Reviewerly/exHarmony huggingface dataset:
Wakaf Produktif Sumber Mata Air Sebagai Upaya Mewujudkan Kesejahteraan Umat Berdasarkan Undang-Undang Nomor 41 Tahun 2004 Tentang Wakaf

Society in general considers waqf limited to immovable objects that are used for the common good. For example, land used to build mosques, Islamic boarding schools, schools, cemeteries, and so on. In fact, apart from having a religious spiritual dimension, waqf is actually an Islamic teaching that is beneficial for the welfare of the people. This study aims to describe the waqf of springs as an effort to realize the welfare of the people. This study used qualitative research methods. The data is sourced from primary and secondary data which is processed and analyzed in a descriptive-analytical manner. The results of the study show that water sources can also be used as legal waqf objects. However, it should be underlined that the waqf is a source of water or wells, and not the water itself. This is because water is classified as something that can be consumed / utilized so that it cannot be used as a waqf object. In contrast to wells or water sources that can always flow and provide benefits. In a sense, this water waqf is used for public and religious purposes, such as bathing, drinking, and ablution.Keywords: waqf, water sources, welfare, people.
Decission Tree Sebagai Metode Penentuan Penjurusan Perguruan Tinggi Berdasarkan Minat Dan Bakat Melalui Data Raport Dengan Uji Algoritma C4.5 (Studi Kasus di SMKN 1 Donorojo Pacitan)

The decision tree method is built using data with variable input, rapot value, gender, and age of SMKN 1 Donorojo learners with label corners. Furthermore, the concept of C4.5 algorithm became one of the techniques in the formation of decision trees. In the procedure, the selection of attributes as a branch in the C4.5 algorithm uses the calculation results of the gain ratio. Based on the concept of calculations designed, the C4.5 algorithm is used in building decision trees in providing recommendations for learners at the college level. This research will qualitatively analyze the implementation of the decision tree method in determining student direction by using the C4.5 algorithm of data mining in the form of a gain ratio of rapot values, interests and talents of students. From the results of the C4.5 decision tree algorithm test can make more accurate predictions in the research of the management of majors and major recommendations for learners. The existence of these methods is expected to be able to provide solutions for students and schools concerned in determining the appropriate majors for students to pursue to the opportunity for success and improve the ability to study in college. C4.5 algorithm itself uses an induction approach where in this approach, the C4.5 algorithm. Divide data based on the criteria selected to create a decision tree.Keywordsâ€”: Decision tree, direction determination, C4.5 algorithm
Organization of mentoring as a necessary condition for managing the quality of education

The article reveals the essence of mentoring, gives a description of its forms and methods. Since the middle of the 20th century, mentoring has acquired the character of a mass movement – mentoring in secondary school, as one of the forms of methodological work, is defined as the help of an experienced teacher to a young specialist or trainee “to adapt to new conditions of activity, to consolidate a number of primary skills necessary in these conditions.” In the twentieth century, it was possible to separate mentoring in the professional and educational spheres, and in the twenty-first century, these boundaries are blurring. The paper focuses on the main models of mentoring, such as traditional, partner, group, flash mentoring, speed, reverse and virtual mentoring. Also in the article attention is paid to the mentoring program implemented in the MBOU secondary school No. 196 in Novosibirsk
Perancangan aplikasi reservation room pada hotel xyz di Indramayu

Management for a business or business is really needed, including management in the hotel environment related to room reservations or room reservations. Room reservations made by consumers at a hotel are administrative matters, so it is necessary to have records or data that need to be stored and retrieved with the aim of being more useful information for the management. This research is an applied research that applies a system development method in the form of the SDLC (Software Development Life Cycle) method with the application of a prototype model. As for data acquisition, researchers use literature studies, observations, and interviews to obtain data in the form of problems that occur, and are called primary data. Meanwhile, in the application of the method using a prototype model, it is carried out in 3 phases, namely the planning phase (data analysis), the design and implementation phase, and the system evaluation phase. The results of this study are in the form of e-reservation room software that was tested in offline conditions. Hope this research can help the management at xyz hotel, especially in serving hotel room reservations.
Efektivitas Penerapan Aplikasi Edmodo Untuk Meningkatkan Literasi Digital Mahasiswa

This study aims to describe the effectiveness of implementing the Edmodo application and digital literacy for 5A semester students at the PGSD FKIP Study Program, Bengkulu University, for the Basic Concept of Dance. The research method used is action research conducted in 2 cycles. Data collection techniques are cognitive learning outcomes tests and digital literacy observations. Data analysis is using the classical absorption formula to analyze the effectiveness of learning and percentage techniques to analyze digital literacy. The results in this study were the classical absorption in cycle 1 was 73.75% and increased in cycle 2 by 85%. Digital literacy in cycle 1 is in the moderate category of 14.29%, good 63.64%, and very good 18.18%, increasing in cycle 2, namely 18.18% good category and 81.82% very good. Based on this, it can be concluded that the application of the Edmodo application is effective and can improve students' digital literacy.
PEMANFAATAN APLIKASI QUIZIZZ SEBAGAI INOVASI MEDIA PEMBELAJARAN DI MASA PANDEMI COVID-19 BAGI GURU SD NEGERI 101877 TANJUNG MORAWA

The purpose of this study was to determine the use of the Quizizz application in learning during the Covid-19 pandemic for teachers at SD Negeri 101877 Tanjung Morawa. This type of research uses a descriptive qualitative approach. This research was conducted at SDN 101877 Tanjung Morawa. The research subjects were teachers and students of grade V SD Negeri 101877 Tanjung Morawa. Data collection techniques in this study were obtained from the results of observations, interviews, documentation and filling out questionnaires by students. The results of online learning research using the Quizizz application are that learning becomes fun, increases focus in learning, is more enthusiastic, and stimulates students to understand questions better and makes it easier for teachers to analyze students' questions and answers.
Characteristics of professional competencies of computer science teacher in digital learning environment: digital competence

Relevance. Digital technologies are presently widely used in general education. Formation of learners’ digital literacy is becoming an important issue. A special role is given to computer science teacher. There is a need for additional research into professional competencies of computer science teacher in the digital education environment, formation of digital competency, his/her readiness to become a tutor for schoolchildren in mastering digital skills. The means for formation of digital competence are practice-oriented assignments on the use of digital technologies in the pedagogical practice. The purpose of the paper is systematisation of tasks handled by the teacher in the digital education environment and development of recommendations for the formation of digital competence of the computer science teacher. Methodology and methods of research. The methodological basis of the research is represented by the ideas of systemic and competency-based approaches in defining the substance of digital competence and characterising the teacher’s success in digital education environment based on the formed digital competence, teacher’s readiness to become a tutor of schoolchildren in learning the digital world and formation of digital literacy. The research results are presented by the description of practice-oriented creative tasks aimed at the formation of digital competence of computer science teacher and systematised by digital proficiency areas according to the digital competencies groups. The scientific novelty, when developing the characteristics of digital competence of a computer science teacher, stems from the use of the notion of structure and content of learners’ digital literacy, the need for formation of digital competencies that would allow a computer science teacher to become a tutor for learners in mastering digital skills, in development of digital competence characteristics of a computer science instructor. The practical significance of the presented research results lies in the possibility of their use in developing the content of the communicative/digital module of pedagogical baccalaureate programmes, in the development of complementary professional education programmes ensuring the formation of teachers’ digital competence and development of their professional readiness for practical use of innovative educational models and digital technologies with a view to form the learners’ digital literacy, create a comfortable and safe learning environment.
Psychological Factors of Classroom Facilitative Management at Secondary School

the purpose of our research is to propose psychological factors of class-room facilitative management at secondary schools.methods of the research. The following theoretical methods of the research were used to solve the tasks formulated in the article: the categorical method, structural and functional methods, the methods of the analysis, systematization, modeling, generalization. Also in our research the statement experiment was used as an empirical method.the results of the research. We’ll identify the principles that should guide the teacher, who seeks to humanize interpersonal relationships with pupils: 1) from the very beginning and during the whole learning process the teacher needs to show the children his/her trust in them, in their personality; 2) pupils should be assisted in formulating and clarifying the goals and objectives that are formulated both for micro-groups and for each pupil individually; 3) we must always assume that pupils have an intrinsic motivation for the learning process; 4) the teacher should be a source of personal experience for pupils, which can always “be turned to” for the help of other people, be faced with difficulties in solving a problem; 5) it is important that this role is performed by the teacher in relations to each pupil; 6) the teacher should strive to develop the ability to feel the emotional mood of the micro-group and understand it; 7) we should strive to achieve empathic relationships that allow us to understand the feelings and the experiences of everyone; 8) the micro-group should actively demonstrate their feelings; 9) it is necessary to be an active participant in group facilitative interaction.conclusions. As a result of comparative studies, which in total surveyed 57 teachers and 92 pupils, we compared different performance indicators of teac-hers who had the ability to facilitate learning at different levels. The analysis of he behavior of pupils in the classes of teachers-facilitators showed that pupils were more proactive in the process of communication, they asked a lot of ques-tions. Pupils spend more time solving learning tasks and problems, show higher levels of cognitive functioning. Pupils are also less likely to miss classes, demon-strate higher academic achievements in all disciplines, steadily increase their IQ and creativity throughout the school year.
Language model compression with weighted low-rank factorization

Factorizing a large matrix into small matrices is a popular strategy for model compression. Singular value decomposition (SVD) plays a vital role in this compression strategy, approximating a learned matrix with fewer parameters. However, SVD minimizes the squared error toward reconstructing the original matrix without gauging the importance of the parameters, potentially giving a larger reconstruction error for those who affect the task accuracy more. In other words, the optimization objective of SVD is not aligned with the trained model's task accuracy. We analyze this previously unexplored problem, make observations, and address it by introducing Fisher information to weigh the importance of parameters affecting the model prediction. This idea leads to our method: Fisher-Weighted SVD (FWSVD). Although the factorized matrices from our approach do not result in smaller reconstruction errors, we find that our resulting task accuracy is much closer to the original model's performance. We perform analysis with the transformer-based language models, showing our weighted SVD largely alleviates the mismatched optimization objectives and can maintain model performance with a higher compression rate. Our method can directly compress a task-specific model while achieving better performance than other compact model strategies requiring expensive model pre-training. Moreover, the evaluation of compressing an already compact model shows our method can further reduce 9% to 30% parameters with an insignificant impact on task accuracy.
Multi-Knowledge Aggregation and Transfer for Semantic Segmentation

As a popular deep neural networks (DNN) compression technique, knowledge distillation (KD) has attracted increasing attentions recently. Existing KD methods usually utilize one kind of knowledge in an intermediate layer of DNN for classification tasks to transfer useful information from cumbersome teacher networks to compact student networks. However, this paradigm is not very suitable for semantic segmentation, a comprehensive vision task based on both pixel-level and contextual information, since it cannot provide rich information for distillation. In this paper, we propose a novel multi-knowledge aggregation and transfer (MKAT) framework to comprehensively distill knowledge within an intermediate layer for semantic segmentation. Specifically, the proposed framework consists of three parts: Independent Transformers and Encoders module (ITE), Auxiliary Prediction Branch (APB), and Mutual Label Calibration (MLC) mechanism, which can take advantage of abundant knowledge from intermediate features. To demonstrate the effectiveness of our proposed approach, we conduct extensive experiments on three segmentation datasets: Pascal VOC, Cityscapes, and CamVid, showing that MKAT outperforms the other KD methods.
Utilization of SAMR Model in the Delivery of Mathematics Instructions in the New Normal Learning Environment

The purpose of this study is to assess the utilization of SAMR model in the delivery of mathematics instruction in the new normal learning environment. Specifically, it assessed the utilization of SAMR Model on the delivery of mathematics instruction in the new normal learning environment by both students and teachers in terms of substitution, augmentation, modification, and redefinition; determined significant difference on the utilization of SAMR Model on the delivery of mathematics instruction: identified the problems encountered in the utilization of SAMR Model in the teaching and learning of mathematics; and proposed recommendations to maximize the utilization of the integration of SAMR Model in the promotion of digital literacy in the teaching and learning of mathematics. Descriptive method was used and 235 randomly selected teachers and students of mathematics during the second first semester of SY 20201-2022 participated in the survey. Questionnaire which was administered using Google Forms served as the main data gathering instrument. Results of which was organized and statistically treated using weighted mean and t-test. Results revealed from both students and teachers that substitution, augmentation, and modification were frequently utilized while redefinition was sometimes utilized. There is significant difference on the respondent’s assessment on the utilization of SAMR Model in terms of substitution but no significant difference in terms of augmentation, modification, and redefinition. The expressed recommendations were believed to help in the utilization of substitution, augmentation, modification, and redefinition in the teaching and learning of mathematics.
THE CORRELATION BETWEEN STUDENT’S READING STRATEGY AND READING COMPREHENSION OF SECONDARY SCHOOL

Reading strategies are procedures to assist students’ reading comprehension which play an active role in reading literacy. This quantitative study aims to find out the reading strategies mostly used by students and to find out the correlation between students' reading strategies and their reading comprehension. The research design used was correlational study. The total sample in this study was 74 ninth graders in one of junior high schools in Surabaya. The participants were chosen using the convenience sampling method due to the availability of the students. The data were collected by using Survey of Reading Strategies (SORS) questionnaire and reading comprehension test. The data were analyzed by using descriptive statistics to find out the strategy mostly used by students, and Pearson Product Moment to find out the correlation between variables. The results showed that the students often used Problem-Solving Strategy (M= 4), Global Reading Strategy (M= 3.04), and Support Reading Strategy (3.04). Furthermore, it was found that there was no correlation between the two variables (p-value= 0.790, &gt;0.05). According to the result, good reading strategy does not affect the reading comprehension correlation.
Automation of Real Estate Registration Using Block Chain Technology

Abstract: Online real estate Registration is a project which provides a friendly format to register land properties. Users can search and browse for property in this application. This application also allows users to see land details on online. This application mainly concentrates on maintaining and managing the details of the property. This application deals with lands details. Now-a-days all applications which require huge security are migrating their application to Block chain as Block chain inbuilt for security data. All existing techniques were not having any facility to check whether data store at decentralized (same data will be saved at multiple nodes and if one node hack or down then data will be gather from other working node) server is intact or change. To check data is intact we can use Block chain technology to maintain land registration details as this technology maintain tree to store each transaction (any data storage will be consider as transaction) and while storing new data then Block chain verify all transaction hash code and if data is not alter or hack then same hash code will be generated and verification will be successful and new block will be added and if data is changed then different hash code will be generate and verification will be failed which indicate node is hack.
THE NURSE IN THE CONTEXT OF TECHNICAL-LEVEL EDUCATION

Introduction: Teacher training encompasses a series of factors and circumstances of specific and pedagogical knowledge. In this process, teaching-learning is linked to the development of knowledge, skills and attitudes. In technical education, there are active methodologies for health courses, especially in nursing, however, several factors have hampered the quality of this education. In this line of thought, this study was developed from the existing problem of the various difficulties that the teaching nurse faces in the classroom at a technical level, from the perspective of the predisposing adversities for such circumstances, aiming to identify in the literature, scientific evidence about of the main challenges faced by nurses in teaching during the Covid-19 pandemic, in technical education. Methodology: This is an integrative literature review, of a descriptive-exploratory nature, carried out from bibliographic searches in the scientific databases: SCIELO, LILACS and BDENF. Results and Discussions: The main challenges for teaching encompass different circumstances, being them at a social and economic level, where the professional is not always supported by all the necessary resources to promote quality teaching, as well as the behavior and interest of students. , which for the most part does not play its current role. Conclusion: It was evidenced that the traditional teaching model does not always attract the attention and interest of students, making it necessary to implement new teaching practices that involve recreational and dynamic activities, especially with regard to remote online classes in periods of isolation.
A Huffman Code Based Crypto-System

A Compression Cryptosystem is a single coding process, the output of which is both reduced in space and secure against unauthorized decoding. Considering Huffman coding, this pa-per proposes to apply repeatedly minor changes to the compression model, with negligible deterioration of its optimality. The cumulative impact of a large number of such changes leads to completely different ciphertexts, which can be decoded only if a given secret key is known. The security of the system is based on the NP-completeness of a problem related to breaking the code. Several variants are suggested, and their results are tested in various settings, including for security against chosen plaintext attacks.
The Generalization of Fourier-transform and the Peter-weyl Theorem

This article is devoted to the generalization of the Fourier transform and harmonic analysis on compact Hausdorff groups, we construct the Fourier-Stieltjes calculus, which is associated with the semigroups on the Hilbert space.We obtain that let    
Adversarial Attack for Asynchronous Event-Based Data

Deep neural networks (DNNs) are vulnerable to adversarial examples that are carefully designed to cause the deep learning model to make mistakes. Adversarial examples of 2D images and 3D point clouds have been extensively studied, but studies on event-based data are limited. Event-based data can be an alternative to a 2D image under high-speed movements, such as autonomous driving. However, the given adversarial events make the current deep learning model vulnerable to safety issues. In this work, we generate adversarial examples and then train the robust models for event-based data, for the first time. Our algorithm shifts the time of the original events and generates additional adversarial events. Additional adversarial events are generated in two stages. First, null events are added to the event-based data to generate additional adversarial events. The perturbation size can be controlled with the number of null events. Second, the location and time of additional adversarial events are set to mislead DNNs in a gradient-based attack. Our algorithm achieves an attack success rate of 97.95% on the N-Caltech101 dataset. Furthermore, the adversarial training model improves robustness on the adversarial event data compared to the original model.