In order to fulfill the purpose of the research, the objectives include to study the theoretical basis of the analysis of foreign language textbook exercises, carry out a close analysis in "English 3" textbook exercises, and to calculate the results. This model of the close analysis of foreign language textbook exercises which was suggested by Littlejohn in 1998 comprises the following components: 1. Students activities 2. Communication in the classroom 3. Content of exercises and tasks. This model reveals the information about the role of students, classroom communication and curriculum content. Thus, our study has shown that this model of the close analysis of foreign language textbook exercises can be used for selecting appropriate textbooks and for improving the textbook design in teaching practice.
Efektivitas buku cerita bergambar berbasis budaya lokal untuk peningkatan ketrampilan membaca

&lt;p class="15"&gt;The background of this research is because the students' reading comprehension ability is still not in accordance with basic competencies. Reading learning media for fourth grade elementary school children makes children bored and difficult to concentrate. The teacher's creativity in making or determining learning media does not suit children's interests. The teaching materials for Local Culture-Based Picture Story Books for Learning Reading Comprehension Skills for Class IV Students are not yet available. The research method is quantitative research in the form of experimental research. Data collection techniques with tests. The research subjects were students at SDN 1 Kebloran and SDN 2 Kebloran. Data analysis used the Independent Sample test and the Paired Sample Test. The results of the effectiveness analysis on the pre test were 21.23 and the post test was 34.27. The sig value is 0.000 &amp;lt;0.05 so that it indicates an effect on effectiveness or in other words Ho is rejected and Ha is accepted. The conclusion of this study shows that the development of local culture-based picture story book media is effective for teaching students' reading comprehension skills.&lt;/p&gt;
Analisis Kesulitan Belajar IPS dan Upaya Penanganan pada Siswa Kelas V Sekolah Dasar

&lt;em&gt;&lt;span lang="EN-GB"&gt;This study aims to describe the social studies learning difficulties and the handling efforts of the fifth grade students of SD Negeri Mangkubumen Kidul. The method in this research is descriptive qualitative research. The approach in this research is a case study. The subjects of this study were 28 students V and it was found that there were 11 students with scores below the KKM. Data collection techniques used in this research are document study analysis, observation, interviews, questionnaires, and documentation. The data analysis technique uses the Miles-Huberman interactive analysis model. Activities in data analysis include collecting data, reducing data, presenting data, and drawing conclusions. The validity of the data in this study uses triangulation of sources and techniques. The results showed that 11 students scored below the KKM (Minimum Completeness Criteria) on the theme 6, 7, and 8 theme test questions. Material difficulties related to the influence of human interaction and the role of society with the natural environment, names of heroes, arrival and resistance against western nations, British colonials, Dutch colonials, economic activities, and forms of business. Based on the data analysis of the factors that cause students to have difficulty learning Social Sciences because they are not interested, a lot of material, a lot of memorization, difficult questions, easy to forget, limited learning resources in schools, limited use of learning media, lack of parental assistance. The efforts made by the teacher are to give special attention and re-explanation of the material to students who do not understand the material. Efforts made by parents are to remind children to study, provide facilities in the form of the internet, and bring in tutors or include children in tutoring. Efforts made by students are asking teachers, parents, siblings, and tutors for material, looking for material in books and the internet.&lt;/span&gt;&lt;/em&gt;
Analisis kesalahan penggunaan bahasa dalam karangan teks eksplanasi peserta didik kelas V SD

The purpose of this study was to identify and describe the forms of language use errors in the form of spelling, diction, and sentences and to determine the factors of language use errors in explanatory text compositions for fifth grade student at SDN Tegalayu Surakarta. The research is a qualitative research with a case study approach that focuces on a phenomenon.The data collection techniques used were document analysis, observation, and interviews. Test the validity of the data used data sources triangulation and technical triangulation. The data analysis technique used is interactive analysis. The most errors in language use were found in spelling errors with 80.37%, followed by diction errors 14.27%, and sentence errors 5.36%. Factors causing errors in the use of language come from two factors, factors from the teacher in the form of writing learning strategies that are too simple and not doing an analysis of essay errors and factors from students in the form of students lack of understanding of the rules of language use, lack of student vocabulary, and lack of motivation to write. So that teacher can provide many example of good essay before writing and repeated writing exercise.