Reviewerly/exHarmony huggingface dataset:
Application of the Teams Game Tournament Model to Increase Biology Learning Activeness

Teachers and students need an adjustment period to adapt from distance learning to face-to-face learning. This condition raises problems in the teaching and learning process. The research used classroom action research as a research design for implementing the TGT cooperative learning method to increase the activeness of class X students in Biology learning. The learning activeness of Class X students in biology subject categorized as low. To improve it, the researcher utilized a fun method such as TGT. The research participants were sixteen class X MIPA SMA Islam 1 Surakarta students. Data collection techniques of the research used observation, questionnaires, and tests. Comparative descriptive statistics were used to examine the quantitative data, while critical analysis was used to analyze the qualitative data. The results of the data analysis presented that students' learning activeness increased to the high category (≥ 75%) with details of 75% visual activity, 76% verbal activity, 83% listening activity, 76% writing activity, 96% motoric activity, 89% mental activity, and 86% vigorous activity. These results arise due to the active role of students in the syntax of games and matches. Nature card media generate students' interest in learning, because contain picture-cued of surrounding natural phenomena in the student environment. The card's questions were scaled to the student's cognitive capacity level and impacted the student's self-awareness to care about the environment. It can be concluded that contextual learning of the environment change with the TGT model can increase student learning activity, especially in Biology lessons.
Factors Inducing the Adoption of Knowledge Management System (KMS) In SMEs, Large and Government Organizations. What Are the Intercepting Factors? A Systematic Review

This paper aims to develop a systematic exploration of the literature investigating the factors that influence the adoption of the knowledge management system (KMS) in organizations as well as identifying the intercepting factors between different types of organizations such as small-medium enterprises (SMEs), large corporation and government organizations. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) is used to structure the research field. The proposed research used filtering scientific papers published in Emerald Insight and Scopus from 2018 to 2022. This paper presents empirical evidence from six articles that identify intercepting factors between small-medium enterprises, large corporations, and government organizations. Among the factors analyzed, only IT capabilities were found to be common across all three types of organizations. The findings and analysis section includes a Venn diagram that illustrates other relevant factors that intercept between the organizations. The accumulation of reviewed research papers is necessary for academia and organizations to analyze the factors influencing the adoption of KMS. This study also will assist in providing information that will offer insights to organizations, particularly those in the small and medium enterprises (SME), large enterprises and government, in the process of implementing knowledge management.
Assessing Information Security Competencies of Firm Leaders towards Improving Procedural Information Security Countermeasure: Awareness and Cybersecurity Protective Behavior

Cybersecurity threats are a serious issue faced by many organizations in this new information era. Therefore, security leaders play a significant role not only to ensure that all their employees are practicing good security behavior to protect organizational information assets but also to ensure that security technology has been installed properly to protect network infrastructure. This study aims to examine cybersecurity protective behavior (CPB) among employees in the organization and focus on the role of leadership competencies and information security countermeasure awareness. The questionnaires were distributed via email and self-administered, and the study managed to obtain 245 responses. Partial Least Squares-Structural Equation Modeling (PLS-SEM) analysis was used to analyze the final data. Confirmatory factor analysis (CFA) testing shows that all the measurement items of each construct were adequate in their validity individually based on their factor loading value. Moreover, each construct is valid based on its parameter estimates and statistical significance. The research findings show that Procedural Information Security Countermeasure (PCM) awareness strongly influences CPB compared to a leader's information security competencies (ISI). Meanwhile, ISI significantly influences PCM awareness. This study adapts the theory of leadership competencies in the context of cybersecurity, which is particularly beneficial to any industry in improving organizational information security strategic plans.
A content analysis of mission and vision statement of NGOs: Focusing on Korean international development NGOs

Non-governmental organisations (NGOs) express their guiding principles and philosophy by defining their mission and vision. Mission and vision make obvious the social issues that NGOs seek to address. Using them wisely will help NGOs allocate their scarce resources better and improve communication with internal and external stakeholders. Despite the significance of mission and vision, more study focusing on NGOs is still needed. This study examines the mission and vision statements of NGOs working on international development in Korea. All KCOC (Korea NGO Council for Overseas Development Cooperation) member organisations’ missions and vision statements were reviewed for this. Based on the eight components of a mission statement identified by Pearce and David(1987), we examined the mission and vision statements of the international development NGOs in Korea. One of the key findings is that international NGOs and organisations with a lengthy history are more likely to have mission and vision statements. Secondly, the mission and vision statements comprise 4.1 components on average. The contents of the mission and vision statements of national NGOs and organisations founded in the 2000s or later are more diverse. Lastly, the organisation’s mission and vision statements most frequently refer to the organisation’s philosophy. The organization’s target, location, problems to be addressed, services, public images, growth, and technology were followed.
Information Security: A Coordinated Strategy to Guarantee Data Security in Cloud Computing

This paper discusses different techniques and specialized procedures which can be used to effectively protect data from the owner to the cloud and then to the user. The next step involves categorizing the data using three encryption parameters provided by the user, which are Integrity, Availability, and Confidentiality (IAC). The data is secured through various methods such as SSL and MAC protocols to ensure data integrity checks, searchable encryption, and splitting the data into three parts for cloud storage. Dividing the data into three portions not only enhances security but also facilitates easier access. Access to the encrypted data requires the user to provide the login information and password of the owner. This paper also studies critical security issues like unauthorized servers, brute force attacks, threats from cloud service providers, and loss of user identity and password.
SISTEM INFORMASI KEUANGAN SEKOLAH BERBASIS WEBSITE MENGGUNAKAN METODE PROTOTYPE PADA SMAN 2 CIKARANG PUSAT

With the development of internet technology, it makes it easier for humans to do work. Many ways or systems from a job that is still done manually (conventionally) are changed to computerized so that it is more effective and efficient. One of them is in the financial management system at SMAN 2 Cikarang Pusat which can be done using a computerized system. The method used is the prototype method, which is a software development method, which is a physical model of the system's work and serves as an initial version of the system. With this prototyping method, a prototype system will be produced as an intermediary for developers and users so that they can interact in the process of information system development activities. The purpose of this study is to build a financial management system for SMAN 2 Cikarang Pusat, which is expected to assist officers in managing school finances more regularly, effectively and efficiently. The results achieved from the design and manufacture of this financial management system are assisting financial officers in the process of data collection, reporting, and filing of finances as well as introducing developed information technology.&#x0D;
Evaluasi Program PKL Kompetensi Keahlian Teknik Kendaraan Ringan di SMK Negeri 39 Jakarta

This study aims to describe what it is about the application of e-learning in the Educational Technology Study Program of the Faculty of Education and Psychology at Mandalika University of Education. This research uses a case study method with various data collection techniques. The results showed that: 1) there were 20 courses held by e-learning by 7 lecturers; 2) e-learning applied is blended learning; 3) the application of e-learning has gone through the stages of analysis, design and development; 4) the analysis phase includes the analysis of student characteristics and e-learning environment analysis); 5) the design phase where most are designed with online learning patterns (studying the material, deepening the material through online discussion forums, applying knowledge through online assignments, and evaluating through online tests and face-to-face learning more emphasis on in-depth discussion, demonstrations, case studies, and practice; 6) the development phase of lecturers developing material by utilizing existing material; 7) the implementation of blended learning is interesting and liked by students; 8) the implementation of e-learning is going well because of the strong commitment of the lecturers, the familiarity of students' ICT and study program support; and 9) the inhibiting factors for the adoption of e-learning are more on the lack of inadequate ICT policy and infrastructure support. Based on research findings it is recommended that educational technology study programs have a minimum standard of developing and implementing blended learning and increasing the support of adequate facilities and access to the internet.
THE USE OF POWTOON IN IMPROVING STUDENTS’ ENGLISH SKILLS

The aim of this study is to explain the use of PowToon in improving students’ English skills. The technology has grown and impacted the learning including the learning media. It left the reverse in the way teacher delivers the material. Library research method was utilized to collect the data. The instruments of this research were journals, e-books, and library findings. The finding revealed that PowToon could enhance students’ English skills. It also has a lot of benefits such as colorful fonts, moving animation, combination of visual and auditory, text and music that could help students in improving their English skills.
THE EFFECTIVENESS OF USING COOPERATIVE INTEGRATED READING AND COMPOSITION (CIRC) METHOD TO TEACH READING SKILL

The research is entitled “The effectiveness of using cooperative integrated reading and composition (CIRC) method to teach reading skill”. The research is aimed to find out the answer of research question that reads “Is using Cooperative Integrated Reading and Composition (CIRC) Method more effective than that of using conventional method to teach reading skill” The research was an experimental research method in which the researcher compared two groups, experimental and control groups that are given different treatment during the research process. The experimental group was taught by using Cooperative Integrated Reading and Composition (CIRC) Method, meanwhile the control group was taught by using conventional reading method, in this case silent reading method. The result of post-test obtained by both groups was taken as the effect of the different treatment given for both groups. The result of this research shows that teaching reading skill by using CIRC Method was more effective than teaching reading skill by using conventional method. The effectiveness of using CIRC Method to teach reading skill was proved by the research findings that show the mean score of experimental group was 83.5 higher than mean score of control group 64. The result of t-test (t-calculation) was 1.90 higher than the value of t-table = 1.684 at level of significance 5% (0.05).
Artifact removal techniques for lung CT images in lung cancer detection

Lung Cancer in today’s world is one of the major widespread dangerous diseases which is the subject of maximum deaths every year. Accurate detection of lung cancer could boost the endurance rate. Medical image processing has a significant impact on the recognition of lung tumors using Computer Tomography (CT) scan images. Images from a CT scan are widely used because they provide comprehensive imaging of tumor progression inside the lungs. Although different types of noise might be experienced while doing CT scans, producing it a monotonous task for recognizing tumors in the lung. Elimination of noise in CT images is a challenging task for medical diagnoses. The presence of noise in an image is inevitable. Hence reducing noise from the CT scan image is critical for further analysis. Hence various filtering techniques have been used that denoise and enhance the image and help in further evaluation of CT images for accurate lung cancer detection. This paper analyses the noises of different kinds in the CT images and different noise removal techniques which help in improving the accuracy of segmentation and feature extraction as they remove unwanted noise and contribute to the accurate detection of lung cancer. The various filtering methods are analyzed with salt along with pepper noise and speckle noise. The performances of different filters are computed in terms of metrics for evaluation like PSNR, SSIM, MSE, and SNR. The experimental results show that the median filter is more efficient in comparison to other filtering methods in eliminating noises that exist in lung CT images by owning fewer MSE values of 214.8522, high SNR value of 19.36304, SSIM value 0.595997, and high PSNR value of 24.80941.
An Intelligent Dog Breed Recognition System Using Deep Learning

Image processing has been getting great attention recently in the field of machine learning and deep learning. This technique can be used to process an image in such a way that the computer understands the features of the image and classifies it. Our study focuses on building an efficient CNN model to predict the breed of the dog using its image, giving the best accuracy possible with the least amount of computing resources involved. This CNN model is deployed on cloud service, Google App Engine which identifies certain characteristics or features in an image such as the paw, nose, stout, and ears of a dog, employing a dataset containing 10222 images of different dog breeds or classes of dogs and opening a wide scope for future developments.
Surmising Assault Resistant E-Healthcare Cloud Framework with Fine-Grained Access Control

Abstract: The e-medicinal services cloud framework has demonstrated its capability to enhance the nature of social insurance and people's personal satisfaction. Shockingly, security and protection obstruct its broad arrangement and application. There are a few research works concentrating on saving the security of the electronic human services record (EHR) information. In any case, these works have two principle restrictions. In the first place, they just help the 'dark or white' access control strategy. Second, they experience the ill effects of the deduction assault. In this paper, out of the blue, we outline a deduction assault safe e-human services cloud framework with fine-grained get to control. We initially propose a two-layer encryption plot. To guarantee a productive and fine-grained get to authority over the EHR information, we outline the primary layer encryption, where we devise a particular access strategy for every datum trait in the EHR, and encode them independently with high proficiency. To save the security of job traits and access strategies utilized in the principal layer encryption, we deliberately develop the second-layer encryption. To take full favorable position of the cloud server, we propose to give the cloud a chance to execute computationally concentrated chips away at benefit of the information client without knowing any delicate data. To save the entrance example of information properties in the EHR, we additionally build a visually impaired information recovering convention. At last, we lead broad security investigations and execution assessments, which affirm the viability and effectiveness of our plans .
Ethereum Auction System Using Blockchain

In the world of online marketplaces, creating online auctions is an intriguing notion, and Ethereum auctions are among the most important e-business applications.By giving buyers and sellers a forum to trade goods using cryptocurrencies, these auctions increase the safety and security of the payment system.By supplying asset addresses for their products, registered users of the Ethereum Auction program can suggest new auctions, allowing other users to make bitcoin purchases or submit bids.Because it provides a dependable, simple, and quick way to buy and sell a variety of goods and services, this system is gaining popularity.The Ethereum Auction System is made to simplify and safeguard the payment process, giving users a hassle-free experience.The system is as simple to use as visiting a webpage, so even non-technical people may do so with ease.The ability to sell goods from the convenience of their homes is a major advantage of this application.
Recommendation System using Multi-Regression Technique

Abstract: Artificial intelligence (AI) and Machine Learning (ML) is one of today's compelling and promising technologies that profoundly affects nearly all areas of business while continuously transforming people's lives. Workforce management is not an exception to the concept, since AI is advantageously indiscriminately thriving in all industries. By recommending programmes to users based on their preferences and needs, app recommendation systems play a crucial role in this regard. The objective of this project was to create an Android app recommendation system based on machine learning for skill matching. Recommender systems are efficient tools for filtering online information, which is widespread owing to the changing habits of computer users, personalization trends, and emerging access to the internet. Time, effort, and tedious everyday duties will be automated, freeing up human attention for more crucial issues related to improving performance and development. It would be possible for systems to function similarly to the human brain in terms of data analysis and the capacity to build an effective systematic engagement to process the data in a fair, efficient, and quick manner if they acquired automation, cognitive insights, and cognitive engagement during the recruitment process.
Conversion of Sign Language to Text

Abstract: Sign language is a form of communication that uses hand sign and gestures to convey meaning. we present a new approach to converting sign language into text format. Our system is designed to enable deaf and mute people to communicate with others in a more accessible and convenient way. The proposed method uses computer vision and deep learning methods to recognize hand gestures and translate them into appropriate text. The system was built using a combination of key point detection using MediaPipe, data pre-processing, label, feature generation and LSTM neural network training. This work has the potential to significantly improve communication for deaf and dumb individuals and reduce the barriers to communication with the rest of the world. The system uses key point detection algorithms such as MediaPipe to identify hand gestures and a Lstm model to translate them into corresponding text output. The data collected from the sign language is pre-processed and then used to train an LSTM neural network to accurately recognize gestures and produce text output. This method of conversion not only helps deaf and hard of hearing individuals communicate with the hearing population, but also serves as an assistive tool for individuals who are trying to learn sign language. Overall, the proposed solution has the potential to greatly improve communication and reduce barriers for deaf and hard of hearing individuals
Metaverse technology

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Based on a literature review and an expert panel's insights, this paper identifies the opportunities and challenges of applying metaverse technology in operations and supply chain management. Originality/value The briefing saves busy executives, strategists, and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.
Analysing Sentiments for YouTube Comments using Machine Learning

Abstract: Sentiment analysis is a method for learning what users think and feel about a service or a product. YouTube is one of the most popular platforms for sharing videos. Millions of views are attained. These get a lot of comments, many of which offer helpful information that raises the posted content's rating levels. Natural language processing and machine learning techniques are used to make use of these remarks. There have been several academic attempts with two classes (positive or negative), three classes (two with neutral), or multiple classes (happy, sad, fear, surprise, and rage). Consequently, there had been efforts to utilise study of comments on YouTube to determine the polarity. This study examines the perception of strategies and methods for analysis that may be used to the material on YouTube.
A Light Weight Optimal Resource Scheduling Algorithm for Energy Efficient and Real Time Cloud Services

Abstract: Cloud computing has become an essential technology for providing various services to customers. Energy consumption and response time are critical factors in cloud computing systems. Therefore, scheduling algorithms play a vital role in optimizing resource usage and improving energy efficiency. In this paper, we propose a lightweight optimal scheduling algorithm for energy-efficient and real-time cloud services. Our algorithm considers the trade-off between energy consumption and response time and provides a solution that optimizes both factors. We evaluate our algorithm on a cloud computing testbed using the Cloud Sim simulation toolkit and compare it with load balancing round robin, ant colony, genetic algorithm, and analytical algorithm. The results show that our proposed algorithm outperforms these algorithms in terms of energy efficiency and response time.
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