Reviewerly/exHarmony huggingface dataset:
Empirical Study on Hybrid technique to predict customer’s intention

Customer churn is one of the most important metrics for a growing business to evaluate.While it's not the happiest measure, it's a number that can give a service oriented company, the hard truth about its customer retention.The churn rate, also known as the rate of attrition or customer churn, is the rate at which customers stop doing business with an entity.It is most commonly expressed as the percentage of service subscribers who discontinue their subscriptions within a given time period.It is also the rate at which employees leave their jobs within a certain period.For a company to expand its clientele, its growth rate (measured by the number of new customers) must exceed its churn rate.Purposes behind customer churn might be the disappointment with the nature of administration, high costs, ugly plans, no comprehension of the administration design, awful help, and so on.This paper gives emphasis on a hybrid data mining techniques which involves Decision Tree and Logistic Regression which is used to create the prediction model to predict the intention of the customers in service oriented organization.
Pembinaan Akuntansi Berbasis SAK ETAP Untuk Perusahaan Manufaktur Mengunakan MYOB Accounting V17 Di SMK Batam Business School

Vocational High Schools that are located close to each other, but have not synergized in the utilization of existing resources in each school are seen as less efficient. On the other hand, several vocational schools have adequate resources and potential to expand and simultaneously improve education services to the community through various education and training programs. In connection with these conditions, the Directorate of Vocational High Schools has programmed to combine these schools in one management and increase the capacity of Vocational High Schools through various education and training programs under the name Development of Large Vocational Schools. Financial statements function as a tool to analyze financial performance that can provide information about financial position, business, performance and cash flow so that it can be used as a basis for making economic decisions. The object of this service is aimed at the Batam Business School Vocational High School (SMK) around the Sekaran Village, where the majority of Batam Business School Vocational High School (SMK) players do not have financial reports. The purpose of this service program is to provide training to Batam Business School Vocational High School (SMK) actors in the preparation of accounting standards based on Financial Accounting Standards for Entities Without Public Accountability (SAK ETAP) as well as to design simple manual and computerized accounting systems that can help and facilitate students. Vocational High School (SMK) Batam Business School actors in making financial reports based on SAK ETAP
Analisis Sentimen Twitter Kuliah Online Pasca Covid-19 Menggunakan Algoritma Support Vector Machine dan Naive Bayes

&#x0D; &#x0D; &#x0D; The World Health Organization (WHO) COVID-19 is an infectious disease caused by the Coronavirus which originally came from an outbreak in the city of Wuhan, China in December 2019 which later became a pandemic that occurred in many countries around the world. This disease has caused the government to give a regional lockdown status to give students the status of "at home" for students to enforce online or online lectures, this has caused various sentiments given by students in responding to online lectures via social media twitter. For sentiment analysis, the researcher applies the nave Bayes algorithm and support vector machine (SVM) with the performance results obtained on the Bayes algorithm with an accuracy of 81.20%, time 9.00 seconds, recall 79.60% and precision 79.40% while for the SVM algorithm get an accuracy value of 85%, time 31.60 seconds, recall 84% and precision 83.60%, the performance results are obtained in the 1st iteration for nave Bayes and the 423th iteration for the SVM algorithm&#x0D; &#x0D; &#x0D;
Features Selection for Supervised Learning Using Centrality Measures

The data mining methods have been extensively used in the process of decision making. The popularity of data mining methods is due to availability of high speed algorithms, processing and storage power of computers. The effective use of data mining methods help in mining datasets and taking better decisions. The data need to be preprocessed before applying data mining methods. Some datasets require little preparation like dealing with missing and redundant instances while some high-dimensional datasets require strong processing like dimensionality reduction. One of the techniques used for dimensionality reduction is feature selection. This study uses graph based centrality measure for feature selection. Graph based centrality measures are used for ranking features which is used for removing irrelevant attributes. After comparison of results with other approaches, it has been found that the proposed approach results in reduction of feature space without compromising accuracy. The results also shows that proposed approach performs better than some other feature selection approaches not only in terms of accuracy but also on the basis of larger reduction in feature space.
Using Big Data in Social Science - Perspectives and Limitations

The article provides an overview of the development of big data technologies in terms of the potential of their use in the study of social processes. The development of these technologies makes it necessary to transform the usual methods of scientific research and revise the models of social reality. To meet the demands of the modern world, the researcher needs to adopt digital tools. However, the relevance of the stated topic is not limited solely to the possibilities, since the use of digital technologies in the study of society is associated with many risks that can lead to negative consequences. Speaking about the sphere of big data, it is important to remember that one of the main risks is the violation of the rights and freedoms of other people, therefore, a researcher of social processes must understand and assess the consequences of his actions, guided, first of all, by ethical norms that allow the use of new technologies for the public. the benefits and suppression of the threats of a technogenic society. The authors propose to consider the complex of risks associated with the use of big data technologies, and also present their own approach to their systematization and classification.
System Development for Learning Process Monitoring in Private Lesson Institution Using Codeigniter Framework

The monitoring information system is one of the main functions in managing student data in Generasi Cerdas private lesson. This study provides the results of an analysis and design of a monitoring information system that can be used to facilitate services to students in monitoring including grades and student absence. This application developed using UML Design and PHP Programming with CodeIgniter Framework and use MySQL Database. CodeIgniter is an open source framework in the form of a PHP framework with an MVC model (Model, View, Controller) for building dynamic websites. The resulting application has been able to provide information of teacher, student, student value and student absence data to assist in processing student and teacher data in the Generasi Cerdas private lesson, so that the institution has a faster, more efficient monitoring information system and easier to use.
The Development of an Augmented Reality (AR) Based-Learning Media in Introducing Asean Countries for Elementary Schools

This research is motivated by the importance of developing learning media that is able to change learning more interesting, effective, and increase student activities in the learning era 4.0.This study aims to describe the stages of making AR-based learning media on ASEAN countries material, develop students' abilities in representing the characteristics of ASEAN countries, and analyze the feasibility of AR-based learning media.Research and development have produced products in the form of AR-based learning media on ASEAN countries' material.The stages of the research were carried out by analyzing the material development of ASEAN countries, design, validation, and testing of students individually and in groups.Validation and testing on students is done to get feedback in the form of recommendations for improvement and assessment of aspects of learning, the substance of the material, visual communication, and software engineering, as well as the feasibility of its use for the purpose of making products.In general, the percentage of content expert testing results was 80%, the percentage of media expert test results was 78.8%, the percentage of results in individual students was 85.9%, and the percentage of results in large group students was 86.2%.This shows that AR-based learning media on ASEAN countries' material is in good category so that it is appropriate to be used as a learning medium for students to get the ability to develop the characteristics of ASEAN countries.
Criminal Records Information Retrieval System: A Conceptual Model

This model helps to increase communication between Police and public. It will reduce time &amp; increase the problem solving efficiency in time period it will be more helpful. In this admin is key person, user(police) is also have secure registration &amp; public can communicate with all other users through mail. Here we are going to use clustering technique because it more powerful to forming accurate cluster, speed of creating cluster, identifying crime trend &amp; crime zone ,crime density of state.
Orthographic vs. Semantic Representations for Unsupervised Morphological Paradigm Clustering

This paper presents two different systems for unsupervised clustering of morphological paradigms, in the context of the SIGMOR-PHON 2021 Shared Task 2. The goal of this task is to correctly cluster words in a given language by their inflectional paradigm, without any previous knowledge of the language and without supervision from labeled data of any sort.The words in a single morphological paradigm are different inflectional variants of an underlying lemma, meaning that the words share a common core meaning.They alsousually -show a high degree of orthographical similarity.Following these intuitions, we investigate KMeans clustering using two different types of word representations: one focusing on orthographical similarity and the other focusing on semantic similarity.Additionally, we discuss the merits of randomly initialized centroids versus pre-defined centroids for clustering.Pre-defined centroids are identified based on either a standard longest common substring algorithm or a connected graph method built off of longest common substring.For all development languages, the characterbased embeddings perform similarly to the baseline, and the semantic embeddings perform well below the baseline.Analysis of the systems' errors suggests that clustering based on orthographic representations is suitable for a wide range of morphological mechanisms, particularly as part of a larger system.
Text Summarization and Classification for Indian Language

Over the last few years, there have been significant advances in Text Summarization.Text Summarization can be implemented using two approaches; one is the NLP based approach and another is Deep Learning approach.Text Summarization is a demanding and fascinating field of NLP.It has become important because of the tremendous increase in information and data.Text Summarization is technique of creating a specific and relevant short abstract of text using different ways like books, news articles, research papers, tweets etc. Research is being done to summarize large text documents which are difficult to summarize manually.For English and other foreign languages various automated text summarization systems are available.However very few techniques are available for Indian language such as Marathi.In this paper, two extractive techniques are proposed to summarize large Marathi texts.This paper also performs classification on Marathi text using Marathi headlines dataset.
A logical method for the synthesis of periodic trajectory in a binary dynamical system

A logic method for structural-parametric synthesis of a binary dynamical system with a given periodic trajectory is proposed. This method provides a constructive solution for the considered problem. The attraction region of such a trajectory must coincide with a given subset of the state space. An additional constraint sets the acceptable time for reaching this trajectory from its attraction region. As admissible structures for dynamical models of the synthesis, we consider the following systems: linear systems, systems with the disjunctive and conjunctive right sides. All conditions of the problem are written in the form of a quantified Boolean formula with subsequent verification of its truth using a specialized solver, which gives values of the required parameters of the dynamical model. The software implementation of the proposed method in the form of a composite service is presented. All stages of the parametric synthesis of a Boolean network based on the proposed method are demonstrated in the example of a one-step linear system.
Bank Innovation Capability and Competitive Advantage of Small and Medium Scale Enterprises in Nigeria

Competitive advantage is the heart of a company's performance.It reflects a company's ability to offer consumers greater value either by employing lowering prices or by providing greater benefits and services that justify higher prices.Porter (1985) argues that competitive advantage stems from the many discrete activities a firm performs in designing, producing, marketing, delivering, and supporting its product.Each of these activities can contribute to a firm's relative cost position and create a basis for differentiation.The advantage of the company is grown from the value or benefits that can be created by companies for the buyers.When companies can create excellence through one of the three generic strategies, it will get a competitive advantage (Aaker, 1989).Competitive advantage allows a firm to create superior value for its customers and profits for itself.A firm position itself in the industry through its choice of low cost or differentiation.This decision is a central component of the firm's competitive strategy (Mathenge, 2013).Bank innovations are important vehicles through which banking institutions can turn around performance of small and medium sized enterprises (SMEs) and lead to an incredible change in business performance.Bank/financial innovation is the act of creating and popularizing fresh monetary instruments as well as fresh monetary technologies, institutions, and markets (Cherotich, Sang, Shisia, &Mutung'u, 2015).It involves the design, the development, and the implementation of innovative financial instruments and processes, and the formulation of creative solutions to problems of finance.Bank innovation encompasses institutional, product and process innovations (Alvarez, 2009).Innovation capabilities are the combination of firm abilities to integrate and build resources to develop new products and processes, improve existing products and processes, and new product to market to provide an advantage towards achieving superior performance (Zhang, 2004).Agyei-Mensah (2016) argued that innovationcapability is undoubtedly one primary means by which businesses can adapt to the demands of today's complex and ever-changing business environment.Small and medium sized enterprises around the world encounter constraints and limitations such as limited number of employees, insufficient financial resources, inconsistency in policies, a lack of educational background of the
Penelitian Evaluasi: Kajian Evaluasi Kinerja Institusi aspek Kinerja Penelitian

The purpose of this article is to analyze the evaluation of the institutional evaluation of research aspects. The results of the analysis on several articles that are spoken, performance evaluation, evaluation of several basic factors in evaluating the impact of research for decision making on the development of research proposal performance, theory of institutional evaluation research concepts, research team trails, research management, research impact, research mobilization and research participant groups.
Reinforcement Learning for Data Poisoning on Graph Neural Networks

Adversarial Machine Learning has emerged as a substantial subfield of Computer Science due to a lack of robustness in the models we train along with crowdsourcing practices that enable attackers to tamper with data. In the last two years, interest has surged in adversarial attacks on graphs yet the Graph Classification setting remains nearly untouched. Since a Graph Classification dataset consists of discrete graphs with class labels, related work has forgone direct gradient optimization in favor of an indirect Reinforcement Learning approach. We will study the novel problem of Data Poisoning (training-time) attacks on Neural Networks for Graph Classification using Reinforcement Learning Agents.
Research on the Inheritance and Development of Linear Skills in Guzheng Performance

As a member of plucked stringed instruments, Guzheng, with its granular sound characteristics, constitutes the melody and lines with a strong Chinese national style.The Guzheng playing technique is made up of 4 point like sound in the early spring and autumn period, such as "Tuo", "Muo", "Gou", and "Da" (transliterate), and later developed and innovated linear music skills such as "Tuopi", "Yaozhi", "Lunzhi" (transliterate), etc. Guzheng art has a long history, and its playing techniques are constantly innovating.These innovations in linear techniques give the Guzheng, which is a traditional plucked instrument, the opportunity and possibility to better express linear music.In order to explore the meaning and effect of the linear technique of Guzheng performance on the art of Guzheng performance, this study systematically analyzes the development status, performance effects and training methods of the three Guzheng playing techniques, Tuopi, Yaozhi, Lunzhi.This study further analyzes the technical characteristics of the three techniques of Tuopi, Yaozhi, Lunzhi in guzheng playing, and draws conclusions about the importance of "linear" art in the development of Guzheng.It not only provides references for the performers in the acquisition of the three skills systematically, accurately and scientifically, but also helps the performers to improve their performance levels.
Predicting Stock Price in Python Using Tensor Flow and Keras

One of the most important practices in the financial world is stock trading.The act of attempting to forecast the future value of a stock or other financial instrument listed on a stock exchange is known as stock market prediction.This paper discusses how Machine Learning can be used to predict a stock's price.When it comes to stock forecasts, most stockbrokers use technical and fundamental analysis, as well as time series analysis.Python is the programming language used to forecast the stock market.In this paper, we propose a Machine Learning (ML) method that will be trained using publicly accessible stock data to obtain intelligence, and then use that intelligence to make an accurate prediction.In this context, this research builds a neural network in TensorFlow and Keras that predicts stock market, which is basically a Python scraper that extracts finance data from the Yahoo Finance platform; more precisely, a Recurrent Neural Network with LSTM cells was constructed, which is the current state-of-the-art in time series forecasting.
Klasifikasi Penyebaran Covid-19 Menggunakan Algoritma C4.5 Kota Pagar Alam

Allof countriesinthe world,includingIndonesia faced the Covid-19 pandemicorthecoronavirusatthebeginning of2020.Thisvirus isknownthat firstappearedinHubeiProvince,WuhanCity,ChinaattheendofDecember 2019.The riskofCovid-19transmissioncanbe avoidedwithpublic discipline by reducingactivitiesinthemiddleofa crowdifthere isnoneedandimplementing healthprotocols.Thedevelopmentofinformationtechnology makeiteasierfor peopletoeasily obtaindatathattendstoberedundantandclassificationactivities thatcarriedout by humansstillhavelimitations,especially thehumanability to accommodatedata tobe classified.The amountof datathatentersaninstitutionor organizationevery day,thelongerthemoreitwillbe,thepileofdatawillbe accumulatedsothattheutilizationisnotoptimal.Thisstudy aimedtobuiltthethe classificationofcovid-19databy usingtheC4.5AlgorithminthecityofPagar AlamwiththeCRIPS-DMmethodwiththeX-crossvalidationopratorsmodel. TheresultsobtainedintestingbyapplyingtheC4.5algorithmtotheCovid-19 dataforthecity ofPagarAlamshowthattheaccuracyresultsare86.67%andthe AUC (Optimise) resultsare0.989.
RANCANGAN E-REPOSITORI UNTUK MENDUKUNG KNOWLEDGE MANAGEMENT SYSTEM (KMS) PADA SMA PGRI 24 JAKARTA

This study aims to produce a prototype of a knowledge management system at SMA PGRI 24 Jakarta. Currently, knowledge management, especially regarding standard operating procedures (SOPs) or work references at SMA PGRI 24 Jakarta, has not been carried out, so that the process of reviewing knowledge in the past cannot be carried out due to several factors, including constraints in the process of finding documents or archives. , because the document archiving method still uses conventional or manual methods, there is no computerized archive storage area, and there is no special knowledge sharing or knowledge sharing media so that the knowledge sharing process becomes less than optimal. The research method used is a field study by conducting observations and interviews as well as the waterfall method in the design of the system. The results of the study are the prototype of a knowledge management system (KMS) that can store both tacit knowledges and explicit, which can be a solution for managing standard operating procedure (SOP) documents, helping in the activities of digitizing archiving, searching for documents and as a means of sharing knowledge