Reviewerly/exHarmony huggingface dataset:
Need Analysis for Designing Administrative Services Websites for Students

Administrative services to students play an important role at the university. Optimal administrative services to students can increase university competitiveness. One effort that can be made is to provide digital and online based service facilities to make the service process easier. However, currently, there are still administrative services at universities that are not digital and online based, which causes problems. The research method starts from requirements and analysis. The aim of the research is to analyze needs for problems in the field as a reference for designing administrative service websites for students. Data were collected using questionnaires and interviews at Educational Technology Study Program, Universitas Negeri Padang. The research results show that students need website-based administration services to handle the administration of letters to departments. The results of this research provide a solution for study programs to the problems they face
The effectiveness of using the software application "geogebra" in the construction of sections

The article provides training in cross-section construction using the GeoGebra software application. In the construction of sections of the GeoGebra software application, the conditions of spatial shapes and bodies of rotation, as well as their coordinate transfer, are fully studied. In order to determine whether students can show the image of sections on spatial bodies, a survey of 24 students on the topic of sections was conducted in Grade 10 "B" of the specialized boarding school "Daryn" in Kentau.In the survey, students were asked to draw a cross-section through given points on parallelepipeds and pyramids. As a result of the survey, it was found that the vast majority of students cannot show cross-section images. In order to compensate for the shortcomings, it was chosen to interpret cross-section imaging for Class 10"B" using the "GeoGebra" software. Effective uses of the "GeoGebra" software have paid off within the prescribed time frame. In particular , we can see an increase in the quality of education by 50% and 86%. Students analyze, prove the idea of change through the visualization process and, as a result, showed a positive conclusion. As a result of the test from students of the 10th grade "B", which was in-depth in the direction of physics and mathematics, the effectiveness of the GeoGebra software was clearly demonstrated.
Male and Female’s Speaking Abilities Differences in Debating Context

This study analyzed the differences in male and female speaking skills such as organization, opinion, rebuttal, sentence structure, and fluency in debate activities. This study used descriptive-qualitative methods and collected the data by using observations, audiovisual recordings, and interviews. As a result, male students were better than female students in constructing speeches, presenting their arguments, responding to opponents, organizing sentences, lexical hedges, and intensifiers in their sentences, and speaking their own words fluently. They could understand the main points, rephrase sentences, use reinforcing words, and sometimes produce pauses. On the contrary, female students were unsuccessful in delivering the main points, using unfinished sentences, repeating the sentences, using lexical hedges and intensifiers, and producing frequent pauses in debate activities. Thus, teachers should use different methods in teaching, assessing, and measuring the speaking ability of male and female students in debate activities, particularly in Speaking classes.
Penerapan Model Pembelajaran Examples Non Examples Untuk Meningkatkan Kemampuan Menulis Puisi Siswa Kelas VIII SMP Negeri 5 Gunungsitoli

The purpose of this study was to improve the poetry writing skills of grade VIII students of SMP Negeri 5 Gunungsitoli using the Examples Non-Examples Learning Model. This Classroom Action Research (PTK) activity is carried out in two cycles using quality and quantitative data analysis. The subjects of this study were 31 students of grade VIII-A SMP Negeri 5 Gunungsitoli. Data collection techniques using tests and non-tests consist of observation and interviews. The results of this study show that there is an increase in the ability to write poetry through the examples non examples learning model. It can be seen in the first cycle that the average score of students was 69.35 with a very good category of 19.35%, a good category of 41.94%, a sufficient category of 29.03%, and a less category of 9.68%. In the second cycle, the average score of students was 76.13 with a very good category of 38.71% and a good category of 61.29%. Based on the results of the study, the application of the Examples Non-Examples Learning Model can improve the poetry writing skills of grade VIII - A students of SMP Negeri 5 Gunungsitoli
IMPLEMENTATION OF BLOCKCHAIN TECHNOLOGY IN SCHOOLS

The purpose of this study was to determine the level of understanding of schools with blockchain technology. The method used in this research is a literature study approach. Data collection through library research. Based on research data, researchers understand that the application of blockchain-based technology in schools plays a very important role because it makes it easier for teachers to teach, makes it easy for students to understand the material with a simple design, and makes teaching more effective and can control students well. Apart from this, blockchain makes it easy for transactions to pay school finances quickly and all data is recorded neatly without having to record it one by one.
ASUHAN KEPERAWATAN PADA PASIEN GAGAL GINJAL KRONIK DENGAN HEMODIALISA MELALUI TINDAKAN KOMPRES DINGIN PADA AV SHUNT

Hemodialysis is an intervention designed to assist patients in managing fluid and electrolyte metabolism. The hemodialysis process involves puncturing the arteriovenous (AV) shunt area to facilitate dialysis. The repeated punctures in this area can result in pain. Research Objective: To provide an overview of nursing care for chronic kidney failure patients undergoing hemodialysis through the use of cold compresses on the AV shunt site. Method: This study is a case study with a medical-surgical nursing care approach. The research was conducted from February to March 2023 on two chronic kidney failure patients undergoing hemodialysis. Results and Discussion: After the intervention of applying cold compresses to patients I and II, a reduction in pain scale was observed. For patient I, the pain scale decreased from 6 (0-10) before the intervention to 3 (0-10) after the intervention. For patient II, the pain scale decreased from 5 (0-10) to 3 (0-10) after the intervention. Conclusion and Recommendations: Cold compresses can effectively reduce pain at the AV shunt puncture site in hemodialysis patients. Therefore, it is recommended to incorporate cold compress interventions for patients undergoing hemodialysis.
Digital Transformation of High School Education: Microlectures and Instructional Design in Teaching Mathematics

The first and second authors contributed equally. The authors acknowledge the Jiangsu College Students Innovation and Entrepreneurship Training Programme (No.202310324115Y) and the Education and Teaching Reform Programme of the Yancheng Normal University (No. 2023YCTCJGY18; 15YCTCJY033). Abstract With the rapid development of digital technology nowadays, education and microlecture resources have become increasingly popular and enriched, in accordance with the more personalized needs of diverse schools and students. In high schools, traditional classroom teaching is also undergoing digital transformation. This paper therefore discusses the common features, production procedure and dissemination channels of microlectures. It then demonstrates the design of a modified microlecture-based teaching process, taking the exponential function as a high-school mathematics example. The flexibilities and possibilities of such digital tools for high-school mathematics are also explored, which are followed by the discussion on potential issues that may arise in the classroom, and the impacts of microlecture innovations on students, teachers, and other education stakeholders. Keywords: Microlecture; Digital Education; High-School Mathematics; Educational Equity DOI: 10.7176/JEP/14-34-02 Publication date: December 31 st 2023
Knowledge Sharing in Higher Institution: A Nigeria Post-Secondary Technical Institution Case Study

In the ever-changing landscape of education, the integration of Information and Communication Technologies (ICT) has emerged as a transformative force, reshaping traditional teaching methods and enhancing learning experiences. This study delves into the complexities of ICT adoption in Nigerian higher education, focusing on post-secondary technical education programs or National Diploma and Higher National Diploma (ND/HND) awarding institutions. The significance of this study lies in addressing challenges faced by developing nations like Nigeria, where harnessing ICT-driven education could resolve pressing issues in the educational sector. The study identifies multifaceted challenges hindering ICT adoption, such as inadequate funding, lack of infrastructure, and resistance from faculty members. It emphasizes the pivotal role of knowledge sharing in higher education, underlining its significance in fostering continuous learning, collaboration, critical thinking, and innovation. Integrating ICT tools, supported by a robust digital infrastructure and tailored training programs, can mitigate these challenges. The study explores prominent knowledge-sharing models and theories, comprehensively understanding knowledge dissemination within post-secondary technical institutions. It emphasizes collaborative learning environments, ICT integration, and supportive policies as critical factors in enhancing knowledge exchange. The findings underscore the urgent need for policies that empower, technologies that enable, and mindsets that inspire. By addressing these challenges comprehensively, policymakers, educators, and stakeholders can create an educational landscape where every student and educator can thrive in the digital age. The insights from this research guide the evolution of post-secondary technical institutions in Nigeria and offer universal principles for educational institutions worldwide. The vision of a future with equal access to quality education for all is attainable through collaborative efforts and a commitment to embracing the potential of technology in higher education. Keywords: Higher Education, ICT, National Diploma and Higher National Diploma, Nigeria DOI: 10.7176/IKM/13-7-01 Publication date: December 31 st 2023
Penerapan Algoritma K-Medoids pada Pengelompokan Wilayah Provinsi di Indonesia Berdasarkan Indikator Pendidikan

Cluster analysis has the goal of grouping data that has the same characteristics into the same cluster and data that has different properties will enter into different clusters. K-Medoids is a grouping method using a representative object as the center point (medoids). The k-medoids method was developed to overcome the weakness of the k-means method which is sensitive to outliers because an object with a large value allows it to deviate from the data distribution in size. After grouping using k-medoids, the results of the grouping were validated. The cluster validation method using the Silhoutte Coefficient (SC) is a method that can be used to see the quality and strength of clusters that combine cohesion and separation methods. This study aims to obtain the optimal cluster from the largest SC value and determine the grouping results of the optimal clusters that are formed. This grouping method is applied to data on education indicators in Indonesia in 2020. Based on the results of the analysis, it is found that the optimal cluster is 2 clusters with a SC value of 0.464, where cluster 1 has 14 provinces and cluster 2 has 20 provinces.&#x0D; &#x0D; Keywords: K-Medoids, Silhoutte Coefficient, Educational Indicators
Perancangan Sistem Informasi Manajemen Berbasis Website Pada Program Studi Teknik Industri Universitas Mulawarman

The current advancement in information technology has had a significant impact on information provision and management. The presence of the internet as the primary medium for accessing information has become a fundamental necessity in modern society. In the context of higher education, the Industrial Engineering Program is not exempt from challenges in disseminating and efficiently managing information. Vital information often gets scattered and is difficult to access, especially when conveyed through conventional methods such as physical bulletin boards or WhatsApp messages. This research is conducted using in-depth interviews with various stakeholders, including program chairs, administrative staff, faculty, and students. The findings of this research strongly indicate the need for the development of a more efficient information management system within the Industrial Engineering Program. As a proposed solution, a website will be developed with various key features, including announcement management, curriculum information, schedule management, administrative management, guidance management, and document archiving. The implementation of this system is expected to address several identified issues, such as limited accessibility to important information and inefficient management. Thus, the operational efficiency of the Industrial Engineering Program is expected to be significantly enhanced. The results of this research highlight the importance of adapting information technology in the constantly evolving context of higher education. In an era where information technology continues to advance, efforts to utilize it optimally in information management within educational institutions like the Industrial Engineering Program remain highly relevant. An efficient information management system can provide substantial benefits in enhancing the quality of information management within the Program
Comprehensive Review of Benefits from the Use of Sparse Updates Techniques in Reinforcement Learning: Experimental Simulations in Complex Action Space Environments

This paper presents a comprehensive exploration of the advantages associated with the utilization of sparse update techniques in Artificial Neural Networks (ANNs) within the context of Reinforcement Learning (RL). The study leverages simulations with environments featuring complex action spaces and wide state spaces, characterized by state vectors of dimension 128 and a choice of 9 distinct actions. The research investigates the impact of different update frequencies in ANNs when applied to RL agents in these simulation environments. The experimental methodology entails testing ANN updates after each action executed by the RL agent, followed by evaluations at progressively less frequent intervals. To assess the effectiveness of these techniques, several critical attributes are compared across simulations. These attributes encompass the collected rewards by the RL agents, the number of actions required to accomplish specific tasks within the complex environments, and the computation time necessary to achieve task completion. The study reveals that the optimal update frequency for RL agents using ANNs varies depending on the specific simulation environment. Some environments benefit from more frequent updates, while others perform better with fewer updates. However, excessively sparse updates can lead to performance drops. These findings emphasize the importance of adaptable update schedules tailored to each RL task, which can significantly enhance RL algorithm design in complex environments with wide action and state spaces.
Survey on Big Data and Cloud Computing: Storage Challenges and Open Issues

The convergence of Big data (BD) and cloud computing has considered as a prominent topic in the IT field, driven by the production of vast amounts of data from diverse sources. Cloud computing is a storage and resource management technology, reduces the cost of storage requirements. The large sets of data, commonly referred to as BD, pose significant challenges in terms of processing and analysis. This study provides a comprehensive review of the utilization of cloud computing for BD processing by introducing BD definitions, main characteristics, and classifications alongside discussions on cloud computing. The research summarizes open research issues related to the integration of BD and cloud computing.
Address Generation and Transaction Simulation in Blockchain

The encryption algorithms that are used in the blockchain are of particular importance for its security. In the current development, the different algorithms for encryption, generation of keys and addresses for secure data transfer, and carrying out transactions in wallets are considered. Two main algorithms for generating addresses in blockchain are considered - RSA and DGK. Tests have been made to generate reliable addresses under different input parameters for both algorithms. The research was done with the Cryptool software product.
Application of Augmented Reality in Creating Added Value for an ERP System

Augmented reality (AR) is one of technologies that lately brings its potential to society. At the same time, all the positive features brought by digital transformation and industry 4.0 are trying to be united in order to create even more added value to a business. Since ERP systems are the foundation of every business, research into the application of augmented reality in the context of ERP systems has great importance and represents an interesting scientific and practical problem. In addition to identifying benefits, opportunities, limitations and application area of using augmented reality in ERP systems this paper also presents one proof of concept (PoC) scenario implementing an augmented reality mobile application for showing 3D models through which extended functionality of ERP system can be achieved and new business value can be created. During development, methodological approach based on extreme programming (XP) was used.
Comparison of Standard and Modified Ant Colony Algorithm with Fuzzy system for Path Planning of Robot in Complex Environment

The requirements of optimizing path planning for the autonomous robot are in high demand in such industrial communities, especially in manufacturing and caring social support. The application of meta-heuristic methods in autonomous problems is considered because of their adaptivity and robustness. Ant Colony Optimization (ACO) is one of the researchers’ approaches because of its effectiveness in the ant community. However, some constraints are making this method less productive. Therefore, this paper is to generate a modified ACO combined with Fuzzy logic (ACOFL) to minimize its drawbacks and maximize the robustness of path planning. This study presents the role of ACO algorithms in Path Planning, especially in the complex aspect, through the theoretical background of ACO and the other combination with other algorithms. The improved mathematics model evaluation demonstrates the upgrade steps in the path-finding process. Simulation results shows that the modified ACO algorithm is effective for complex environment compare to standard ACO algorithm. Moreover, the comparison results are presented in this paper between the standard ACO and modified ACO algorithm.
Identifying Near-Duplicate Pairs in Exams: Similarity Detection Using Kshingling, Minhashing, and LSH

In the field of data mining, identifying near-duplicate documents is a key challenge. This task, crucial for detecting cheating in online exams, can be approached using techniques from Natural Language Processing: Shingling and Minhashing. Furthermore, using the Locality Similarity Hashing (LSH) approach refines the process by focusing on high-probability document comparisons. This paper introduces a novel method that combines K-shingling, Minhashing, LSH, to uncover near-duplicate pairs in online exams. Experimental results highlight the success of this integrated approach in enhancing detection accuracy, ultimately strengthening the capability to address academic dishonesty.
Cloud Infrastructure Monitoring Using Splunk: Expectations and Challenges

Monitoring cloud-based IT infrastructures is a challenging task. Monitoring provides low-level metrics from Docker instances to higher-level application-specific metrics provided by multi-services, databases or applications log files. The observed metrics and information can be assessed to trigger policies aiming at the automation of complex management tasks within a cloud environment. This study aims to improve the current body of knowledge regarding the monitoring of applications deployed within AWS cloud environment. A case study regarding setting up a monitoring platform, namely Splunk. We conclude that monitoring should focus not only on application logs but also on tracking issues related to the containerized infrastructure. We report also on the expectations and challenges from the industry to shed light on future research directions.
Data Protection during Hardware-software Mobile Signal Transmission of Earth-moving and Construction Machines' Sensors in Multiservice Network

This paper discusses the factors affecting data security transmitted from earthmoving and construction machines sensors' in multiservice networks. Various methods for data protection, their strengths and weaknesses are considered. Authors analyzed trends in this area and developed their own algorithm for searching for software bookmarks in telecommunication equipment code to exclude using ones in order to gain data access by equipment suppliers and third parties. The paper presents results of software testing from various manufacturers for Linux and Windows operating systems using several existing analyzers and the developed system. Assessment of the time spent on searching for vulnerabilities using the developed subsystem and other searching tools is given.
Intelligent system for online Hand Gesture Prediction

Humans may engage with computers in a natural way by using hand gestures to carry out a variety of tasks. However, elements like the hand's complexity, Gesture structures, differences in hand size, posture, and ambient illumination can all have an impact on how well hand gesture recognition systems perform. Due to recent advancements in deep learning, picture recognition algorithms now perform significantly better. Real-time picture segmentation is essential for many uses of autonomous vehicles. Due to recent advancements in deep learning, picture recognition algorithms now perform significantly better. The Deep Convolutional Neural Network has shown improved performance in visual representation and classification, especially when compared to traditional machine learning methods. In this study, a Convolutional Neural Network (CNN) for hand gesture detection is proposed. In order to quantitatively increase the size of the dataset and provide the resilience required for a deep learning approach, data augmentation is initially utilized, which randomly moves photos both horizontally and vertically to an extent of 20% of the original dimensions. A gesture can be used to convey both an activity or an emotion. Also included are sign language and body language. The static and the dynamic are the two different categories of gestures. The former use nonverbal cues like a raised hand or body language to communicate. The latter can communicate certain ideas through body language and hand gestures. In order to determine the user's intent, the gesture or movement of the body or body components is recognized.