Reviewerly/exHarmony huggingface dataset:
Pengaruh Model Pembelajaran Berbasis Masalah berbantuan Chatbot AI terhadap Higher Order Thinking Skill

This study aims to determine the effect of problem-based learning models assisted by AI chatbots on higher-order thinking skills in Class IV at SDN 1 Genteng Kec. Genteng, Kab. Banyuwangi, East Java. This type of research uses a quantitative approach with a quasi-experimental research method and a Non-equivalent Control Group Design. Non-probability sampling was used. The population and sample consisted of 33 students in class IV-A as the experimental class and 39 students in class IV-B as the control class in SDN 1 Genteng, Kec. Genteng, Kab. Banyuwangi, East Java. The data-collection instrument used a written test in the form of multiple choices and descriptions. Data analysis techniques using SPSS Statistics 21. The results of the study showed that problem-based learning models assisted by AI chatbots affected learning outcomes. Other results using problem-based learning models assisted by chatbot AI are different from those obtained using conventional models. The improved learning outcomes based on the N-Gain score of problem-based learning models assisted by AI chatbots is 56.1545, and that of conventional models is 21.0266. It can be concluded that the use of problem-based learning models assisted by AI chatbots is effective in elementary school learning.
Deep k-Means Node Clustering Based on Graph Neural Networks

Recently, graph node clustering techniques using graph neural networks (GNNs) have been actively studied. Notably, most of these studies use a GNN to embed each node into a low-dimensional vector and then cluster the embedding vectors using the existing clustering algorithms. However, since this approach does not consider the final goal of clustering when training the GNN, it is difficult to say that it produces optimal clustering results. Therefore, in this paper, we propose a deep k-means clustering method that iteratively trains a GNN considering the final goal of k-means clustering and performs k-means clustering on the embedding vectors generated by the trained GNN. The proposed method considers both the similarity between nodes and the loss of k-means clustering when training a GNN. Experimental results using real datasets confirmed that the proposed method improves the quality of k-means clustering results compared to the existing methods.
MODELING OFA SYSTEM FOR ASSESSING THE QUALITY OF CAREER GUIDANCE OF APPLICANTS UPON ADMISSION TO A UNIVERSITY

Issues related to student management have always been one of the most important for both universities and the labor market of the regions in question. In the article, the importance of managing the process of conducting career guidance work by universities is confirmed, and problems arising in the career guidance systems of universities are identified. The main goal of this study was to build a mathematical model for assessing the quality of professional guidance of applicants for specific specialties at a university and to simulate the process of admission to a university using the Matlab &amp; Simulink system. As a result of the study, a model based on Buchanan's club theory was proposed. To represent the actual utility function, it is proposed to use an approximating nonlinear relationship. It is based on the beta distribution function (developed by the authors). The construction of the type of marginal utility dependence is based on a meaningful analysis of regulatory documents, plans and development strategies of the university, region, country, statistical reports, and demographic forecasts. As a result of the simulation, six variants of system behavior (career guidance for applicants) using the Kalman filter under the influence of various factors were considered. The best option for the applicant's professional guidance has been determined. This is when a school graduate, having decided on his specialization, attended courses (organized by the university) to pass final exams. In these courses, teachers took into account the students’ preparation and adjusted the training program at each stage. In this case, the applicant showed the best results in the entrance exams. The scientific novelty of the proposed model lies in the application of a system-adapted dependence based on the beta distribution function. The proposed mathematical model can be used to support decision-making by universities during the planning of career guidance activities based on the conclusions obtained in the process of simulating the behavior of the system under consideration.
Metode Peningkatan Literasi pada Pendidikan: Analisis Bibliometrik pada Publikasi 2013 – 2023

This study aims to determine the conditions in the range of 2013-2023 related to the scientific map, publication trends, and thematic research coverage of literacy learning methods in education, especially articles published in Scopus, Google Schoolar, and Crossref indexed journals. The research process focused on the following questions: (1). How are literacy improvement methods in education seen from the publication map; (2). What is of interest to academics regarding literacy improvement methods in education? and (3). What topics are often written about in publications related to methods of improving literacy in education? In addition to the research and data sources to be used in the bibliometric analysis, 1200 articles were found through the keywords "literacy, education" in the "article title &amp;; abstract" published in Scopus, Google Schoolar and Crossref indexed journals. To explore and identify the main thematic areas and topics that appear in the publications using keyword occurrence analysis. To support the data analysis and visualization process obtained from Harzing's Publish or Perish and VOSviewer applications. The results of this study show that the method of improving literacy in education is a research trend that has been in great demand in the last 10 years and is still growing. In the visualization section, the high keyword density is presented in 8 clusters, namely: (1) literacy; (2) student; (3) study; (4) ability; and (5) technique. Bibliometric analysis in the form of mapping provides information about the development pattern of publications in the field of literacy in education. These findings provide contributions for future research: 1) The need for holistic research on improving literacy in education; and, 2) the need for in-depth research that focuses on one or several themes that are still rarely studied such as: (1) literacy culture; (2) early age; (3) student response; (4) literacy numeracy; (5) scientific literacy skills; (6) literacy tree; (7) culture and (8) habituation. Keywords: methods, literacy, education
Factors Influencing Consumer Satisfaction in Online Shopping: A Case of College Level Students

Purpose - The purpose of this study is to examine the influence and relationship between product quality, information availability, and shipping cost with customer satisfaction among college-level students in Kathmandu Valley.&#x0D; Design/methodology/approach – This research adopted the explanatory research design. The study targeted college-level students in Kathmandu Valley as a population. A total of 400 respondents were selected from the different colleges by using a convenience sampling technique. The questionnaire survey was applied to collect primary data. The study adopted cross tab, independent t-test, and correlation to analyze the data.&#x0D; Findings - The study shows that customer satisfaction is influenced and associated with product quality, information availability, and shipping costs in online shopping. The availability of information is a major factor in customer satisfaction with online shopping. Online shopping companies must uphold reliable websites, ensuring accurate and up-to-date information about products and services to attract potential customers. Additionally, they need to maintain the standard of quality for retaining existing customers and meeting their expectations in enhancing the company's reputation.&#x0D; Research limitation/implications - The study examines only three explanatory variables i.e., product quality, availability of information, and shipping cost so that future researchers can study other factors impacting customer satisfaction among college-level students of Kathmandu Valley in different geographic concentrations with new analytical tools.&#x0D; Originality/value –The study targeted college-level students of Kathmandu Valley as population. The study is based on the Technology Acceptance Model (TAM), developed by Fred Davis in 1986 to measure the results.
Application of the PIECES Framework Method in E-Report Evaluation

The evaluation of the E-report application at SMK N 1 Banyudono is integral for assessing its alignment with the latest curriculum guidelines and its effectiveness in meeting students' learning and assessment needs. This evaluation ensures that learning support technologies, such as E-report, stay relevant, responsive to user needs, and supportive of the school's long-term educational objectives. Using the PIECES method, the assessment of user satisfaction comprehensively considers Performance, Information, Economy, Control, Efficiency, and Services indicators. The Likert scale aids in gauging user satisfaction across various aspects. Quantitative data analysis involves 26 respondents, including teachers, homeroom teachers, curriculum staff, and school principals, providing a holistic perspective on learning and assessments management. The PIECES method and Likert scale evaluation reveal a satisfaction level of 4.52, categorizing it as "SATISFIED." This comprehensive assessment covers system performance, information accuracy, cost-effectiveness, system control ease, time efficiency, and service flexibility. The qualitative descriptive approach using the PIECES method and Likert scale identifies areas for improvement, ensuring the E-report application remains efficient, relevant, and aligned with DITJEN VOKASI guidelines
Effects of Explicit Language Instruction on Students’ Vocabulary Retention and Reading Comprehension Skills

The study investigated the effects of explicit vocabulary instruction on students’ vocabulary retention, and on their reading comprehension in 11th grade at Shinta Preparatory School, Gondar. The study was a quasi-experimental in design. Out of the five sections, two sections (11th C= and 11th E=: a total of 93 students) were randomly selected. Explicit instruction was used for the experimental group whereas conventional methods were used for the control group. In addition, vocabulary retention and reading comprehension tests were used to collect data. Accordingly, the results of the independent sample t-test showed that there was a statistically significant difference between the experimental, and the control groups in their vocabulary retention (P &lt; 0.05, i.e., p = 0.003), and in their reading comprehension (p &lt; 0.05, i.e., p = 0.000) respectively. Similarly, a paired sample t-test was used to compare post-test, and delayed post-test results. The result of the comparison showed that the experimental group retained more vocabulary than the control group since the mean difference between the tests was close to zero (i.e., 0.120) and p &gt; 0.05. Finally, the overall test results indicated that explicit instruction improved students’ vocabulary retention and reading comprehension than conventional methods. Thus, the findings from this study pointed out that explicit vocabulary instruction was one of the most effective methods for improving students’ vocabulary retention and reading comprehension.
Effects of Cohesion Analysis-Based Instructions (CABI) on English as Foreign Language (TEFL) Students’ Reading Comprehension and Self-Efficacy

This study examined effects of CABI on grade 11 EFL students’ reading comprehension and self-efficacy using reading self-efficacy as mediating variable at Azezo Secondary School, Gondar City Administration. The study employed a quasi-experimental design with quantitative approach. Thus, intact groups were selected using simple random sampling technique, and one out of these groups was assigned as an experimental group (n=52) while the other as a control group (=52) by lot; both of them were selected using lot method. Then, the experimental group was taught using CABI, whereas the control one was taught using conventional way of teaching reading. In order to collect the data, reading comprehension test and reading self-efficacy questionnaire were used as data collecting instruments. The data were analyzed using chi square, independent samples t-test and SEM. The results of the study indicated that there was a direct significant difference (B = 1.781, CR = 5.844 (&gt;±1.96), p &lt; .05) between the control and experimental group students’ reading comprehension posttest scores in favor of the experimental group participants. Besides, the result showed that there is significant effect (β = .533, CR = 4.630 (&gt;±1.96), p &lt; .05) of CABI on experimental group students’ reading self-efficacy beliefs posttest score in comparison to the control one. In the same vein, the result (β = .825, CR = 3.855(&gt;±1.96), p &lt; .05) unveil that CABI had positive effect on experimental group participants’ reading comprehension posttest score through reading self-efficacy compared to the control group students. Hence, the instruction has a positive effect on reading comprehension both directly and indirectly (through reading self-efficacy). This implies that reading self-efficacy partially mediates the causal relationship between CABI and reading comprehension.
Development of an Innovative Air-Ground Carrier Platform for Multi-mode Drones

The air-ground drone, capable of both ground movement and aerial flight, exhibits enhanced flexibility and adaptability to different environments. In comparison to existing technological solutions, this paper proposes an air-ground drone capable of automatic switching between automotive and flying modes. The drone employs a screw-rod linkage mechanism to drive the retractable and extendable motion of four rotor arms. Through meticulous torque and speed calculations, only a small-sized reduction motor is needed to simultaneously drive the automatic retraction and extension of all four arms. This paper outlines the overall structure and operational principles of the air-ground drone, providing a detailed exploration of the design and core component selection for the screw-rod linkage mechanism. The presented solution serves as a design approach for similar amphibious drone configurations.
Rekognisi Huruf Tulisan Tangan Menggunakan Convolutional Neural Network

The development of technology in the field of computer vision in recent years with the application of Technological developments in the field of computer vision in recent years with the application of convolutional neural networks have shown sophisticated performance with a high level of accuracy, such as object detection. The problem in the world of computer vision that has been looking for a solution for a long time is object classification in general images. How to duplicate the human ability to understand images, so that computers can recognize objects in images like humans. Therefore, the need for deep learning is one branch of machine learning where the algorithm used is inspired by the workings of the human brain. Some people may be more familiar with Convolution Neural Network. CNN is used to recognize and classify patterns in handwriting. The network assumes that the input used is an image. The network has a special layer called the convolution layer. In this layer, the images are inserted according to the predefined filters. In this study, various combinations of CNN architectural designs were carried out such as the number of convolution layers, stride size, number of epochs, type of kernel size optimizer. The research data comes from the National Institute of Standards and Technology (NIST) database, then the data is divided into three, namely 60% training data, 20% validation and 20% testing. The results of this experiment produce a very good accuracy value using 2 convolution layers, 50 epochs, with Adam optimizer producing an accuracy value of 99.5% when testing the model. Then evaluate the model using the confusion matrix, assigning a high value with an average value of 100% accuracy, while for the average value of precision with a value of 100%, for an average recall value of 100%, and finally an average value of f1 score of 100%.
EXPERIENCE IN PREVENTING PROFESSIONAL AND PEDAGOGICAL DIFFICULTIES OF FUTURE TEACHERS

The article discusses the problem of professional and pedagogical diffi culties of future teachers and overcoming them. The results of a survey of senior students about the reasons that make it diffi cult for them to communicate with students are analyzed, which confirmed that one of the most important reasons for professional and pedagogical diffi culties is the lack of developed pedagogical communication skills among future teachers. The article presents the results of a survey of 4th year students of the Faculty of Foreign Languages of the South Ural State Humanitarian and Pedagogical University who completed teaching practice. The authors of the article also analyzed the diaries of student interns, presented based on the results of industrial (teaching) practice in the 4th year. The authors identifi ed and presented in the text of the article the diffi culties that students encountered during their internship. The article describes the experience of working with students in the format of a workshop, which is educational in nature and aimed at preventing professional and pedagogical diffi culties of future teachers. The content of optional educational meetings with students, aimed at gaining them new knowledge about the features of communication between various subjects of education and applying this knowledge in practice, is described in detail. It is stated that the introductory stage of the workshop contributed to the formation of a positive psychological climate in the group and the development of self-presentation and self-presentation skills, the main stage of the work made it possible to introduce students to modern technologies of effective psychological-pedagogical interaction in theory and practice, and the fi nal stage, dedicated to micro-teaching, contributed to the deepening of methodological training future teachers and developing their self-reflection skills. It is concluded that the work carried out will allow future teachers to skillfully build relationships with various subjects of the educational process and overcome professional and pedagogical diffi culties. The authors consider the activation of such forms of work with students as the analysis of problem situations and microteaching as the most promising areas for using the experience of preventing professional and pedagogical diffi culties of future teachers.
Intuitionistic fuzzy operations and operators: Some observations

Since its inception, the concept of intuitionistic fuzzy sets is getting popularity day by day. In addition to several operations, so many operators are there to excel the development of this thought. Few of such operators have been focused here. The key objective of this paper is to study those operators over intuitionistic fuzzy sets and to explore some major properties on it.
Hyperparameter Optimisation of Reinforcement Learning Algorithms in Webots Simulation Environment

Reinforcement learning (RL) has shown great potential for solving complex mobile robotic tasks. However, developing RL algorithms that can perform effectively on a variety of robotic systems and environments can be challenging. In this paper a RL hyperparameter optimisation framework is presented, which designed to be flexible, scalable, and adaptable to various mobile robot scenarios. The proposed framework is built on top of the Webots simulation environment, which provides a realistic 3D physics engine for simulating different mobile robots. Stablebaselines3 is utilized, which is a popular RL library, to train and evaluate RL agents. Moreover, to address the challenge of hyperparameter tuning, a genetic algorithm-based hyperparameter optimization technique is incorporated to automatically tune the hyperparameters of the RL agents. The effectiveness of the proposed framework is demonstrated on two different mobile robot scenarios, including inverted pendulum balancing, and target tracking. The results show that the proposed framework can be used and achieves state-of-the-art performance in all of the scenarios. The proposed framework can provide a solid foundation for developing and testing RL algorithms on mobile robots and has the potential to accelerate the development of intelligent robotic systems.
Quantum Imprecise Bayesian Networks (QIBN) for Modelling Socio-Ecological-Technical Systems under Uncertainty

Socio-ecological-technical systems are dynamic ecosystems composed of natural and man-made elements, whose interactions are affected not only by the natural environment, but also culture, personal behaviour, politics, economics and social organisation. These systems must be resilient to respond systemically to shocks and stresses. To cope with the inherent uncertainty of load effects and resistances, safety analyses are often performed through risk-based methods. An interesting tool is represented from Bayesian Network (BN), a probabilistic graphical model useful for risk-informed decision making. A notable example of socio-ecological-technical systems is represented by urban ecosystems. They rely on infrastructures that are not stand-alone and are dependent on other systems (environmental, cyber, physical, and human) to which they are interconnected, i.e., forming a system of systems. Moreover, empirical findings show that humans tend to violate the expected utility metric and consequently violate the laws of Classical Probability (CP). Thus, novel methodologies are necessary to model, understand, and predict their dynamic responses. (ii) hidden interdependencies, where the variables of the BN can be dependent even if they are not linked nor sharing a common parent node, and (iii) human decision making under uncertainty. The promising features of QIBN are demonstrated through three benchmark examples of different nature: (a) two-stage gambling as an example of human decision making showing violation of the total probability theorem, (b) Structural Health Monitoring (SHM), and (c) damage monitoring through risk-informed digital twin technologies.
MICROSOFT 365 POWER POINT APPLICATION TRAINING AT COMDEV BINUS FOSTERY COMMUNITY

Presentation is one activity that has an important role in today's modern world. Conveying ideas and ideas in the right way can generate understanding and maintain audience interest. The importance of mastering the use of presentation applications is the basis of training for the community so that they bring more benefits to everyday life, both in work, education and social activities. The Microsoft 365 Power Point Application Training which was held on February 24, 2021 is expected to have an impact on community empowerment, especially by equipping them with mastery of the Power Point application that can be used at work.&#x0D;
Extending the Planning Poker Method to Estimate the Development Effort of Parallel Applications

Since different Parallel Programming Interfaces (PPIs) are available to programmers, evaluating them to identify the most suitable PPI also became necessary. Recently, in addition to the performance of PPIs, developers’ productivity has also been evaluated by researchers in parallel processing. Some researchers conduct empirical studies involving people for productivity evaluation, which is time-consuming. Aiming to propose a less costly method for evaluating the development effort of parallel applications, we proposed modifying the Planning Poker method in this paper. We consider a representative set of parallel stream processing applications to evaluate the proposed modification. Our results showed that the proposed method required less effort for practical use than the controlled experiments with students.