Reviewerly/exHarmony huggingface dataset:
Web-Based Student Extracurricular Value Monitoring Application

Extracurricular is a program of activities outside of the regular teaching and learning activity agenda prepared by the school for its students in order to develop the talents and interests of their students. In one of the upper secondary education institutions that provide several extracurricular activities to its students. The current problem is the lack of optimal extracurricular management in one of the educational institutions in Bandung, starting from the registration process, monitoring, to activity reports that still rely on conventional systems. The purpose of this research is to design a website information system to support the management of extracurricular activities at an institution in the city of Bandung by utilizing a database-based application. The research method used is data collection techniques and waterfall software development methods in designing applications. So that this research produces a website information system with several levels of access rights in accordance with the analysis carried out in the early stages of software development. The results of this information system, the parties involved as actors in extracurricular activities In one institution in the city of Bandung are very helpful in managing and monitoring extracurricular activities carried out So that this research produces a website information system with several levels of access rights in accordance with the analysis carried out in the early stages of software development. The results of this information system, the parties involved as actors in extracurricular activities In one institution in the city of Bandung are very helpful in managing and monitoring extracurricular activities carried out So that this research produces a website information system with several levels of access rights in accordance with the analysis carried out in the early stages of software development. The results of this information system, the parties involved as actors in extracurricular activities In one institution in the city of Bandung are very helpful in managing and monitoring extracurricular activities carried out.
Podcast Media Credibility as a Means of Fulfilling Public Information

In this era of high speed of information flow, a lot of information has the potential to become fake news. Mass media is an essential means of fulfilling public information, so that public trust is greatly influenced by the credibility of the related information media. Podcasts are a new phenomenon in the digital era which has become one of the users of new media to find various information used by the public. This study aims to see how far the credibility of podcast media in conveying information to the public. The type of this research is descriptive qualitative research with phenomenological method. The subject of the research was carried out by observing several podcast platforms, the researcher was only limited to observing to check interview data with content publications on a number of these platforms. The results of this study indicate that the credibility of podcast media in fulfilling public information is quite high because it is one part of the clarification of circulating information by presenting themselves not as anonymous and carried out through in-depth research. Listening to a podcast about a particular theme can stimulate the audience's brain to receive information which is equivalent to reading a book. Information on a podcast is based on the podcaster's specialty. so that with the credibility built, podcasters are able to become accurate and reliable presenters and help stimulate the audience's mind to be able to think further and also imagine a visualization, think more critically, be creative, and get various interesting inspirations
PENGEMBANGAN E-MODUL DENGAN MENGGUNAKAN APLIKASI FLIP BUILDER BERBASIS PROBLEM SOLVING MATA KULIAH PERPAJAKAN PRODI PENDIDIKAN EKONOMI UNIMED

This research aims to develop an E-module using a Flip Builder Application Based on Problem Solving in the subject of Taxation for PPH Chapter 23,24,25, 26, and Chapter 28(a)/29. This research was conducted using the Research and Development (R&amp;D) method. The research and development steps are guided by the ADDIE model (Analyze, Design, Development, Implementation and Evaluation). The development stage has 3 stages, namely 1). Validation test in which there are two validators, namely material experts and media experts. 2). The practicality test is a test from a tax lecturer (one person). 3). The next step is to test the attractiveness of the E-module, namely the individual test (3 people) and the small group test (6 people). limited group trial by distributing online questionnaires. The validation results from material experts and media experts obtained that the criteria could be used with partial revisions results is 85% and could be used with partial revisions with 84% results. The results obtained from the practicality test in which the course lecturers amounted to 91.7% and individual trials and small group trials of 93%. Keywords : E-modul, Flip Builder, Problem Solving
PENGARUH KECERDASAN EMOSIONAL (EMOTIONAL QUOTIENT) DAN LITERASI EKONOMI TERHADAP KESIAPAN MENGAJAR (TEACHING READINESS)

This study aims to analyze the effect of emotional intelligence (emotional quotient) and economic literacy on teaching readiness of students of the 2018 and 2019 Economics Education Study Program students, State University of Surabaya. The research data were taken from 86 students who were analyzed using a quantitative approach with structural equation modeling. (SEM) WarpPLS approach. The results showed that emotional intelligence has an influence on economic literacy, the higher the level of emotional intelligence of students, the higher the economic literacy of students. Likewise, emotional intelligence variables affect teaching readiness, so the higher the emotional intelligence of students, the better their teaching readiness. However, the economic literacy variable has no effect on teaching readiness, so students who have high, medium or low levels of economic literacy have no effect on their level of teaching readiness. Thus, the economic literacy variable does not mediate the influence of emotional intelligence on teaching readiness for students of the 2018 and 2019 S1 Economics Education Study Program students, State University of Surabaya. Keywords : Emotional Intelligence, Economic Literacy, Teaching Readiness
PENGEMBANGAN E-MODUL INTERAKTIF PADA MATERI PELAKU KEGIATAN EKONOMI SEBAGAI PENDUKUNG BAHAN AJAR KEMANDIRI SISWA

The problems contained in learning at SMAN 1 Dsidoarjo about the difficulty of students understanding the material. With the Covid-19 pandemic, the need fpr a teaching material for students in order to be able to better understand the materials provided by teachers such as Electronic Module teaching materials or often called E-modules developed using the Flipbook Application. With that the learning process will be more maximal. This research uses a Research and Development research model designed with a 4-D model (four D-Models, there are 4definition planning (design), development (development), deployment (dessiminate). Rith this teaching material is expected to later be trialled on a wider scale. The subjects of this study amounted to 36 students at positive impact on student understanding and learning autcomes. Keywords: Teaching Materials, Flipbook-based E-modules, understanding the material, student independence
The Synergy of Double Neural Networks for Bridge Bidding

Artificial intelligence (AI) has made many breakthroughs in the perfect information game. Nevertheless, Bridge, a multiplayer imperfect information game, is still quite challenging. Bridge consists of two parts: bidding and playing. Bidding accounts for about 75% of the game and playing for about 25%. Expert-level teams are generally indistinguishable at the playing level, so bidding is the more decisive factor in winning or losing. The two teams can communicate using different systems during the bidding phase. However, existing bridge bidding models focus on at most one bidding system, which does not conform to the real game rules. This paper proposes a deep reinforcement learning model that supports multiple bidding systems, which can compete with players using different bidding systems and exchange hand information normally. The model mainly comprises two deep neural networks: a bid selection network and a state evaluation network. The bid selection network can predict the probabilities of all bids, and the state evaluation network can directly evaluate the optional bids and make decisions based on the evaluation results. Experiments show that the bidding model is not limited by a single bidding system and has superior bidding performance.
PENGEMBANGAN MEDIA PEMBELAJARAN APLIKASI MOLEK (MONOPOLI EKONOMI) BERSISTEM OPERASI ANDROID

The background of this research is about the importance of mastery of learning media for educators in delivering learning materials. The purpose of the study was to determine the feasibility of monopoly learning media, interest in learning and student responses. This research involves material experts and media experts. This research uses the type of research development or Research and Development (R&amp;D) with the development model used is ADDIE The development model used is ADDIE which consists of 5 stages, namely Analysis, Design, Development, Implementation and Evaluation. MOLEK (Economic Monopoly) learning media is an Android-based mobile learning. To measure interest, use a questionnaire with a score of positive and negative statements, while to measure student responses the Guttman scale is used. Implementation of Economic Monopoly Learning Media Implementation of Economic Monopoly Learning Media in class XI students of SMA Muhammadiyah 3 Surabaya was carried out for 20 students. Based on the research results, the development of MOLEK (Economic Monopoly) Learning Media on Monetary and Fiscal Policy Materials in Senior High Schools is declared valid, practical and significant. Validation by material experts got a score of 84% while validation by media experts got a score of 84%. The analysis of student response data obtained a score of 91.5%, it can be concluded that the application of MOLEK (Economic Monopoly) learning media received a very decent response from students. Keywords : Android-based mobile learning, monopoly learning media, interest in learning and student responses
Novel approach of Predicting Human Sentiment using Deep Learning

Due to its interactive and real-time character, gathering public opinion through the analysis of massive social data has garnered considerable attention. Recent research have used sentiment analysis and social media to do this in order to follow major events by monitoring people's behavior. In this article, we provide a flexible approach to sentiment analysis that instantly pulls user opinions from social media postings and evaluates them. As time passed, an increasing number of people shared their opinions on social media. More individuals can now communicate with one another as a result. Along with these advantages, it also has certain drawbacks that cause resentment in some people. Hate speech is another possibility. Hate speech impacts the community when it contains insulting or threatening language. Before it spreads, this kind of speech has to be identified and deleted from social media platforms. The process of determining whether a text's feelings reflect hatred or not involves sentiment analysis. Python language was used to analyze the Twitter dataset. There were 5000 Tweets in total in this dataset, and we used deep learning to improve the machine learning model's accuracy. The experimental outcome in both cases of the Twitter dataset uses the Random Forest approach, which has a 99 percent accuracy rate.
Perkembangan Evaluasi Tata Kelola Teknologi Informasi: Literature Review

Information technology is an important organizational asset to be managed and maximized so that its use can be aligned with business needs, thus helping to improve the achievement of the organization's vision and mission. Therefore, the implementation of information technology governance in every organization needs to be monitored for its implementation, this makes the organization more mature and immediately makes improvements to its management of its IT assets. Various studies have been conducted to evaluate IT governance in organizations using various frameworks. This study aims to conduct a review of previous studies related to the development of IT governance evaluation in reviewing research activities carried out in a certain period, analyzing the framework used and why the framework is used. The results show that research to evaluate IT governance peaked in 2014 which was dominated by the institutional sector using the COBIT 5 framework and the various reasons for using COBIT 5 are discussed further in this study.
Multilingual Speech Emotion Research Based on Data Mining

In order to improve the effect of speech emotion research, this paper combines data mining technology to construct a speech emotion research model and establishes a state space model of speech emotion risk problem. Moreover, this paper uses fuzzy variables to describe the external uncertain environmental factors and intuitively shows the relationship between each technology, that is, clearly shows how actions and external environmental factors affect their action results, which is helpful in understanding the voice emotional risk problem from the root. In addition, this paper uses the basic knowledge of credibility theory to transform the model and finally transform the model into an optimal control problem. Through the speech emotion simulation experiment, it can be seen that the multilingual speech emotion analysis model based on data mining proposed in this paper has a good effect in speech emotion analysis.
Reasonable Agda is correct Haskell: writing verified Haskell using agda2hs

Modern dependently typed languages such as Agda can be used to statically enforce the correctness of programs. However, they still lack the large ecosystem of a more popular language like Haskell. To combine the strength of both approaches, we present agda2hs, a tool that translates an expressive subset of Agda to readable Haskell, erasing dependent types and proofs in the process. Thanks to Agda's support for erasure annotations, this process is both safe and transparent to the user. Compared to other tools for program extraction, agda2hs uses a syntax that is already familiar to functional programmers, allows for both intrinsic and extrinsic approaches to verification, and produces Haskell code that is easy to read and audit by programmers with no knowledge of Agda.
Distinguishing Non-natural from Natural Adversarial Samples for More Robust Pre-trained Language Model

Recently, the problem of robustness of pre-trained language models (PrLMs) has received increasing research interest. Latest studies on adversarial attacks achieve high attack success rates against PrLMs, claiming that PrLMs are not robust. However, we find that the adversarial samples that PrLMs fail are mostly non-natural and do not appear in reality. We question the validity of current evaluation of robustness of PrLMs based on these non-natural adversarial samples and propose an anomaly detector to evaluate the robustness of PrLMs with more natural adversarial samples. We also investigate two applications of the anomaly detector: (1) In data augmentation, we employ the anomaly detector to force generating augmented data that are distinguished as non-natural, which brings larger gains to the accuracy of PrLMs. (2) We apply the anomaly detector to a defense framework to enhance the robustness of PrLMs. It can be used to defend all types of attacks and achieves higher accuracy on both adversarial samples and compliant samples than other defense frameworks.
Efficient Self-Ensemble for Semantic Segmentation

Ensemble of predictions is known to perform better than individual predictions taken separately. However, for tasks that require heavy computational resources, e.g. semantic segmentation, creating an ensemble of learners that needs to be trained separately is hardly tractable. In this work, we propose to leverage the performance boost offered by ensemble methods to enhance the semantic segmentation, while avoiding the traditional heavy training cost of the ensemble. Our self-ensemble approach takes advantage of the multi-scale features set produced by feature pyramid network methods to feed independent decoders, thus creating an ensemble within a single model. Similar to the ensemble, the final prediction is the aggregation of the prediction made by each learner. In contrast to previous works, our model can be trained end-to-end, alleviating the traditional cumbersome multi-stage training of ensembles. Our self-ensemble approach outperforms the current state-of-the-art on the benchmark datasets Pascal Context and COCO-Stuff-10K for semantic segmentation and is competitive on ADE20K and Cityscapes. Code is publicly available at github.com/WalBouss/SenFormer.
Research on the Direction of Marine Science and Technology R&amp;D Policy in the Fourth Industrial Revolution-The case of Korea

In the fourth industrial revolution environment, it has become an important issue to improve the first-stage R&D planning system of the national research and development business of marine science and technology.Taking South Korea as an example, it is of great practical significance for the development of marine science and technology in China to study the research on the direction of marine science and technology R&D policy in South Korea, analyze its shortcomings and limitations, and find improvement measures for the R&D planning structure.
PERANCANGAN SISTEM INFORMASI PEMBAYARAN BIAYA PENDIDIKAN DI UNIVERSITAS MA’SOEM JATINANGOR

Ma'soem University is a university located in the Al Ma'soem Foundation Bandung (YAB). At present Ma'soem University has four Faculties, namely the Faculties: Computers, Faperta, Islamic Business Economics, Teacher Training and Education. With the increasing number of new students every year around 350 people per class, the Ma'soem University finance department must have an information system design that can help and facilitate financial acceptance and report preparation so that it can be produced quickly. The finance department of Ma'soem University is currently using its manual financial management system, where every student who makes a payment is recorded on a proof of payment invoice which is then recapitulated for financial statements. Based on these considerations, it is deemed necessary to design a financial information system that is expected to help facilitate the process of payment of education costs at Ma’soem University.In this Education Fee Payment Information System Design, the writer uses the SDLC (System Development Life Cycle) system development life cycle method, which consists of five stages: analysis, design, code, testing and implementation.The design of this information system is expected to handle the payment of tuition fees with various facilities, namely: can facilitate the search for data of students who have not paid tuition fees, can avoid duplication of data and calculation errors in education costs and is expected to present reports of tuition payment payments quickly and automatically.Ma'soem University is a university located in the Al Ma'soem Foundation Bandung (YAB). At present Ma'soem University has four Faculties, namely the Faculties: Computers, Faperta, Islamic Business Economics, Teacher Training and Education. With the increasing number of new students every year around 350 people per class, the Ma'soem University finance department must have an information system design that can help and facilitate financial acceptance and report preparation so that it can be produced quickly. The finance department of Ma'soem University is currently using its manual financial management system, where every student who makes a payment is recorded on a proof of payment invoice which is then recapitulated for financial statements. Based on these considerations, it is deemed necessary to design a financial information system that is expected to help facilitate the process of payment of education costs at Ma’soem University. In this Education Fee Payment Information System Design, the writer uses the SDLC (System Development Life Cycle) system development life cycle method, which consists of five stages: analysis, design, code, testing and implementation. The design of this information system is expected to handle the payment of tuition fees with various facilities, namely: can facilitate the search for data of students who have not paid tuition fees, can avoid duplication of data and calculation errors in education costs and is expected to present reports of tuition payment payments quickly and automatically.
Research on the Correlation Between COVID-19 and Bitcoin Price Volatility Based on Time-series Model

From 2020 to 2021, COVID-19 spread across the globe, which has a significant impact on the global economy and people's lives.With the development of the COVID-19 pandemic, people's pessimism about the economy has increased, leading to a significant increase in demand for safe-haven currencies and a sharp rise in the price of safe-haven currencies.Bitcoin, the new safe-haven currency, also saw huge price swings during the pandemic.Select bitcoin price yield index for empirical analysis of time series model.First, this paper use ADF to test the stationarity of the time series and establish the ARMA model.Second, the conditional heteroscedasticity of the residual of the model was found through model testing, and then the GARCH model was modeled.Finally, based on the ARMA-GARCH model, through analyzing the relationship between bitcoin price volatility and the development of COVID-19 in China and the US, the correlation between the two is determined.Through research and calculation, this paper concludes that there is an obvious correlation between the COVID-19 epidemic and the fluctuation of the bitcoin return rate.
Algorithm Aversion and Self-driving Cars

Algorithm aversion is the phenomenon that humans tend to resist using algorithms for assisting decision-making, and this aversion has affected the application and spreading of autonomous vehicles, which deploy algorithms.This paper will at first shortly review the researches about algorithm aversion, by mainly referring to the literature review by Burton, Stein and Jensen's in 2020, to address three causes and general solutions for autonomous vehicles industry to alleviate algorithm aversion, the case of Tesla company will occasionally be taken as an example to make detail explanation.Then the article suggests several policies that self-driving car companies can adopt to alleviate influences such as possible sales decline and customers' complaints brought by algorithm aversion, then propose an experiment to verify if these policies are reasonable and feasible, and will finally discuss the limitations of the proposal and this paper and some works that can be done in the future.