Reviewerly/exHarmony huggingface dataset:
Perbandingan Metode Random Forest Classifier dan SVM Pada Klasifikasi Kemampuan Level Beradaptasi Pembelajaran Jarak Jauh Siswa

WHO has declared that COVID-19 or SARS-CoV-2 has been a global pandemic since March 2020. Distance learning as we often hear is learning that prioritizes independence. Teachers can deliver teaching materials to students without having to meet face to face in the same room. This kind of learning can be done at the same time or at different times. This study aims to compare the results of the classification of students' distance learning adaptability levels with the random forest classifier and SVM methods. Obtaining the evaluation results of each algorithm used. Precision, recall, f1-score, and accuracy are evaluation indicators. The results of the classification of each adaptivity class got 73.1% for Moderate, 74.7% for Low and 66.1% for High. With the total accuracy of the SVM algorithm on the tested data of 73.36%. The results of the classification of each adaptivity class got 92.1% for Moderate, 92% for Low and 86% for High. With the total accuracy of the Random Forest Classifier algorithm on the tested data, it is 91.5%. From 1205 test data contents for each model, it was found that the Random Forest model has a higher accuracy but has an incorrect classification value of 321 data, and the accuracy of the Support Vector Machine model is lower but has an incorrect classification value of as much as 101 data
Analisis Usability Testing pada SITIDES Menggunakan System Usability Scale dan PIECES Framework

SITIDES Bengkaung Village is a website-based integrated system owned by Bengkaung Village located in West Lombok Regency, West Nusa Tenggara (NTB) Province under the management of village officials. All information related to Bengkaung Village is displayed on SITIDES Bengkaung Village. However, since the system was officially used, there has never been an evaluation and testing of the level of user satisfaction, in this case the manager of SITIDES Bengkaung Village, so a usability analysis is needed which in this case uses two methods, namely the PIECES Framework and the System Usability Scale. The purpose of this evaluation and testing is to measure the level of satisfaction of SITIDES users in Bengkaung Village, in this case the managers of which there are 9 people who have different access rights. Based on the research that has been done, the results of the analysis using the Pieces Framework method are a value of 4.36 obtained from the average value of 6 domains. This value is in the very satisfied category. While the results of the user satisfaction level of SITIDES Bengkaung Village using the System Usability Scale method are obtained a value of 77.78 where the value for the acceptability range version is Acceptable, while the grade scale results from the level of user acceptance are included in class B. Based on the measurement results using 2 The method obtained almost the same results, which showed that the users were very satisfied with the SITIDES system in Bengkaung Village so that the system was very feasible to use.
Penentuan Penerima Bantuan Pangan Non Tunai (BPNT) Menerapkan Metode Multi Objective Optimization on the Basis of Ratio Analysis (MOORA)

Non-Cash Food Assistance (BPNT) is something that is made as assistance in the form of food, to help the community, especially in social services that are given to the community in a non-cash way or called electronic money whose source is the government and is given to underprivileged families or beneficiary families. (KPM). This assistance is distributed every month using a card and exchanged at e-Warong. The result of the exchange is food or in the form of rice, milk, instant noodles etc. In the process of selecting candidates for BPNT assistance, it will be very difficult if it is decided manually. Therefore, a system called DSS is needed. Decision Support System (DSS) is a stage in finding a solution to a problem where the process is carried out using a solution according to how the computer works. DSS can work optimally if using the method. In this study, the authors chose the Multi-Objective Optimization Method on The Basic of Ratio Analysis (MOORA) which is a method that can be used in the completion and completion process of the DSS. This method has a working procedure that uses mathematical calculations. The results of this study were obtained as the best candidate for the recipient of BPNT funds, alternative A4 on behalf of Jefri with a value of 0.2362 as the first rank
Sistem Pendukung Keputusan Penilaian Kinerja Tenaga Honorer Menerapkan Metode Weighted Product (WP) dan Complex Proportional Assessment (COPRAS) dengan Kombinasi Pembobotan Rank Order Centroid (ROC)

Honorary workers are someone who is appointed by a Personnel Development Officer or other officials in the government to carry out certain tasks in government agencies whose salary is paid by the APBN or APBD. The performance evaluation of honorary workers is aimed at planning the development of human resources and training and increasing the utilization of honorary workers in accordance with their duties and functions. The process of assessing the performance of honorary workers who are unfair can have an adverse effect on the honorary workers themselves. In the process of evaluating honorary staff, an efficient system is needed to see the performance results of the honorary staff, a Decision Support System is needed. The method applied in this study is the Weighted Product (WP) and Complex Proportional Assessment (COPRAS) methods applying Rank Order Centroid (ROC) weighting using these two methods, it is expected to provide effective results in evaluating honorary workers. The final results obtained in calculating the best alternative value in the calculation of the Weighted Product (WP) method, namely A4 on behalf of "Karin" with a value of Vi = 0.246 and in the calculation of the Complex Proportional Assessment method (COPRAS), namely A6 in the name of "Love" with a value of Ui = 100
Pendampingan Administrasi Sekolah berbasis Digital di SMP Muhammadiyah Palangka Raya

Technological developments have a significant impact, one of which is education. Activities or services in schools that were initially manual are now turning digital. Of course, this also requires preparation from various components of the school, both students and educators. This service aims to help schools with digital services. The method is a mentoring method with an approach in this service using the PAR or Participatory Action Research approach. The results of this dedication activity are: Improving quality, broadening insight, knowledge, and skills for educators and education staff at Muhammadiyah Junior School of Palangka Raya through community service activities related to school administration governance and providing strengthening the implementation of school administration governance by both lecturers and students. Produced 2 Microsoft Exel-Based School Administrative Governance Applications, the PPDB EMIS and DAPODIK Applications, and the Lahajar v.4.4 Application.
AI and Human Relationship in the Workplace: A Literature Review and Future Research Agenda

The relationship between human and artificial intelligence has attracted debates and polarized views. A key area of this debate that received research attention is human and AI capability to augment each other to achieve better outcomes. While there is a growing research interest in the topic, research is currently dispersed and spread across the management disciplines making it hard for researchers to benefit from an accumulated knowledge in this domain. This study synthesises the literature and describes the current research findings in order to provide foundation for future research in this area. Based on a systematic review, we identify and discuss three emerging themes in the literature and highlight different possible challenges related to integrating AI in organisations. A future research agenda is also presented.
Factors Affecting Chatbot Resistance to Gain Knowledge About Family Planning Among Arab Women: A Conceptual Paper

Unplanned pregnancies are a serious public health concern in both developed and developing countries. In many developing countries, such as Arab countries, discussing family planning is surrounded by different barriers such as social and cultural stereotypes, and limited access to information. Chatbots provide women with the opportunity to learn about family planning while overcoming issues such as privacy and stereotypes. Although Chatbots have many benefits for Arab women in the family planning domain little research is conducted to study factors affecting women’s adoption of chatbots to learn about their family planning options or factors affecting them resisting adoption of this technology. Hence, this conceptual paper comes to focus on factors that might lead women in Arab communities to resist adopting chatbots to learn about family planning options regardless of their benefits. The proposed propositions in this paper are based on the Innovation resistance theory (IRT).
Unified Metaverse Architecture Powered by Blockchain Decentralized Autonomous Organizations (DAO)

Metaverse platforms or ecosystems can be considered virtual or extreme reality spaces where end-users live, communicate, collaborate, entertain, work and game with other personas or avatars in computer-simulated environments. Metaverse environments envisage a cybernetics future where man, machine and systems work together in the virtual world to replace humans. Metaverse platform’s vision is to integrate communities, products, service offerings, creators, commerce, entertainment, workspace etc. Metaverse works on the self-service marketplace requiring many formats of digital payments based on the transaction type. Metaverse virtual operations happen worldwide beyond the firewalls and state boundaries using the internet. Legislation and jurisdiction enforcement are challenging as they go beyond countries and are primarily untraceable sources. Hence, there is a need to study the metaverse components of resources required, communication network essentials, orchestration/automation possibilities, virtual organisation prerequisites, interface-spatial considerations and well-thought experience ecosystems. This paper proposes the architecture of virtual metaverse space using the blockchain-led decentralised autonomous organisation to create immutable, transparent, fair, inclusive and socially immersive platforms using smart contracts and distributed apps (DApps). The proposed unified metaverse architecture powered by the decentralised autonomous organisation (DAO) is the gateway design for metaverse infrastructure (computing and networking resources) to the orchestrated virtual-meta environment (interface, spatial and experience).
Sentence Generator for Hindi Language Using Formal Semantics

Natural Language Processing (NLP) is a specific field within artificial intelligence (AI) that focuses on enabling computers to understand spoken and written language in a manner similar to humans. Its practical applications include facilitating everyday activities such as texting, emailing, and cross-language communication. The demand for intelligent systems capable of reading text, listening to voice memos, and engaging in natural language conversations, even in languages like Hindi, has significantly increased in recent years. This paper presents a random clausal hindi sentence generator, which generates simple, compound, and complex sentences. This tool is particularly useful for students studying on online platforms as it provides a variety of exercises to practice on and learn about clauses. The sentence generation process begins with the generation of simple sentences and gradually progresses to compound and complex sentences. The method employs approximately one hundred verbs to introduce randomness, along with three to four conjunctions and objects that are closely associated with the verbs. This approach ensures that the generated sentences are both syntactically and semantically meaningful.
Exploring the Fusion of Metaverse and Sports: Current Trends and Future Directions

Metaverse is a virtual realization of the physical environment made possible with lifelogging tools like physiological sensors that help in performing life-like virtual interactions amongst users/customers present as avatars in the cyber-physical world. The metaverse is a rapidly growing technology that has the potential to revolutionize the world of sports. In this research work, we used the Scopus database to extract documents published in the domain of sports and metaverse. The descriptive analysis and collaboration analysis of existing literature, and topic modeling Latent Dirichlet Allocation of abstracts highlight the use of augmented reality, virtual reality, blockchain, artificial intelligence, wearables, and the Internet of Things in building domain-specific applications. The findings reveal that these technologies can enhance the learning and training experience for athletes, providing them with immersive and interactive environments to hone their skills. The physical and psychological well-being of athletes can be ensured with the rational use of metaverse. However, the use of these technologies also raises concerns about privacy and the protection of data. The research in the domain of information technology and information systems from marketing is also unexplored. As the metaverse continues to evolve, it is important for the sports industry to address these concerns and ensure that the use of these technologies is done in a responsible and ethical manner.
Sentiment analysis and classification of COVID-19 tweets using machine learning classifier

&lt;p&gt;In March of 2020, the World Health Organization identified COVID-19 as a new pandemic and issued a statement to that effect. This fatal virus was able to disperse and propagate throughout several countries all over the world. During the progression of the pandemic, social networking sites like Twitter generated significant and substantial volumes of data that helped improve the quality of decisions pertaining to health care applications. In this paper, we proposed a sentiment classification using various feature extraction and machine leavening techniques for social media dataset. The system has divided into four phase data collection, preprocessing and normalization, feature extraction and feature selection and finally classification. In first phase we collect data from social media sources such as twitter using Twitter API. In second phase the tweets, data was ready for preprocessing and it was sorted into three categories: positive, neutral, and negative. During the third phase, various features were extracted from the tweets by employing a number of widely utilized approaches, including as bag of words (BoW), Term Frequency-Inverse Document Frequency (TF-IDF), Word2Vec, and FastText, to gather feature datasets. These methods were employed to extract distinct datasets for the features. The final phase different machine learning classification algorithms are applied for detection of sentiment using machine learning. In the extensive experimental analysis, the BoW performed better results with modified support vector machine (mSVM) than existing machine learning algorithms. The proposed mSVM performed superiorly to the other classifiers by 98.15% accuracy rate. Once the tweets are correctly classified as COVID-19 tweets, it is further categorized into three sentiments that is positive, negative and neural. Proposed mSVM achieves 93% of accuracy rate for positive sentiment which better as compared to other Machine Learning (ML) classifiers.&lt;/p&gt;
Investigate the effects of AI Chatbot on repurchasing behavior of online consumers

In the current competitive landscape, when online retail companies are using several different techniques in motivating customers repurchasing products or services, AI Chatbot has become one of the most popular tools to increase customer trust and experience. This study investigates the effects of information quality, system quality, and service quality of AI Chatbot on online consumers' trust and repurchasing behavior. Quantitative methods are used to examine causal relationships. The results show that three aspects of AI Chatbot have significant positive impact on customer trust. Service quality has the highest influence while system quality has a lower effect. When customer trust increases, the frequency of rebuying products/services is also higher. Therefore, the article makes specific contributions in terms of both theory and practice.
Heatmap Visualization Approach for Descriptive Analytics of Covid-19 Cases in Malaysia

The Covid-19 pandemic has presented unparalleled obstacles to the world, including Malaysia and Indonesia. A visual analytics approach known as the Covid-19 heatmap visualization is proposed to provide relevant and timely information about Covid-19 daily cases and deaths in Malaysia. The aim of this approach is to offer a platform for various stakeholders to make informed decision based on descriptive analytics. The Covid-19 information visualization approach allows users to compare different types of visualizations such as heatmaps, line charts, and bar charts to detect Covid-19 trends or patterns. The approach is implemented as a web-based system using D3 JavaScript library and tested using the data collected from Coronavirus Pandemic Data Explorer. Results show that the Covid-19 heatmap visualization approach is an invaluable approach for understanding pandemic trends as it provides users with easy access to visualizations and fast understanding of Covid-19 situations such as daily cases, deaths and recoveries. The target users for the proposed approach are the National Security Council and Ministry of Health staff, company crews, and the general public. Future upgrades to the approach includes adding additional attributes such as the number of tests and recoveries to assist users in making predictive analytics using machine learning models.
Team Formation for Agile Software Development - Crowdsourcing-based Empirical Study

Agile Software Development (ASD) is gradually substituting the plan-driven Waterfall development process. The nature of ASD requires that Agile development teams be more effective than any other development team in that Agile development is incremental, rapid, and responds well to changes. Therefore, team formation should be done properly in order for effective teamwork which leads to great performance and project success. To date, there is limited guidance, model, or frameworks that can assist in achieving optimum team formation. Currently, team formation is done based on heuristics and instincts which seemingly results in bias and incorrectness. This study aims to validate the Agile team formation conceptual model. This paper reports the initial empirical study that was done using a crowdsourcing-based method due to pandemic restrictions on close contact. The study was done in an Agile professional network group platform on the internet. The data collected is then analysed using contents analysis. The respondents validated that the team formation characteristics in the conceptual model were applicable with an emphasis on continuous learning and having a growth mindset. Future plan would be to determine the optimized team formation by using elements of Artificial Intelligence algorithms such as Genetic Algorithm.
Analisis Komparasi Metode Sistem Pendukung Keputusan pada Gaya Belajar “VARK”

Learning style is an important factor in the success of the learning process from learning resources to individuals or groups. Understanding learning styles can be a strategy in the learning process. One of the learning styles is "VARK" which is the preference of individuals or learning groups consisting of visual, aural, read/write, and kinesthetic. Various methods are developed to find out the learning style of an individual or group of learners. In this research, a decision support system (SK) will be developed that provides learning style recommendations for individuals or study groups whether the tendency is visual, aural, read/write, or kinesthetic. The method used is a combination of simple additive weighting (SAW) and weighted product (WP). The SPK development stages consist of data collection through distributing surveys to 55 student respondents at the 1926 Education Foundation where the dominant characteristic of the respondent's learning style is visual, namely 56%, analyzing SAW and WP methods, developing SPK with a web-based system, testing the system using the black box testing method.
The impact of the removal of information and communication technology subjects on students' digital literacy

This study aims to find out how the perception of class XI MA Darul Irfan students in Serang City about the abolition of ICT subjects, and also to determine the level of digital literacy skills of students in class XI MA Darul Irfan Serang City after the abolition of ICT subjects. The type of research used in this research is qualitative. Qualitative research is research that intends to understand the phenomena experienced by research subjects such as behavior, perception, motivation by means of descriptions in the form of words and language. So, in this study researchers conducted observations, interviews and documentation. The results of the study show that: 1) ICT subjects are very important for students in schools to face the current digital era so that students are not ignorant in using technology. 2) the ability of students to find, manage, and convey information through digital is already high. Students prepare to take advantage of digital literacy in learning is already high. The ability of students to think critically, creatively and innovatively in the use of technology is still low. Student participation in digital literacy activities is quite high.
Development of learning media based on macromedia flash 8 to see learning outcomes and achievements in vocational high school students

This research aims to produce ICT learning media based on macromedia flash 8 to see the learning outcomes of students of SMK achievement class X multimedia and determine the quality of ICT learning media products based on macromedia flash 8 to see the learning outcomes of students of SMK achievement with the development method of R&amp;D (Research and Development). This ICT media was assessed by 30 students of class X multimedia to find out student responses. The instrument used is a check list (?) questionnaire. The type of data obtained is qualitative data which is analysed using and will then be converted into quantitative data and then tabulated to determine the quality of the product developed. The results of this study indicate that the value of ICT learning media based on macromedia flash 8 has been produced, namely the results of user testing by students with a score of 4.78 in the very feasible category, thus it can be concluded that ICT learning media based on macromedia flash 8 to see the learning outcomes of X multimedia class achievement vocational students are declared feasible to be used as learning media on the material of basic concepts of computer operations