Reviewerly/exHarmony huggingface dataset:
Implementasi Akuntansi Melalui Pelatihan Dasar Kepada Siswa Smp Pelita Cemerlang Pontianak

The purpose of this activity is to provide an increase in students' knowledge and abilities in the field of basic accounting as well as evaluate the shortcomings possessed by students in terms of the field of accounting. The method of activity carried out uses lecture methods, practice methods and evaluation methods. Participants of the activity came from all students of Pelita Cemerlang Junior High School in the eighth grade which amounted to 66 students where four students were not present on the day of implementation. Based on the results of the examination of the results of work practice answers conducted by pelita Cemerlang junior high school students, there are 80 percent who have the ability to answer and solve problems well. The results of this basic accounting training activity received a very good response because the 8th Grade Junior High School students were very careful to follow and listen to every process that was carried out. This activity is expected to have sustainability with the improvement of accounting materials provided so that the development of students' knowledge and abilities is increasingly widespread
(De-)Randomized Smoothing for Decision Stump Ensembles

Tree-based models are used in many high-stakes application domains such as finance and medicine, where robustness and interpretability are of utmost importance. Yet, methods for improving and certifying their robustness are severely under-explored, in contrast to those focusing on neural networks. Targeting this important challenge, we propose deterministic smoothing for decision stump ensembles. Whereas most prior work on randomized smoothing focuses on evaluating arbitrary base models approximately under input randomization, the key insight of our work is that decision stump ensembles enable exact yet efficient evaluation via dynamic programming. Importantly, we obtain deterministic robustness certificates, even jointly over numerical and categorical features, a setting ubiquitous in the real world. Further, we derive an MLE-optimal training method for smoothed decision stumps under randomization and propose two boosting approaches to improve their provable robustness. An extensive experimental evaluation on computer vision and tabular data tasks shows that our approach yields significantly higher certified accuracies than the state-of-the-art for tree-based models. We release all code and trained models at https://github.com/eth-sri/drs.
Pengembangan dan Implementasi Sistem Informasi Tiga Tema Pada Kemen-LHK

The integrated information system solution is one example of a solution from information technology which is currently very helpful for humans in processing data and presenting a report that is precise, fast and accurate. One example of a much-needed information system is the forest area management information system managed by the Ministry of Environment and Forestry. The information system is managed by the Directorate General, there are a number of systems that can be used to build a system used in management, supervision and control, namely an information system related to areas, deforestation and licensing, including the management of environmental permits through Amdal.net. This research was conducted with a two-method approach, namely a field study conducted by direct analysis of the system that is currently running where the system will later be integrated into a three-theme information system and literature study. which is done by collecting informationrelated to the forest area management system including Amdal.net. The result of the research is the application of the Three Themes Information System which is an integration of: Forest Area, Licensing and Deforestation Themes. The Ministry of Environment and Forestry can benefit from this three-themed system, namely the integration of mapping of several forest areas that is integrated with permits and deforestation. This web-basedsystem was built using the PHP 7.4 programming language with the Code Igniter framework and the MariaDB database.
The Use of Scientific Organisation Methods of Labour in the System of Work of Design and Technology Teachers

The relevance of the study is conditioned by the need to implement solutions that contribute to the development of schools and institutions, acting in changed organisational conditions, working using methods of scientific organisation of labour in the system of work of Design and Technology teachers. Solutions that allow organising the learning process using such methods contribute to the implementation of didactic and educational tasks defined by schools and educational institutions. The purpose of these measures is to ensure the implementation of the main curriculum, taking into account the limitations arising from the specifics of the activities being carried out. In the current circumstances, the key issue is reasonableness and consideration of the current state of the organisation of subject training, considering the correct approach to the material provided to students, instructions, and tasks. The purpose of the study is to consider effective methods of scientific organisation of labour in the system of work of Design and Technology teachers. The theoretical and methodological basis of the study consists of the following methods: correlation, empirical, and component analysis. It is important to constantly develop the skills in this area, use the wide variety of modern technologies dedicated to this activity, overcoming the technological barrier. Organisation and planning are one of the main conditions for the effectiveness of any conscious and purposeful activity of a teacher, especially long-term ones, throughout the school year. The system of work of a Design and Technology teacher distinguishes the tasks assigned to such a teacher in an educational institution in the context of the performed functions. The teacher should certainly take into account the tasks that follow from the analysis of the provisions of the educational process that regulate the sphere of activity of a school teacher. The practical significance lies in the productive use of methods of scientific organisation of labour in the system of work of Design and Technology teachers
Rancang Bangun Aplikasi Persediaan Barang pada Toko Endo Tani

ABSTRACT - In this modern era, technology is developing rapidly in various aspects of life, where technology that is already known for its effectiveness has also begun to be widely used both from the education sector, government, and in the trade sector. Endo Tani shop is a type of trading business that sells various types of agricultural fertilizers, which is located at Jl. Parakan - Trajaya Blok Rabu RT/RW 004/005 Parakan Leuwimunding Village. As for the problems that exist at the Endo Tani Store, the data processing of incoming goods and outgoing goods is still using a manual system, namely by writing in books or on paper that has been provided, the data search process becomes constrained and inefficient because they have to search first in the document. This is of course less effective and efficient, considering that paper bags can be damaged or lost, which allows inventory data to be lost. Therefore, there is a need for a solution to these problems, namely designing a computerized inventory system. In the process of collecting data with the aim of solving problems, the authors use primary data sources, namely (Observation and Interview). The software methodology used for development is the prototype method, this inventory system is built using the PHP (Hypertext Preprocessor) programming language and the data is stored in a MySQL database. The final result obtained in this study is an inventory application that is expected to help and facilitate shop owners in processing goods data, searching for goods, and being able to produce the information and reports needed quickly, precisely, and accurately.
Weakly Supervised Representation Learning with Sparse Perturbations

The theory of representation learning aims to build methods that provably invert the data generating process with minimal domain knowledge or any source of supervision. Most prior approaches require strong distributional assumptions on the latent variables and weak supervision (auxiliary information such as timestamps) to provide provable identification guarantees. In this work, we show that if one has weak supervision from observations generated by sparse perturbations of the latent variables--e.g. images in a reinforcement learning environment where actions move individual sprites--identification is achievable under unknown continuous latent distributions. We show that if the perturbations are applied only on mutually exclusive blocks of latents, we identify the latents up to those blocks. We also show that if these perturbation blocks overlap, we identify latents up to the smallest blocks shared across perturbations. Consequently, if there are blocks that intersect in one latent variable only, then such latents are identified up to permutation and scaling. We propose a natural estimation procedure based on this theory and illustrate it on low-dimensional synthetic and image-based experiments.
BLOGGING AND E-LEARNING PLATFORM WITH COMPANY PORTFOLIO

In this paper we will focus on Blogging and ELearning platform for the member of organization. This platform aims to provide a platform for organizations to build a digital presence for their members. It can be used for any type of organization. Members will be able to configure a personal website or blog on the platform. The platform will provide the ability for the organization to configure how the platform is presented, including branding and background images. Organizations need to provide a blogging environment as a platform for the members. To achieve this, organization need to have a platform with which they could build a custom blogging environment. This platform should be able to create an environment for the members.
GBC: An Efficient and Adaptive Clustering Algorithm Based on Granular-Ball

Existing clustering methods are based on a single granularity of information, such as the distance and density of each data. This most fine-grained based approach is usually inefficient and susceptible to noise. Inspired by adaptive process of granular-ball division and differentiation, we present a novel clustering approach that retains the speed and efficiency of K-means clustering while out-performing time-tested density clustering approaches widely used in industry today. Our simple, robust, adaptive granular-ball clustering method can efficiently recognize clusters with unknown and complex shapes without the use of extra parameters. Moreover, the proposed method provides an efficient, adaptive way to depict the world, and will promote the research and development of adaptive and efficient AI technologies, especially density computing models, and improve the efficiency of many existing clustering methods.
Pengaruh Penguasaan Kosakata dan Minat Baca terhadap Kemampuan Menulis Teks Deskriptif Siswa

This research is a qualitative research on Indonesian language education, especially on the influence of vocabulary mastery and reading interest on the ability to write descriptive texts. This study aims to determine the effect of vocabulary mastery and reading interest together on the ability to write descriptive texts of State Vocational High School students in Kebumen Regency. In addition, it also aims to determine the effect of vocabulary mastery on the ability to write descriptive texts of State Teacher High School students in Kebumen Regency. The next objective was to determine the effect of reading interest on the ability to write descriptive texts of State Vocational High School students in Kebumen Regency. The method used in this study is a survey method with multiple linear regression correlational approach with a sample of 65 students. The results showed: There is a significant effect of vocabulary mastery and reading interest on the ability to write descriptive texts at the State Teacher Training School in Kebumen Regency. This can be seen from the results of statistical calculations carried out and analyzed in this study. From the description of the data after the correlation analysis, the correlation coefficient is 42.7% and the determination coefficient is 40.8%. After testing with the SPSS program, it is proven that the correlation coefficient is significant. This means that there is an effect of vocabulary mastery and reading interest together on the ability to write descriptive text. Keywords: Vocabulary mastery, reading interest, ability to write descriptive text.
Sosialisasi Self-Efficacy dan Motivasi Belajar IPA Peserta Didik Kelas VIII di SMPN 2 Gerung Berdasarkan Gender

Self-efficacy basically has a close relationship with students' learning motivation. Where between male and female students, of course, there are some differences in the level of self-efficacy and learning motivation. Therefore, it is necessary to make efforts to build self-efficacy and learning motivation of students, one of which is by carrying out socialization activities, especially in science learning. The method used consists of several steps, namely the stages of preparation, implementation, and evaluation. Based on the results obtained, the self-efficacy of male students was much higher than that of female students with an average score of 83% in the very high category. As for learning motivation, female students have a higher average than male students, where the average is ≥83% in the very high category. So it can be concluded that self-efficacy and learning motivation of students are interrelated, but have a slight difference if data collection is carried out based on gender.
Event-Based Motion Segmentation of Small Objects in the Wild

Event-based cameras are sensitive to brightness changes and can capture rich temporal information with very high temporal resolution, which has great potential for motion segmentation of moving objects. Under static background, events are only triggered by motion of objects, thereby moving objects can be easily segmented. However, in many real-world applications, events are also be triggered by the motion of camera or background and submerge the ones corresponding to moving objects. In this letter, we propose an event-based motion segmentation method to segment moving small objects in events obtained from the wild. First, motion estimation is performed to align the events triggered by the background. Then, candidate events corresponding to moving objects or moving backgrounds are detected. Finally, motion information is adopted to segment the events of moving small objects from the ones triggered by the background. In addition, we develop the first dataset for event-based motion segmentation of small objects, namely EMSS. Experimental results demonstrate the effectiveness of our method and show that our method can achieve robust motion segmentation of small moving objects in the wild.
Innovative Nature of the 21st Century Criminology

The aim of the current article is to study the development trends of criminology, also taking into account the impact of Covid-19 pandemic. The rationale for the innovative criminological approach is related to new types of criminal threats and their consequences. Certain forms and types of traditional crime in postmodern society are transforming into the digital environment, including through the use of DarkNet platforms. At the same time, criminological research in Latvia is insufficiently developed, criminology study courses are not included in all law study programmes. In the 21st century, new criminological approaches and schools are emerging, including neocriminology, synergistic, narrative, digital, neurocriminology. Appropriate criminological approaches have a specific nature and content. These trends confirm that, despite the importance of criminology, there is a need for research into the development trends of organized crime, cybercrime, trafficking in human beings, drugs and arms, and the possibilities for combating and preventing them. It would also be necessary to develop specialized criminology study programmes.
Determining Factors of International E-Tutoring

&#x0D; Purpose: Virtual Exchange (VE) enables geographically separated collaboration without the need for physical travel and the use of resources like time and money. The complexity for students participating in VE modules can be reduced by using e-tutors as learning facilitators. In this context, we focus on determining factors for e-tutorial support in international collaborations in higher education and thus cross-cultural and cross-border collaboration of learners in the sense of VE.&#x0D; &#x0D; &#x0D; Study design/methodology/approach: This paper aims to answer the question “Which determinants impact e-tutoring during collaborative and international Virtual Exchange modules?”. Therefore, the results are compiled, analyzed, and synthesized with the help of a Systematic Literature Review (SLR) according to Okoli &amp; Schabram (2010). &#x0D; &#x0D; &#x0D; Findings: The result is a concept matrix of 41 identified determinants of international e-tutoring in higher education, divided into six main categories: responsibilities, competencies, communication, organization, pedagogy, and prerequisites. The results allow a more precise separation of e-tutors activities in VE modules and thus offer concrete proposals for differentiating, improving, and scaling the role of the e-tutor. &#x0D; &#x0D; &#x0D; Originality/value: Students' demand to acquire global skills becomes more and more common. VE modules offer the potential to meet this demand if delivered correctly. Previous research in this field partially covers determining factors of e-tutoring, but there is a lack of a concise overview that can serve as a basis for improvement. &#x0D;
ConFUDA: Contrastive Fewshot Unsupervised Domain Adaptation for Medical Image Segmentation

Unsupervised domain adaptation (UDA) aims to transfer knowledge learned from a labeled source domain to an unlabeled target domain. Contrastive learning (CL) in the context of UDA can help to better separate classes in feature space. However, in image segmentation, the large memory footprint due to the computation of the pixel-wise contrastive loss makes it prohibitive to use. Furthermore, labeled target data is not easily available in medical imaging, and obtaining new samples is not economical. As a result, in this work, we tackle a more challenging UDA task when there are only a few (fewshot) or a single (oneshot) image available from the target domain. We apply a style transfer module to mitigate the scarcity of target samples. Then, to align the source and target features and tackle the memory issue of the traditional contrastive loss, we propose the centroid-based contrastive learning (CCL) and a centroid norm regularizer (CNR) to optimize the contrastive pairs in both direction and magnitude. In addition, we propose multi-partition centroid contrastive learning (MPCCL) to further reduce the variance in the target features. Fewshot evaluation on MS-CMRSeg dataset demonstrates that ConFUDA improves the segmentation performance by 0.34 of the Dice score on the target domain compared with the baseline, and 0.31 Dice score improvement in a more rigorous oneshot setting.
Creative Potential and Orientation of the Personality of the Student-HR Manager

The chapter examines the relationship between the personality's focus on achieving success or avoiding failures in professional activities and the creativity of student-future HR managers. The results of a ten-year study of students of the Faculty of Sociology and Management of Ryazan State University named after S.A. Yesenin are presented. Various methods were used to analyze the peculiarities of students' perception of their future professional activity in the context of considering it as professional creativity. The dependence of the conditional level of creative potential and motivation to solve previously unknown professional and creative tasks was determined, as well as barriers blocking the achievement of the goal were identified.
Review of various Models in the Field of Sentiment Analysis

This article provides a case study of all sentiment analysis-based deep learning models. One of the most important studies in natural language processing is sentiment analysis, which is frequently employed in politics, news, and other sectors. Given the large number of products purchased through ecommerce websites, it makes sense to drive clients to web pages that showcase the greatest products with the highest ratings and reviews. The notion of sentiment analysis aids in the translation of feedback into numbers, but it also aids in determining whether feedback is favourable or negative in deep learning models. The SLCABG model, for example, combines a large vocabulary with the advantages of deep learning methods. To begin, sensory vocabulary was employed to improve the review's emotional features. It then applies attention to weights and extracts fundamental emotion and contextual data from the review using CNNs and Gated Recurrent Units (GRUs). The SLCABG model improves on the inadequacies of classic sentiment analysis models for product reviews by using sensory vocabulary and deep learning techniques. This approach can also be used to enhance the surfing experience, particularly for websites that track user sentiment. Keywords: SLCABG model, CNN, BIGRU, GRU, Sentiment analysis
Learning logic programs by combining programs

The goal of inductive logic programming is to induce a logic program (a set of logical rules) that generalises training examples. Inducing programs with many rules and literals is a major challenge. To tackle this challenge, we introduce an approach where we learn small non-separable programs and combine them. We implement our approach in a constraint-driven ILP system. Our approach can learn optimal and recursive programs and perform predicate invention. Our experiments on multiple domains, including game playing and program synthesis, show that our approach can drastically outperform existing approaches in terms of predictive accuracies and learning times, sometimes reducing learning times from over an hour to a few seconds.
Penerapan Media Pembelajaran Interaktif untuk Meningkatkan Motivasi dan Hasil Belajar IPS

The rapid development of science and technology today causes the flow of information to be fast and without limits. This allows all parties to obtain information quickly, easily, and abundantly from various sources and places where they are located. The purpose of this study was to determine the effect of interactive learning media on increasing students' motivation and learning outcomes on the content of Social Sciences (IPS) lessons and so that teachers can learn more concrete information that is abstract. This study used an experimental method, carried out in class V SD Negeri 1 Kutoarjo, and the sample was taken as many as 38 students. The results showed an increase in learning motivation of 0.74 with high interpretation, critical thinking ability of 0.72 with high interpretation, and student learning outcomes of 0.35 with medium category. The application of interactive learning media can increase the motivation and learning outcomes of fifth graders at SD Negeri 1 Kutoarjo for Social Studies Lessons.