Reviewerly/exHarmony huggingface dataset:
Analysis and Verification of Probability in Chinese Double Chromosphere Lottery

Probability theory is an important mathematical branch to study the law of random phenomena.Its application widely exists in our life.As a typical random experiment of classical probability model, lottery is an excellent material for the study of probability theory.Similarly, the study of various probability problems in lottery can also guide the real lottery activities.This paper will explore the probability information hidden in the double chromosphere, one of the two staterun lotteries, from the perspective of probability theory and answer the important question that many lottery people are concerned about-what is the specific odds of winning the lottery?Is it realistic to buy lottery tickets to get rich?Finally, the relevant conclusions are verified by publishing the data of double chromosphere lottery.
Volatility Spillovers of New Cryptocurrencies Over Traditional Cryptocurrencies in the NFT Market: A Case Study of Mana

This study uses the DCC-GARCH model to compare the correlation between two types of cryptocurrencies in two different fields.In the context of the popularity of NFTs and the metaverse, new cryptocurrencies based on the metaverse have been favored by investors.Through empirical analysis of mana cryptocurrencies in the NFT market, we find that the new cryptocurrencies in the NFT market have high volatility to Bitcoin, Ethereum, and traditional cryptocurrencies in the past year.Therefore, we conclude that new cryptocurrencies are more likely to be one of the factors for portfolio diversification.
Analysis on the Company Lovepop Using POCD-Model

The analysis of start-up enterprises is one of the important research topics in venture capital.Researchers use many methods to analyze start-up enterprises.However, POCD model is rarely used to analyze start-up enterprises in these methods, and there is still a research gap in the analysis of start-up enterprises with POCD model.So the purpose of research is using POCD to analyze startups in order to show a comprehensive understanding of the POCD model and how to use it to analyze startups.Therefore, the research topic of this paper is how to use POCD to analyze whether startups are worth investing in.The research methods of this paper are as follows: firstly, the data of start-up enterprises are collected, and then a start-up enterprise is selected for analysis.In this study, Lovepop is showed as the research object.The result of the study is that lovepop is at a high risk for investors to invest in lovepop because the industry is in a declining industry, the total revenue of this industry is declining every year, people's demand for this industry is declining, and Lovepop is short of capital, and the initial investment is small.Investors need to bear more investment pressure and they need to be given more investment to help them operate otherwise they tend to run out of money and the company cannot operate.Lovepop should further improve its product quality and technology.
Speech Signal Algorithm Conversion from Sasak Language into Sasak Script with CNN and Rule-Based Method

Sasak speech-language is can't operate in application such as google speech, Alexa assistance, and so on.It makes society need a new development technology who can solve the problem for sasak language.West Nusa Tenggara Province has more than thousand ancient manuscript writen in lontar leaves and papers, that the manuscript spread in Lombok Island and Sumbawa Island.Speech recognition technique for local language is important topic in computer science research, that it can save the culture from the island.This research should be explained how speech processing method working for conversion analog speech signal in Sasak language into Latin text.This study uses the Mel-Frequency Cepstral Coefficient (MFCC) method as a feature extraction method and Convolutional Neural Network (CNN) as a voice classification method into text, and the Rule Base method with UTF-16 which is used to provide rules on Latin letters that will be converted into text.Sasak characters.The algorithm developed is expected to be able to change 50 sound classes into Sasak letters with good accuracy results or above 88%, in changing the voice of the Sasak language into Sasak script by 90.00%.
Implementation of Knowledge Management on Customer Relationship Management System, A Literature Review

Currently the value of a customer (customer's value) is very important in a business competition.For this reason, they continuously improve customer relationships using Customer Relationship Management System (CRM).The implementation of Knowledge Management (KM) can improve the quality of information generated through CRM system.This paper is studied how far the implementation of KM on CRM system has occurred and its impact.What is Customer Knowledge Management (CKM) as a result?Using the Literature Review method and several comparisons to produce an understanding of the application of KM on CRM system, and then use as reference for case study implementing KM on CRM.
Using Phase Coding Method for Audio Steganography with the Stream Cipher Encrypt Technique

One of the most popular audio file formats suitable for hiding information is Windows Audio-Visual (WAV).The two main areas of modification in a WAV file for data embedding are the storage environment and digital representation of the signal that will be used.In order to conceal secret messages successfully, a variety of methods for embedding information.The proposed system consists of four steps of steganography techniques; encoding, embedding, extraction and decoding.The trend of the test results from the 10 audio tested, showing a decrease in the PSNR value along with the increase in the size of the embedded message.This is in accordance with the theory that the greater the embedded information, the smaller the PSNR generated the steganography system using the phase coding method with the addition of stream cipher encryption has been successfully implemented.The system works well, as indicated by the success of the embedding and extraction tests, as well as the test results from BER.The PSNR test itself gets good results when the size of the embedded message is not more than 45% of the cover size.
Central Bank Digital Currencies-Embrace the Future

In the 21st century, digital currency has attracted much attention in financial technology (Fintech).Currently being seriously explored by most of the world's major central banks, electronic money, the innovative product of the digital economy, may have a significant impact on the macro-financial pattern and financial stability.This paper breaks through geographical restrictions to study electronic currency in major countries and explores the motives and risks of launching electronic currency in China.
Design of Physical Education Teaching Quality Evaluation System Based on BS Architecture

In order to solve the reliability of the traditional physical education quality evaluation system, this paper designs a physical education quality evaluation system based on the BS architecture.First, in the hardware aspect of the system, there will be a design about data sets and analog-to-digital converters; then That is, while carrying out the system design, the instruction and contribution of the quality evaluation of physical education are determined.The purpose of evaluating physical education teaching is to make the teaching plan more clear and clear, so that learners can adapt and learn more quickly.It also plays a great role in the teaching process of the physical education teaching quality evaluation system.The BS architecture is a more new application structure.The purpose of the system design is to enable the physical education system to be based on the BS architecture, so that better students can be better educated, and physical education can be improved.The system design of this paper is mainly carried out through the BS structure, and the functions brought by the BS structure are used to further improve the physical education teaching.Use data to analyze the BS structure, and at the same time integrate the BS structure into physical education teaching, and use mathematical statistics to analyze the learning effect of the evaluation system and participate in the teaching objectives and other dimensions, which have a great impact on the quality evaluation of physical education.Influences.The result of the research on the design of the physical education quality evaluation system based on the BS structure is that to some extent, it can make physical education better, and can attract more students to participate in physical education and learn more from it.The same can be achieved with the practicality and creativity of the BS framework for physical education.Allow more students to change the concept of physical education teaching and carry out physical education independently.
Research on the Development of Digital Online Education in Colleges and Universities During the Period of COVID-19

Digital online education makes up for the shortcomings of traditional education.In the face of the impact of COVID-19 (Corona Virus Disease 2019), digital online education can better ensure the continuity of students' learning and evaluation.At present, the sharing of digital resources is the top priorities of digital online education, and there are still some problems to be solved.In the context of COVID-19, this paper analyzes the significance and development status of digital online education in colleges and universities, explores its sharing mechanism to improve the sharing and utilization of online resources, and puts forward corresponding countermeasures for promoting the construction and development of high-quality video open courses.It is of great significance to promote the modernization of higher education.
The Effect of the Performance of Gas Station Operators on the Use of the MyPertamina Application in PT. Satria Citra Kencana

The use of the MyPertamina application influences the lower middle class.The limited information and the exposure of the lower middle-class community have implications for the realization of the distribution of subsidized fuel oil.The writing of this article aims to determine the effect of the performance of gas station operators on the use of the MyPertamina application in PT.Satria Citra Kencana uses qualitative research methods by collecting data using observation and interviews with gas station operators.The result of this study is that the presence of the MyPertamina Application brings a positive influence on gas station operators pt.Satria Citra Kencana is a power that arises from people who form characters and characters, where gas station operators immediately understand the use of the MyPertamina application and help the community in its use.
A Hybrid Teaching Model for the Software Requirement Analysis and Modeling Course

The Software Requirement Analysis and Modeling course, as a core course of software engineering, is extremely difficult to provide knowledge to students because of its ambiguity, uncertainty, variability and subjectivity.To solve the problem, a hybrid teaching model is proposed in which flipped classrooms, case-centered teaching, and scenario-based teaching are integrated used.In addition, designing software prototype as a part of requirements verification is added into course.By comparing to traditional prototyping tools, the preliminary software requirement and modeling can be validated better.Through practice, the hybrid teaching model can further improve students' learning and has guiding significance for the reform of the courses in software engineering.
Distance Estimation Using Low Calibrated Tx in BLE’S Advertising Mode for COVID-19 Contact Tracing

The ability to estimate distance between people has been an important aspect in contact tracing especially in this Covid-19 pandemic.This is because, distance is one of the crucial element in determining whether a person is a close contact or not.In this context, Centers for Disease Control (CDC) and Prevention has provided a guideline to be followed, which is the distance of no more than 6-feet (~2 m) to be accepted as close contact.With regards to that, many of the solutions in existence are adopting Received Signal Strength Indicator (RSSI) in Bluetooth Low Energy's (BLE) connected mode to determine distance.However, the mainstream approach has two main setbacks and they are: (1) Unreliable reallife implementations and (2) Ability to cater for limited number of users which makes it unscalable.Thus, in providing some closure, our study proposed using low calibrated Transmission Power, Tx, in BLE advertising mode for indoor scene, to effectively conduct distance estimation for the pandemic.Results obtained have shown that our proposed solution has a maximum error of 0.3209m in distance estimation within the distance of 2 m.Contributions of this study is two-fold:(1) It provides a novel approach in estimating distance using BLE's RSSI in the advertising mode utilising low calibrated Tx and (2) The proposed solution eliminates limited number of users that makes it scalable.
Optimization of Data Mining for Grouping Courses Using the MDDS and MAR Methods

To find meaningful clusters from a data set, attribute clustering is carried out, so that the attributes in the created cluster will have a high or very good correlation, as well as interdependence with each other.While the attributes in the other clusters are less correlated or more independent.The experimental results show how to determine the list of dominant attribute ratings using soft set theory.A series of experiments were conducted to evaluate the clustering performance, clustering efficiency and scalability of the MAR and MDDS algorithms.The experimental results show that, MDDS achieves better clustering accuracy and stability than the MAR algorithm, at the same time increasing efficiency.MDDS has clear advantages over MAR on large data sets in terms of clustering efficiency as well as clustering accuracy.In addition, the MDDS technique has better scalability.It can be applied to small category data sets as well as large category data sets.The clustering of data under soft set theory can be considered as a technique for data mining.Maximum Degree of Domination in soft set theory is applied to select grouping attributes.In the assessment of student lectures to determine the optimal clustering attributes, and get the best value is very urgent in data clustering.So in the assessment of lecturers' lectures on the subjects being taught, in order to get optimal results, clustering of lecture assessments is needed.Actually, there are five types of methods and techniques, based on coarse and soft sets, to select the attributes for grouping course assessments, namely TR, MMR, MDA, NSS, and MAR.However, the MAR method has better numerical computational time, compared to the other four approaches.In the MAR method, there is a drawback, namely the execution time is still slow, because in the iteration process it determines the relative attributes.So to overcome these problems, use an alternative technique based on soft sets to select clustering attributes, namely the Maximum Degree of Domination in Soft set theory (MDDS) method.In this method, the steps in defining the multi soft set are explained first.Then determine the dominance of the soft set and its degree.Then the maximum degree of dominance will be used to determine the best grouping attributes in the assessment of student lectures.The results of the experimental data obtained show that the MDDS technique is very good, and can significantly reduce the numerical computation time.
Design and Build a Mobile-Based Pet Care Information System with Personal Extreme Programming Method

Pets are animals that are tamed and cared for by their owners and have an emotional bond between the two that will form a relationship.The high interest in raising animals has led many communities and animal lovers because animal owners have the same interest in caring for and caring for animals.The author has interviewed several animal lovers in the city of Mataram.Five out of seven animal lovers who have left their pets at a pet shop experience the same problem: it is difficult to find a reliable place of care when they want to travel far.It is not possible to bring their pets to that time.Three out of five people are more confident in entrusting their pets to the animal lover community because the care and maintenance carried out by pet shops are often not optimal; The high cost of the pet shop is also an obstacle.Based on these problems, the authors created a "Mobile-Based Animal Care Application", which is a forum that connects fellow animal lovers who need each other's help to deposit and care for their pets according to the desired facilities and budget.Work on this system is carried out by the author individually.This author must handle changes in the system's functionality that will be developed according to what the client wants quickly and precisely.Therefore, this application is made using the PXP method, which makes it easy to handle changes in the system's functionality to be developed because PXP has a high level of flexibility in planning and implementing an application/software.This application system will use the Java programming language and firebase for data storage in its design.From the test after developing and making the system, the results obtained from black-box testing with the Linkert Scale that all scenarios made are appropriate and can help the needs of the community and clients, the score for strongly agree is 50% from the client-side and 57.1% from the community side.
Relationship Invasion Games on Mobile Learning-Based Media PJKR FIK UM

This study aims to analyze the need for mobile learning-based learning media on basketball invasion materials.This research is a qualitative descriptive study, the subjects of this research are students of the Department of Physical Education, Health and Recreation, Faculty of Sports Science at Malang State University batch 2020.The samples were selected randomly.Collecting data using a questionnaire.The results of data collection needs analysis, there are 2 types of learning media in the form of sipejar and youtube, support devices for the learning process 61% laptops, 78% mobile phones, 58.9% students never use application-based media, and 56% of students stated the need for development application-based learning media.It was concluded that students of Physical Education, Health and Recreation needed a development of learning media based on mobile learning invasion materials.The following factors make there must be a mobile learning-based learning media, namely the supporting devices owned by students are adequate and teaching materials in the subject of the invasion material are still limited.
Modern educational landscape and stem approach to education: transformation of traditional environments for training engineers

Relevance.Avalanche-like technologies that require high-quality engineering education for their development and implementation, for the sustainability of the economy, are in dire need of a comprehensive way to solve super-complex tasks and problems.The emerging problems sometimes cannot be solved by the old methods within the existing distinctions.The relevance of the study is caused by the need to search for new approaches and educational technologies in the system of engineering education.Purpose.The purpose of the work is to consider new, interconnected and mutually dependent resources that feed the idea of continuity of professional engineering and technological education.Research methods.The author's research uses such methods as: analysis of theoretical ideas about engineering economics, technological education, transdisciplinarity and continuity of education for an engineer of the future; analysis of pedagogical and research experience in the field of technological education; a local expert survey conducted in December 2021 in an online format -to identify the problems and opportunities of today's popular STEM education; content analysis of answers to open-ended questions offered to respondents working in STEM technology.Scientific novelty/theoretical and/or practical significance.Conclusions are drawn about the need to reflect on the special equipment and responsibility in relation to the technological educational space.Results.Based on the research, the article presents a view on the duality of training engineers of a new formation, on combining their theoretical training with the cultivation of the ability to practically solve production problems.It is shown that transdisciplinarity sets the most important vector for the development of technological education.Conclusions.Integration, transnationalization, information openness, commercialization and digitalization of all aspects of life place new demands on the education, development, and training
Black Box Testing with Equivalence Partitioning and Boundary Value Analysis Methods (Study Case: Academic Information System of Mataram University)

Mataram University Academic Information System (SIA UNRAM) is software built and managed by UPT PUSTIK to make it easier for users to manage various academic data and academic information at Mataram University.Although the system has been developed, the users still discover the system's lack of features and functions.So, this study aimed to test the SIA system.Software testing is a significant thing to do so that the result of the device is appropriate to the user's needs.Moreover, it can detect and reduce the errors contained in the software.Black box testing is one of the software testings that focuses on functionality.Equivalence partitioning and boundary value analysis are used as the research methods.The final result of this study found various feature errors in 4 SIA actors at Mataram University, including students, lecturers, study program operators, and faculty operators.This test found that the total test cases were 322 scenarios, with 242 test cases passing and 80 defects, so the average test case pass percentage was 75.16%.UPT PUSTIK uses these results to evaluate and improve the SIA software at Mataram University.
Autoencoders with Reconstruction Error and Dimensionality Reduction for Credit Card Fraud Detection

The increase in credit card transactions has inevitably caused an increase in credit card fraud.A total of 157,688 fraud cases occurred in 2018 worldwide, causing a total loss of $24.26 billion.This paper proposes using two types of autoencoder models to detect credit card fraud.The first type uses reconstruction error to detect anomalies in the data.The model detects fraud by defining a threshold in the reconstruction error to flag the transactions as legitimate or fraud.The second type performs dimensionality reduction to encode the data and removes noises.The encoded data were then used to train three other models: K-nearest neighbours (KNN), logistic regression (LR), and support vector machine (SVM).We then applied these models to a European bank's imbalanced credit card data set.A comparison was made between the two autoencoder types and three baseline models: KNN, LR and SVM.The results showed that both autoencoders gave a good and comparable performance in detecting credit card frauds.