Reviewerly/exHarmony huggingface dataset:
Perancangan Pembuatan E-Learning Berbasis Website Pada SMK Ad-Da’wah Jakarta

In the world of education, there are many elements that can affect the achievement of learning outcomes, including elements of teachers, students, curriculum and facilities and infrastructure that can support learning. Currently, there are still many students in learning who have not found the answer on their own because they are not given the opportunity to practice by the teacher, thus making students feel bored and more passive. Currently, there are still many schools whose students are only given memorization about concepts and not understanding and mastering concepts in terms of solving a problem plus the support of teachers who are less creative in using media in the learning process which makes it increasingly difficult for students to understand the material. Learning methods that take place effectively and efficiently and can be done anytime, anywhere, using any path and with any access speed can be done with the E-learning method. The E-learning method, apart from being able to provide teaching materials and instruction in learning that can be accessed anytime and anywhere, also does not require a large room like a conventional room. In the teaching and learning process there are several problems that arise, namely the problem of limited learning time at AD-DA'WAH Vocational School, the lack of interaction between teachers and teachers outside school hours, limitations between classrooms and the number of students who are not commensurate, which makes the learning process less efficiency. These problems will be solved by designing a learning application with e-learning, which is proven to be efficient in solving problems such as those that occur in the teaching and learning process. The results showed that the e-learning method succeeded in increasing positive efficiency when applied to solve problems. Making e-learning using PHP, MySql, OOP, jQuery, Ajax, CSS as programming languages.
PIMIKIRAN ABRAHAM MASLOW TENTANG MOTIVASI DALAM BELAJAR

Motivation is needed every day by students, especially from outside themselves to have a passion for learning. The feeling of laziness felt by students makes them not enthusiastic in participating in learning in class. Absorbing so many materials and lessons requires the intention and seriousness of a student. Various features that interfere with the arrival of smartphone technology that has a big impact on students. Teachers and parents have an important role to have a positive influence in following each lesson. There are several ways that can motivate students by giving awards, prizes, or praise for those who have tried to learn. This method provides a stimulus to be more enthusiastic in achieving goals with several rewards. Abraham Maslow's theory explains that a person has needs such as eating, drinking and so on. Needs must be met as well as student learning must have a sense of need to do so.
Maternal Decision Support Systems to Reduce Maternal Mortality in Indonesia: Resolving Barriers to Implementation in Community Health Centers

Aim: This paper aims to design a decision support system in Maternal and Child Health services or MCH that can monitor cases of pregnant women and prevent maternal deaths because maternal deaths are still found in Semarang. Indonesia. Method = Research and Development with system development using the System Development Life Cycle method, which includes studying user needs, analyzing the system used, determining the form of the system being developed, and designing the Maternal Decision Support System. The sample of this research is in the form of MCH service data in 2019 - 2021. Meanwhile, respondent data collection is carried out by interviewing MCH Program Holders and observing the system used, analyzing MCH data, and designing a region-based Decision Support System using PHP programming and MySQL database. Result: The development of an MCH decision support system application that can support the area-based MCH program is https://spk-maternal.com/. It is easy to use by officers at the community health centers and the Health Office to monitor pregnancy history to reduce maternal mortality. Conclusion = Results of our study indicate that a district-based decision support system is easy to use to reduce maternal mortality. The study's findings indicate a need for tremendous support from the government to make policies based on a decision support system for appropriate maternal and child health services.
Efforts to Improve the Quality of Learning of PKN Unity and Unity Material in Diversity Through Team Game Tournament (TGT) Methods in Students of Grade IV C SDN Perigi 01 Years of Lessons 2019/2020

The low quality of PKn learning in students of grades IV-C at SDN Pondok Kacang Timur 03 years of lessons 2019/2020 memotiti researchers look for solutions how efforts in improving the quality of learning PKn through the Team Game Tournament (TGT) method. After the study was found 1) Student test results in cycle I meeting 1 obtained an average of 55.42 student test results with a completion percentage of 25%, cycle I meeting 2 obtained an average of student test results 63.33 with a completion percentage of 38%, cycle II meeting 1 obtained an average of student test results 72.50 with a percentage completion of 54%, cycle II meeting 2 obtained the average student test results 85.83 with a completion percentage of 100%, Showed significant improvement in performance. 2) The application of cooperative learning through TGT can improve the quality of students' civic education learning outcomes. The average grade of student test results each cycle increases. In cycle I meeting 1 obtained an average of student test results 55.42 with a percentage completion of 25%, cycle I meeting 2 obtained an average of student test results 63.33 with a percentage completion of 38%, cycle II meeting 1 obtained an average of student test results 72.50 with a completion percentage of 54%, cycle II meeting 2 obtained an average of student test results 85.83 with a completion percentage of 100%, Showed significant improvement in performance. The advice that can be given from the results of this class action research is 1) The application of a learning model with the Type team games tournament as one of the alternative learning models for teachers that can improve the quality of civic education learning. 2) Tournament games in the TGT learning model, should be designed in such a way that students are more interested and can improve the quality in students who can ultimately improve their achievements.
User Interface Design of a Mobile Application for Creating Digital Posters

The purpose of this study was to determine the user interface design of mobile application in making attractive digital posters. The mobile application for making this poster is targeted at users who are unfamiliar also with the minimum skills. Where users can take advantage of free tools and templates that can be used by custom. The method used in this research is a descriptive visual method by testing an application called Canva. This poster maker application provides many templates in various formats. They also provide a choice of images, fonts, or some other design object. Applications for making posters are perfect for individuals who have many activities for promotion. It can be used for school activities, offices, competitions, even for an online shop. All of this can be done easily by using an effective and efficient mobile application to convey information. the conclusion is that a good application is one that easy to use. This criterion is important for choosing the best application that is easy to use by everyone.
Pengembangan Media Timeline Interaktif Untuk Meningkatkan Kemampuan Berpikir Kronologis Siswa

This study aims to: 1) Know how the process of developing interactive timeline media for the history learning of high school students in grade XI. 2) Analyzing the feasibility of the media and the effectiveness of learning after using the interactive timeline media for class XI students at SMAN 2 Padang. The method used is research development, by following the steps of developing the ADDIE model (Analyze, Design, Development, Implementation and Evaluation). The subject of this research trial consisted of 33 students of SMA Negeri 2 Padang class XI IPS 2. In this study a feasibility test was conducted based on the assessment of 2 material experts and 2 media experts to see the feasibility of the media before the trial. In addition, practicality tests were also conducted by history class XI teachers and 33 students to see the practicality of the interactive timeline media. The results showed that the feasibility of the media based on the assessment of the material experts stated that the interactive media timeline was very feasible to use with the average research data of 4.49, while the feasibility based on the assessment of the media experts stated that the interactive timeline media was very feasible to be used with the research average of the media obtained a score of 4, 26. The research product is effective in improving students' chronological thinking ability with an ngain of 0.68 and is categorized as moderate. Research products are also categorized as very practical by teachers and students with an average value of 4.75 and 4.50.
Peace Education as a Catalyst for Sustainable development in nigeria

Over the last two decades of Nigeria’s transition from military to civilian rule, the country has experienced series of conflicts, crises and crashes. The repeated inadequacies of the government to tackle this menace has disillusioned many Nigerian citizens. It appears the efforts made by the government are not good enough. The thrust of this paper is to look at peace education as a catalyst for sustainable development in Nigeria. The paper looks at the concepts of peace and peace education, strategies for peace education, sustainable development as well as peace education and sustainable development in Nigeria. The paper concludes that Nigerians must embrace peace education in all facets of our daily life until lasting peace is attained in the country.
The Future of Blockchain Tech in Transactional Business

"This paper represents an attempt at a thorough analysis of the complexity of blockchain technology &amp; cryptocurrencies while reviewing the core aspects of the development stages that this growing market has undergone and where it may lead. Additionally, we provide a review of current obstacles and advantages for wider adoption of such disruptive tech in banking &amp; fintech industries for its potential for fast, cheap and secure transactions and mass utilization prospective. Considering such benefits and advantages, we have to ask the question of whether there is a need for the middleman transaction participants in the future digital economy. In order for this innovative and disruptive tech to become truly global, we need to go through four phases of development presented in the development matrix. Using various examples, our analysis puts the blockchain tech &amp; crypto at the current second development phase. The main obstacle to move from the second to the third, and subsequently, the fourth and final phase remains the absence of unified legal framework and regulations in key global economies such as the United States and the European Union. Once the legal foundation is established by the G20 economies, regulating cryptocurrency use, trading and taxation, the transition to this final phase should be rapid, and will be followed by mass adoption, with more than a quarter global population fully utilizing and enjoying the benefits of blockchain tech innovation and cryptocurrencies."
The analysis of risk assessment for the transmission of COVID-19 by using PROMETHEE and ELECTRE methods

Multi-Criteria Decision Making (MCDM) methods help researchers in solving many problems in terms of numerical analysis.However, MCDM methods have not been very popular in the health sector.In this study, five ones of Turkey's most intense and highly populated cities were selected and the risk of the spread of Covid-19 disease was evaluated on the basis of seven criteria.The PROMETHEE and the ELECTRE methods were conducted to rank the cities in terms of the spread of Covid-19.The PROMETHEE method correctly ranked the most risky city as Istanbul, but ELECTRE ranked Istanbul the second most risky.The results of the methods are compared with real data.PROMETHEE gave more convenient results than ELECTRE.Also, this paper offers a new field of study to the literature.
Image Forgery Detection Using Neural Network In Python

The advancements of technology in every aspect of the current age are leading to the misuse of data. Researchers, therefore, face the challenging task of identifying these manipulated forms of data and distinguishing the real data from the manipulated. Splicing is one of the most common techniques used for digital image tampering; a selected area copied from the same or another image is pasted in an image. Image forgery detection is considered a reliable way to verify the authenticity of digital images. In this study, we proposed an approach based on the state-of-the-art deep learning architecture of ResNet50v2. The proposed model takes image batches as input and utilizes the weights of a YOLO convolutional neural network (CNN) by using the architecture of ResNet50v2. In this study, we used the CASIA_v1 and CASIA_v2 benchmark datasets, which contain two distinct categories, original and forgery, to detect image splicing. We used 80% of the data for the training and the remaining 20% for testing purposes. We also performed a comparative analysis between existing approaches and our proposed system. We evaluated the performance of our technique with the CASIA_v1 and CASIA_v2 datasets. Since the CASIA_v2 dataset is more comprehensive compared to the CASIA_v1 dataset, we obtained 99.3% accuracy for the fine-tuned model using transfer learning and 81% accuracy without transfer learning with the CASIA_v2 dataset. The results show the superiority of the proposed system
PELATIHAN PEMANFAATAN APLIKASI RUMAH BELAJAR UNTUK MEMBANTU PEMBELAJARAN PADA MASA PANDEMI BAGI GURU-GURU DI YAYASAN WALADUN SHOLEH

Learning that takes place at the Waladun Sholeh school is carried out online by utilizing several learning platforms, but there are some educators/teachers who are still lacking in literacy in the utilization and use of learning platforms, one of which is the Learning House portal. Therefore, it is necessary to train in the use of learning houses for learning during the pandemic for educators/teachers. Training on the use of learning houses for learning during the pandemic was carried out as a solution to the problem of lack of literacy in the use and utilization of learning portals. This training was wrapped in the form of community service and was held on December 17, 2021 at the Bill Gates Computer Laboratory, Department of Informatics, which was attended by 20 school teachers, Waladun Sholeh. The training provided is registration materials in the study house, uploading and downloading materials at the study house. As a result, 97.65% of participants stated that they were very satisfied with the training provided.
Adaptive Balance Optimizer: A New Adaptive Metaheuristic and its Application in Solving Optimization Problem in Finance

Adaptability becomes important in developing metaheuristic algorithms, especially in tackling stagnation.Unfortunately, almost all metaheuristics are not equipped with an adaptive approach that makes them change their strategy when stagnation happens during iteration.Based on this consideration, a new metaheuristic, called an adaptive balance optimizer (ABO), is proposed in this paper.ABO's unique strategy focuses on exploitation when improvement happens and switching to exploration during stagnation.ABO also uses a balanced strategy between exploration and exploitation by performing two sequential searches, whatever circumstance it faces.These sequential searches consist of one guided search and one random search.Moreover, ABO also deploys both a strict acceptance approach and a non-strict acceptance approach.In this work, ABO is challenged to solve a set of 23 classic functions as a theoretical optimization problem and a portfolio optimization problem as the use case for the practical optimization problem.In portfolio optimization, ABO should optimize the quantity of ten stocks in the energy and mining sector listed in the IDX30 index.In this evaluation, ABO is competed with five other metaheuristics: marine predator algorithm (MPA), golden search optimizer (GSO), slime mold algorithm (SMA), northern goshawk optimizer (NGO), and zebra optimization algorithm (ZOA).The simulation result shows that ABO is better than MPA, GSO, SMA, NGO, and ZOA in solving 21, 18, 16, 11, and 8, respectively, in solving 23 functions.Meanwhile, ABO becomes the third-best performer in solving the portfolio optimization problem.
A Radial Basis Network-based Early Warning Algorithm for Physical Injuries in Marathon Athletes

For marathon runners, a single injury may affect their lifelong athletic career, so their injury management is very important.The current injury management for marathon runners has a certain lag, and the current injury warning is mainly based on manual teams, which is costly and poorly automated.To solve these problems, the study proposes a marathon athlete physical injury warning algorithm based on inertia weight adjustment optimized radial basis network.Particle swarm optimization technology has also been incorporated into early warning algorithms.Finally, an athlete injury and disease early warning model is constructed based on the algorithm.The results of performance tests show that the algorithm has a minimum fitness function value of 0.13, which is significantly lower than the current algorithm used for comparison.In the test with real data, the MAPE of the proposed algorithm was as low as 7.598% and the agreement of the hazard score results with the expert human assessment reached 100%.The results of the study indicate the practicality of the algorithm to assist work teams and perform early warning of physical injuries in athletes.However, the high number of iterations required is a limitation awaiting resolution.
Chinese Sign Language Recognition Based on Two-stream CNN and LSTM Network

Sign language recognition is the use of computer technology to convert sign language into text or speech to facilitate the communication between deaf-mute people and normal people. This paper takes Chinese sign language words as the research object, and proposes a new method of sign language recognition based on two-stream 3D-CNN and LSTM network. First, the key frame extraction algorithm is used to remove redundant data frames in the original data, and then a two-stream3D-CNN is used to learn local hand change features and global trajectory features at the same time, and aggregated as the feature input of the video clip to the LSTM codec network. In order to focus on the video frames that express the meaning of sign language, a time attention mechanism is introduced in the LSTM encoding and decoding network. On the DEVISIGN-D sign language data set, an experiment was compared with three sign language recognition algorithms, the experimental results show that the method can identify Chinese isolated words sign language very well, with an accuracy rate of 98.4%.
Realization of social information system using React.js and Redux

The article analyzes technologies and selects tools for creating a system. Professionals can provide their skills and knowledge by expanding the knowledge base of the platform. Mentors can publish articles on various business topics. Any user will have access to an extensive database of information about the latest industry trends, answers, and recommendations on topics of interest, read about real examples of the company's work and learn about the points of view of experts on various topics. This article provides an overview of the information system to facilitate knowledge sharing and the means to create it. A system was implemented that is a web-based mentoring platform and a knowledge database created and managed by users of the platform. Through communication and collaboration, platform users share knowledge. They can gain and exchange experience, resources, ideas, and solutions.
Fraud Mitigation in Attendance Monitoring Systems using Dynamic QR Code, Geofencing and IMEI Technologies

Attendance monitoring is a vital activity in several organizations.Due to its importance, many attendance monitoring systems have been developed to automate this process.Despite several advancements in automated attendance management solutions, attendance fraud remains an issue as some end users can manipulate known vulnerabilities, such as proxy attendance, buddy-punching, early departure, and so on.In this paper, a fraud-resistant attendance management solution is developed by harnessing technologies such as geofencing, dynamic QR code and IMEI Checking.The proposed solution is comprised of a single-page web application where QR code can be enabled for attendance registration, and a mobile application, where endusers can scan generated QR code to register their attendance.Attendance cheating via QR code sharing is prevented by encoding the polygonal coordinates of the event venue in the QR code to determine if the user is within the venue.The proposed system solves the problem of proxy attendance by registering and verifying the end user's device IMEI number.Results obtained from testing indicate that attempts at committing a variety of attendance frauds are effectively mitigated.
Utilizing Deep Reinforcement Learning and QLearning algorithms for Improved Ethereum Cybersecurity

The purpose of the research is to explore and develop Deep Reinforcement Learning and Q-Learning algorithms in order to improve Ethereum cybersecurity in contract vulnerabilities, the smart contract market and research leadership in the area. Deep Reinforcement Learning (Deep RL) is gaining popularity among AI researchers due to its ability to handle complex, dynamic, and particularly high-dimensional cyber protection problems. The benchmark of RL is goal-oriented behavior that increases rewards and decreases penalties or losses, and enhances real-time interaction between an agent and its surroundings. The research paper examines the three major cryptocurrencies (Bitcoin, Litecoin and Ethereum) and the role played by cyber-attacks.The Design Science Research Paradigm as applied in Information Systems research was used in this research, as it is hinged on the idea that information and understanding of a design problem and its solution are attained in the crafting of an artefact. The proposed constructs were in the form of Deep Reinforcement Learning and Q-Learning algorithms designed to improve Ethereum cybersecurity. Smart contracts on the Ethereum blockchain can automatically enforce contracts made between two unknown parties. Blockchain (BC) and artificial intelligence (AI) are used together to strengthen one another's skills and complement one another. Consensus algorithms (CAs) of BC and deep reinforcement learning (DRL) in ETS were thoroughly reviewed. In order to integrate many DCRs and provide grid services, this article suggests an effective incentive-based autonomous DCR control and management framework. This framework simultaneously adjusts the grid's active power with accuracy, optimizes DCR allocations, and increases profits for all prosumers and system operators. The best incentives in a continuous action space to persuade prosumers to reduce their energy consumption were found using a model-free deep deterministic policy gradient-based strategy. Extensive experimental experiments were carried out utilizing real-world data to show the framework's efficacy.