Reviewerly/exHarmony huggingface dataset:
Increasing Awareness of the Village Disaster Risk Reduction Forum in Magetan Regency in Realizing Disaster Preparedness

Disaster risk reduction forums as a capacity in disaster resilient villages often experience difficulties in realizing disaster preparedness. It is necessary to prioritize any element that is immediately realized, so that what is done truly makes society have resilience and toughness. five disaster preparedness parameters that must be prepared by the forum. These five parameters have 25 elements as constructs. Elements as a construct of disaster preparedness parameters become an instrument called Difficulty and Usefulness of Elements in Disaster Preparedness (DUEDP-Questionnaire). This DUEDP questionnaire serves as a guide enumerator for interviewing forum administrators and communities in 23 disaster-resilient villages in the Magetan district. Data was collected for three months starting May-July 2023. The element prioritization technique uses the Quadrant of Difficulty and Usefulness (QoDU) method. This method focuses on elements in the upper left quadrant, namely elements that are very useful but how to make it happen is very difficult. The research results place the elements of involving vulnerable groups in socializing about disasters, providing village funds for disaster management, preparing contingency plan documents, providing early warning system tools, and training families to provide disaster preparedness bags as the main priorities that must be immediately realized by the forum.
PREDICTION OF INDUCED STRESSES WITHIN SOIL MASS USING ARTIFICIAL NEURAL NETWORK

In this paper, an Artificial Neural Network (ANN) is applied to predict the soil stress within a soil mass for a variety of depths and displacements under applied loading. The neural network model is created and applied for two cases, point load, and Uniform rectangular load.Theses two cases were selected among many other cases of loading as a representation of the capabilities of ANN in finding proper solutions. The first case needs one input to get one output, where in the second case we need two inputs, to get one output only.Results revealed that function approximation using neural network can be applied easily and can give accurate results by choosing the appropriate learning algorithm, number of layers, and number of neurons to solve the problem. ANN model can provide reasonable accuracy for civil engineering problems, and a more effective tool for engineering applications.
Unveiling the Catalysts of Digital Transformation Acceptance: Insights from Employees in Online Distance Learning Higher Education Institutions

Online distance learning in higher education institutions is experiencing significant growth and is increasingly adopting digital transformation. However, employee acceptance and adoption of these changes present a major challenge. This study investigates the factors influencing employee acceptance of digital transformation in online distance learning institutions. It examines the influence of latent variables, such as effort expectancy, performance expectancy, self-efficacy, and intention, on the acceptance of digital transformation. It also expands on existing theoretical frameworks and provides empirical evidence of their importance. Data was collected from 387 employees using a structured questionnaire, and statistical analysis, including regression and PLS structural equation modelling, was used to assess the relationships between variables. The findings revealed that effort expectancy, performance expectancy, self-efficacy, and intention significantly influenced employee acceptance of digital transformation. The indirect relationship hypotheses are also supported. Several practical implications and strategies such as user-friendly technologies, effective communications, professional development opportunities and involvement in decision-making processes are identified as key strategies to enhance employee acceptance. The study contributes to the existing knowledge of acceptance theories and suggests avenues for future research including exploring additional variables such as culture and contextual factors and conducting longitudinal studies to understand the long-term effects of digital transformation.
Analisis kesadaran hukum terhadap pelanggaran penggunaan sepeda motor oleh anak di bawah umur di SMP Negeri 1 Kerinci

This research was presented to determine the level of legal awareness regarding violations of motorbike use by minors at SMP Negeri 1 Kerinci. This research was conducted at SMP Negeri 1 Kerinci located : Jln. Raya Pugu Semurup, Desa Pugu Raya, Kecematan Air Hangat Barat, Kabupaten Kerinci. The samples that will be used as subjects for this research include: Students of SMP Negeri 1 Kerinci, parents of students of SMP Negeri 1 Kerinci who use motorbikes to school, Student Representatives of SMP Negeri 1 Kerinci, and the Kerinci Traffic Police (Polantas). The approach used is a qualitative descriptive approach. The resulting data will be a description in the form of words and does not emphasize data in the form of numbers. The data obtained and collected in this research was then analyzed so that it could be explained further. The research results showed that students have low legal awareness, where this can be seen from students' low knowledge and understanding of law, there are still many children who do not know the legal bases that regulate traffic and road transportation. Meanwhile, legal attitudes and behavior are categorized as quite high, where SMP Negeri 1 Kerinci has established rules that must be obeyed by students of SMP Negeri 1 Kerinci, and Traffic Police have carried out their duties in accordance with procedures that have been regulated or determined by law.
The function and role of big data: focusing on the diplomatic perspective

The rise of the fourth industrial revolution has catalyzed the rapid development of information and communications technologies like AI, big data, and IoT, driving changes in international politics and diplomacy. This study examines the significance of big data and its application as a diplomatic tool, scrutinizing domestic and international instances.The analysis found that using big data and AI technologies in risk management and international politics is emerging as crucial elements of globalization and national influence. Nevertheless, the process of incorporating big data into diplomacy necessitates the resolution of current obstacles. Various applications to expedite diplomatic activities will become more viable when related protocols are defined and concerns about the ethics of managing big data are addressed.
Study of Literature: The Role of Traditional Games as a Learning Media to Instill Character Education in Elementary School Students

Traditional games are games owned by a group of people, where in these games they adhere to the norms and customs of the community passed down from their ancestors to the next generation. The aim of this research is to describe the role of traditional games as interactive learning media to instill character education in elementary school students. Character education contained in traditional games contains the values ​​of honesty, enthusiasm, good manners, responsibility, cooperation, discipline, hard work, helping each other, never giving up and so on. The methods used in this research are literature study, searching, analyzing and drawing conclusions. And the results obtained in this research show that traditional games can instill character education, for example religion, honesty, enthusiasm, good manners, responsibility, cooperation, discipline, sportsmanship, hard work, mutual help, never giving up and many more. Therefore, it is important to re-instill traditional games for children as a learning medium that can build good character in children
Harmonizing the voices of AI: Exploring generative music models, voice cloning, and voice transfer for creative expression

The intersection of artificial intelligence (AI) and creative expression has sparked a revolution in various artistic domains. This review paper delves into the realms of generative music models, voice cloning, and voice transfer, exploring their significance in fostering novel avenues for creative expression. Beginning with an overview of AI's evolution in creative arts, we scrutinize the progression of AI in music generation and voice synthesis. We delve into the mechanics and impact of generative music models, followed by an examination of voice cloning technologies and their ethical implications. Furthermore, we explore the application of voice transfer in music creation and its extension to other forms of storytelling and podcasting. Ethical and legal considerations surrounding AI-generated voices are also addressed, alongside user perspectives on creativity and the technical challenges and innovations in this field. Through case studies and future directions, we illuminate the potential of AI-driven creative expression, delineating its implications for the future of art and self-expression.
Deepfake Face-Swap Animations and Affect

The chapter analyses face-swapped deepfakes in moving images, focusing particularly on two different applications: ‘the public speech’ and ‘the porn scene’. Face-swap technologies generate fears about their abuse: for example, in connection with fake news, advertisements, or hate crime strategies. The fear is that epistemic claims (‘He said this’, ‘She did that’) in a medium that is historically associated with authenticity may affect people differently from other media (writing, audio, still images). The chapter critically questions the affect and the temporality of deepfakes, and analyses what it is like to be depicted in a deepfaked face-swapped animation. It draws on the interrelation between affect and animation, and outlines the medial and attentional ecologies of digitized bodies. Deleuze and Guattari’s ‘faciality’, Bernard Stiegler’s ‘tertiary memory’, and Mark B.N. Hansen’s notions of temporality (‘life’ and ‘artificial time’) are used to theorize about the affect of face-swaps in deepfakes.
Digital Accounting Information System Implementation at BPKAD SAMOSIR District

Problems at BPKAD Samosir Regency evolved over time with the changing landscape of information technology. Initially, BPKAD relied on Microsoft Office Excel software. However, with technological advancements, Microsoft Office Excel was superseded by e-finance applications. The e-finance application played a crucial role in supporting financial activities, particularly accounting, and was in use from 2019 until the conclusion of 2020. In early 2021, a further enhancement occurred as the SIPKD application (Regional Financial Management Information System) took over the role from the previous e-finance application. The aim of this research is to identify and analyze the factors that influence, either partially or simultaneously, the implementation of the Computer-Assisted Accounting System in the management of assets and finances of Samosir Regency. To conduct this research, researchers used quantitative methods with primary data, by distributing questionnaires to Samosir Regency BPKAD employees. Research participants are public service employees and honorary BPKAD Samosir Regency employees who have worked for at least two years and have made a direct contribution to the implementation of the Informal system. The research was conducted between March and April 2023. The results showed that the application of personal technical skills, user involvement, accounting expertise, and superior assistance had a positive and significant impact on the implementation of computerized accounting information systems, while training and education did not have a positive or significant impact on the implementation of information systems. computerized accounting. Human Resources Management plays a crucial role in the successful implementation and operation of Computerized Accounting Information Systems (CAIS) within an organization. This paper examines the key factors that influence the effective utilization of CAIS, including Personal Technical Ability, User Involvement, Training and Education, Accounting Knowledge, Leadership Support, and the Application of CAIS. The recommendation from this research is to add other variables outside the variables that have been researched, such as Good Government Governance, Use of Information Technology, and others. and conducting in-depth interviews regarding the advantages and disadvantages of implementing a computerized accounting information system. As well as adding references and expanding research objects such as all SKPD in Samosir Regency.
Instagram Features as Media for Learning English Listening Comprehension

This study aimed to investigate what Instagram features that help students in learning English listening comprehension, and to find out the students’ perceptions towards Instagram as a media to learn the subject. Mixed method was used for this study, specifically in the form of a case study in one secondary school in Cimahi, West Java, Indonesia. Ten secondary school students aged between 15 and 18 years were chosen as participants of this study. The researchers tried to create Instagram content that would help the students learn the subject, combined with the use of questionnaires, classroom observation, and students’ interview to obtain data. Data from questionnaires were analyzed using percentage calculation, data from classroom observation were analyzed based on the activities in the classroom and displayed in the form of table, while students’ interview were analyzed based on deductive thematic data analysis. The result shows that the students are familiar with Instagram Story, Post, Reel, and Live. These Instagram features were used as tools for learning English Listening comprehension. The students perceived that the use of Instagram features for listening English comprehension could help them develop their potencies, make the learning materials more interested, assist them to learn and be more creative.
Analysis of Credit Card Fraud Detection Performance Using Random Forest Classifier &amp; Neural Networks Model

Credit card fraud is one example of data manipulation in the e-commerce industry. Because credit card fraud is so common, preventing it can be difficult. Therefore, it is important to identify credit card fraud as soon as it occurs. Determining the validity of a transaction is a fraud detection process. Credit/ Debit cards/ any financial services are small plastic cards given to members of certain financial organizations with proper identity and verification. This research is quantitative research that uses a dataset that has been verified and classified as fraudulent or non-fraudulent transactions. This research will limit itself to credit card fraud detection methods that use Neural Networks and Random Forest Classifier algorithms. Using publicly available credit card transaction data as a starting point, this study will examine how well machine learning algorithms do overall in identifying credit card fraud. First of all, we check for the presence of duplicate values in the data set. The result of this check shows that there are no duplicate values in the set, marked with the value ‘False’. Next, we focus on class in the target variable ‘Class’. The output of this check shows the wide variety of samples for each class in the goal variable ‘Class’. In this example, class 0 has 284.315 samples and class 1 has 284.315 samples. Based totally on the studies performed, it is possible to conclude that the usage of machine learning algorithms, together with Random Forest Classifier and Neural Networks, can be effective in detecting credit card fraud. The results of the algorithm performance analysis show that the model developed can identify fraudulent transactions accurately. In addition, the data preparation stages, correlation analysis, and model performance evaluation also contribute to understanding potentially fraudulent credit card transaction patterns.
A New Hybrid Algorithm Based on the Firefly Algorithm and Cuckoo Search to Estimate Survival Analysis of Truncated Inverse Gompertz Distribution

This paper introduces the Right Truncated Inverse Gompertz Distribution (RTIGD) with two parameters δ and ϑ with some of its properties as; (Survival-Function, Hazard-Function, cumulative distribution function, probability density function, ‎r-th moment, mean, variance, Moment Generating Function, Median, and Mode. In addition, we propose a new hybrid algorithm, namely the firefly Algorithm with Cuckoo Search Algorithm (FA_CSA) to estimate the parameters based on the survival functions of RTIGD. Simulation is utilized to compare the proposed algorithm with traditional methods, for example, the Maximum Likelihood Estimator and moment method and the standard algorithms Firefly Algorithm and Cuckoo Search. In most cases, the results demonstrate that the proposed algorithm (FA_CSA) provides an accurate estimation for the survival function since it has less mean squared error than the other estimation methods.
Task Scheduling in a Cloud Environment Based on Meta-Heuristic Approaches: A Survey

Cloud computing is one of the emerging technologies that expands the boundaries of the internet by using centralized servers to maintain data and resources. It allows users and consumers to use various applications provided by the cloud provider, but one of the major issues is task scheduling. Task scheduling is employed for the purpose of mapping the requests of users to the appropriate resources available. This paper provides a detailed survey of the available scheduling techniques for cloud environments based on six common metaheuristic algorithms. Those algorithms are the Cuckoo Search Algorithm (CSA), Chicken Swarm Optimization (CSO), Genetic Algorithm (GA), Bat Algorithm (BA), Whale Optimization Algorithm (WOA), and Grey Wolf Optimization (GWO). The literature is analyzed from three perspectives: task type, objectives to be optimized, simulation environment, and quality of service performance metrics. In addition, the research gaps and future directions for future investigation are presented.
Recension Financial regulation of cryptoassets

Money, as it is traditionally known, is undergoing its own digital revolution. Time will show whether we are facing a true paradigm shift in the essence of money or just mere modifications in the supports of representation. If the latter is linked to trust, the essence of money is related to trust in the issuer and the social consensus for its use and extension. The arrival of cryptoassets in the financial system has been a recurring topic of discussion in recent years.
Meningkatkan Literasi pada Siswa Siswi SD Negeri Grogol Utara 09 melalui Kegiatan Festival

Literacy is a vital aspect of education to ensure students' abilities in comprehending, interpreting, and interacting with various forms of texts. This study aims to evaluate the effectiveness of festival activities as a strategy to enhance students' literacy at SD Negeri Grogol Utara 09. A case study method was utilized to analyze the impact of festival activities on literacy skills, with 50 students from grades IV and V participating. Festival activities included film screenings, poetry readings, and dance performances, with data collection conducted through observation, interviews, and questionnaires before and after the events. Data analysis revealed a significant improvement in students' reading, writing, and speaking skills after engaging in festival activities. Additionally, students' interest in literacy and creative expression also increased positively. These findings affirm that festival activities can serve as an effective means to expand students' literacy beyond conventional curricula, providing a meaningful contribution to holistic education.
PEMANFAATAN FANPAGE FACEEBOOK: PENJAHIT KEBAYA DAN SALON DI DESA SIOPAT SOSOR KABUPATEN SAMOSIR

The kebaya sewing service industry and beauty salons are industries that are always in demand by Indonesian people both in cities and in regions. Kebaya is a traditional Indonesian dress. Every religious event and custom almost always uses kebaya cloth. In using kebaya cloth at every event, Indonesian women always make up themselves so that the kebaya cloth used looks more beautiful and beautiful when worn. Therefore, the kebaya cloth sewing industry and beauty salons are one of the service industries that are in great demand by the public in starting a business. The purpose of this community service activity is so that people who start kebaya sewing and beauty salon businesses can reach a wider market by utilizing social media accounts such as Facebook in promoting their business. Facebook social media accounts can be turned into business accounts by adding a fanpage or business page feature. Facebook fanpage is a special page like a blog that contains various kinds of content according to the wishes of its users. The results of this activity are kebaya sewing and beauty salon business actors who have changed their personal Facebook account to a business Facebook account by adding a fan page feature. So that business actors in kebaya sewing and beauty salons can expand their market share through promotions on social media.
A Survey on Optimization Algorithms: Challenges and Future Opportunities

This paper conducts a comprehensive exploration of contemporary optimization algorithms, addressing challenges and outlining potential avenues for future research. The survey encompasses a wide spectrum of optimization techniques employed in various domains, ranging from mathematical programming to machine learning and artificial intelligence. It systematically analyses the inherent challenges faced by existing algorithms, including scalability issues, convergence speed, and adaptability to diverse problem spaces. Furthermore, the paper critically examines the impact of optimization algorithms on real-world applications, considering their effectiveness and limitations. The survey identifies emerging trends, such as hybrid approaches and metaheuristic methods that offer promising directions for overcoming current challenges. By synthesizing the state-of-the-art in optimization algorithms, this paper provides a valuable resource for researchers, practitioners, and decision-makers, guiding them towards addressing existing limitations and unlocking new opportunities in the evolving landscape of optimization research.
Pengaruh Media Papan Perkalian Terhadap Hasil Belajar Matematika Siswa Kelas III SD YPK Elim Kota Sorong

The purpose of this study was to determine the Influence of Multiplication Board Media on Mathematics Learning Outcomes of Grade III Students of SD YPK Elim Sorong City. This type of research uses Quantitative Research with the research design used is a pre-experimental design with the type One-Group Pretest-posttest. The population is class III A students with a total of 19 students with a sampling technique carried out by nonprobability sampling, namely purporsive sampling. The instruments used are observation sheets and essay tests to measure student learning outcomes, while the results of the analysis of student learning completeness on the average posttest score are 83.84. The reliability test results obtained by Cronbachs Alpha for student responses amounted to 0.852 which means it has a high level of reliability with the normality test of student posttest learning outcomes having a significance level of 0.028 &gt; 0.05. The hypothesis test obtained tcount of 7.001 with df = n – 1 (19-1=18) obtained ttable of 1.729. Based on the results of the analysis of value data, namely tcalculate &gt; ttable (-7.001&gt; 1.729), with a magnitude of significance level of 0.05, the hypothesis is accepted. Thus, it can be concluded that there is an influence of Multiplication Board Media on the Mathematics Learning Outcomes of Grade III Students of SD YPK Elim Malanu in Sorong City.