bluuebunny/crossref_metadata_2025_split huggingface dataset:
Legitimizing austerity in crisis-hit Greece
Authors: Kitis E. Dimitris , Serafis Dimitris 
Published: March 2020

Abstract
The article examines two key-speeches given by Greek PMs, at crucial junctures of the Greek crisis, both aiming to
legitimize austerity programs to the Greek population. The speeches by Papandreou (Socialists) and Tsipras (Radical Left)
represent critical moments of the crisis as the two PMs prepared to annul their pre-election promises for a cessation of
austerity. Within a CDS framework, we combine Systemic-Functional and Cognitive-Linguistic perspectives to demonstrate that both
speeches, contrary to depoliticized/technocratic (neoliberal) discourse, converge on the construction of a discourse that
privileges ‘the people/nation’ while, contrary to left-populist discourse, obscure any references to ‘the-establishment’. We,
thus, offer evidence of how left-wing discourses (of both established socialists and radical left) publicly (pro-)claim the
reconfiguration of social-democracy while, in fact, capitulating to market demands for neoliberal austerity policies. Findings
corroborate the view that real social-democracy has been neutered at the European level.
Reframing translational norm theory through 4EA cognition
Authors: Robinson Douglas 
Published: March 2020

AbstractNorm theory was invented in 1986, by Daniel Kahneman and Dale T. Miller, as a decision-science subdiscipline of psychology, but with close connections with emerging embodied, embedded, enactive, extended and affective (4EA) cognitive science. Notably, they gave affective response a key role in marking not only the intensity but the cognitive load of norm-formative decision-making. A few years later, in the early 1990s, Gideon Toury, Andrew Chesterman, and other translation scholars began to theorize translational norms—with a very different model that apparently owed nothing to Kahneman and Miller’s pioneering work. In translational norm theory, norms are established based on the rational work of competent professionals, and anyone who doesn’t simply obey those norms cannot be considered a professional. This article rethinks translational norm theory using not only Kahneman & Miller but the later convergence of Merleau-Ponty’s lived experience with cognitive science in 4EA cognition.
Rare events in stochastic processes with sub-exponential distributions and the big jump principle
Authors: Burioni Raffaella , Vezzani Alessandro 
Published: March 2020

Abstract
Rare events in stochastic processes with heavy-tailed distributions are controlled by the big jump principle, which states that a rare large fluctuation is produced by a single event and not by an accumulation of coherent small deviations. The principle has been rigorously proved for sums of independent and identically distributed random variables and it has recently been extended to more complex stochastic processes involving Lévy distributions, such as Lévy walks and the Lévy–Lorentz gas, using an effective rate approach. We review the general rate formalism and we extend its applicability to continuous time random walks and to the Lorentz gas, both with stretched exponential distributions, further enlarging its applicability. We derive an analytic form for the probability density functions for rare events in the two models, which clarify specific properties of stretched exponentials.
Development of Local Web-Based Learning (LWBL) as Low-Cost Digital Learning Efforts
Authors: Supratman  , Arianto Toni , Maiyana Efmi 
Published: March 2020

Abstract
In a learning practice, we cannot avoidthe use of Information Technology (IT). IT has been able to contribute to the world of education. Learning is more effective, interactive, broad, not time-bound and not patterned only in the classroom. This condition makes IT able to improve the quality of education that can be proud of. The use of IT in the world of education is increasingly being realized its benefits and not only as a complementary medium for educational institutions but has become one of the competitive strategies for institutions in order to improve the quality of its outcomes. In practice, there are some obstacles in the use of IT in learning, namely inadequate infrastructure, inadequate human resources and high operational costs. This research aims to develop a local web-based learning product in an effort to minimize the above constraints. This technology is theoretically able to contribute to students in their learning activities such as increased productivity, flexibility and interactivity without being burdened by the cost of internet access and anxiety in the appearance of content that does not educate when learning takes place. This research uses the 4D version of Research and Development (R&D) approach (Define, Design, Develop, and Disseminate). The results of the study are localhost-based learning websites that can be accessed without the cost of internet access and avoidance of negative content carried by the internet. Based on the test results on the product, it is stated that the products produced can be categorized as valid, effective, and practical to be used in learning.
e-Consult: The Effectiveness of Thesis Advisory Model Using Management Information Systems in IAIN Bukittinggi
Authors: Supriadi  
Published: March 2020

Abstract
This study aims to obtain accurate data about the effectiveness of thesis advisory model using management information systems or e-Consult in IAIN Bukittinggi. This model has been developed in previous research in a series of research and development and has been validated by several experts with the result of very valid category. The effectiveness testing in this study involved 30 students whose thesis are advised by the researcher himself. It was done to facilitate the data selection. They were divided into the experimental group and the control group, each consisting of 15 students. This study was conducted through pre-experimental design with Static Group Comparison model. The data were analyzed by using non-parametric statistics through Binomial test. From this statistic test, the obtained level of effectiveness of this model is in very effective category.
Kahoot:Engage Students Into English Economic Fun Learning
Authors: Syafitri Widya , Pami Putri Hilma , Reflinda  
Published: March 2020

Abstract
Blended learning or E-learning has been famous in this digital age. The teaching and learning process is done through technology as an answer to millennial generation struggle. Several higher educations, which A accreditation, have implemented this learning. IAIN Bukittinggi can’t have fully actualized blended learning because of that reason. Some educators have done semi-blended learning, like in teaching English economic, the educator uses Kahoot in form of quiz to measure students’ achievement of a topic. So this research is aimed at answering research question whether Kahoot App can engage students into English fun learning, how Kahoot is implemented and also to know the benefit and limitation of Kahoot implementation in teaching learning process in IAIN Bukittinggi. This research was held qualitatively. The data were gotten through observation and interview and analyzed descriptively. The findings showed that the English educator had successfully engaged students into English economic fun learning. The students were inspired and motivated to learn English. However, it is expected that institution is going to provide backing media, like LCD and Wi-fi for all classes, in order to support the successful of this gamification program, Kahoot, implementation
Indigenous Bali on Augmented Reality as a Creative Solution in Industrial Revolution 4.0
Authors: Aditama Putu Wirayudi , Setiawan I Nyoman Anom Fajaraditya 
Published: March 2020

Abstract
Packaging creative media in augmented reality technology has become a new media in the face of the industrial revolution 4.0. The rapid development of the latest technology has caused problems for traditional Balinese culture - the phenomenon of colliding traditional culture towards the industrial revolution 4.0, motivating the development of culture-based technology. Bali has a variety of storytelling cultures, one of which is the traditional story of Cupak and Grantang. Story designation based on traditional fairy tale literacy will collaborate with augmented reality technology to add value to local content. The use of technological developments in traditional stories increases opportunities for cultural preservation in the form of creative and commercial media, while at the same time providing design solutions for Balinese native folk media in the field of augmented reality technology with traditional stories so that they can exist in the industrial era based on the industrial revolution 4.0 with native Balinese elements.
Improving the Quality of Management with the Concept of Decision Support Systems in Determining Factors for Choosing a Cafe based on Consumers
Authors: Sari Wisdalia Maya , Fitria F , Suharto Edi , Ikhwani Yusri , Wagino Wagino , Alamsyah Nur , Windarto Agus Perdana 
Published: March 2020

Abstract
The management quality of a cafe really needs to be maintained. This is considering that Cafe is one of the fast-growing and promising businesses. This research was conducted in the city of Pematangsiantar. The development of cafes in Pematangsiantar has not been accompanied by developments in modern technology. This makes customers still feel confused and need information to decide to visit a cafe that is in accordance with their wishes. The purpose of this research is to analyze the Analytical Hierarchy Process (AHP) method in choosing the dominant factor in determining the best cafe factor based on consumers from a number of assessment criteria. Researchers used 8 assessment criteria including: (C1) reliability, (C2) responses, (C3) tangible, (C4) certainty, (C5) security, (C6) ease, (C7) credibility, and (C8) understanding needs. The questionnaire assessment was carried out using 7 alternative cafes among 339, A +, Kok Tong, Coffee Cups, Coffee Time, Eldivo and Indis Cafe. The results of the questionnaire were processed and calculated using the Analytical Hierarchy Process (AHP) method. The results of the study showed that (C1) reliability with vector eigenvalues (0.231) as the first, second and third rank (C6) Ease with vector eigenvalue (0.141) and (C2) responses with vector eigenvalue (0.130). It is hoped that this research can provide input to the owner in creating a decent cafe atmosphere to be a family gathering place..
Sigmoid Activation Function in Selecting the Best Model of Artificial Neural Networks
Authors: Pratiwi Heny , Windarto Agus Perdana , Susliansyah S. , Aria Ririn Restu , Susilowati Susi , Rahayu Luci Kanti , Fitriani Yuni , Merdekawati Agustiena , Rahadjeng Indra Riyana 
Published: March 2020

Abstract
The aim of the research is to make predictions from the best architectural model of backpropagation neural networks. In determining the outcome in the form of a prediction model, the activation function in the artificial neural network is useful to transform an input into a certain output. In this study the activation function used is sigmoid. The study uses the case of population density in Indonesia considering that for developing countries population growth has many negative impacts such as increased poverty, unemployment and crime rates. This study uses data from Badan Pusat Statistic Indonesia for population categories in 2003-2015. The process of determining the architectural model is carried out 2 stages including: the training stage and the testing stage. The two architectural models used (5-2-1 and 5-10-1), the selection of architectural models is done by looking at several assessment parameters such as epoch, accuracy, MSE training and MSE testing. The process of training and testing of data is done by using the help of the Matlab application. The results of the study obtained that the architectural model 5-2-1 is the best model for predicting with an accuracy of 65%, MSE Training 0,0009997254, MSE Testing 0.0014897214 and Epoch 28548.
Usability Testing for Android Radio Streaming Apps of Songgolangit FM
Authors: Asy’ari Nur Aini Shofiya , Muriyatmoko Dihin 
Published: March 2020

Abstract
Songgolangit FM Radio (SFMR) is one of Ponorogo pride information and solutions. Based on previous research, a few months ago, SFMR has an Android Streaming Apps launched on July 29, 2019, in the Google Play store (https://play.google.com/store/apps/details?id=com.amoled.radiosonggolangit&hl=en) As a newly launched application, usability testing needs to measure how easy to use its user interface. The research aims to measure ease of use using usability testing of SFMR based on five-factor: learnability, efficiency, memorability, error, and satisfaction. The usability testing used a questionnaire by nine people from five division in SFMR. The usability testing gets an average total score with a value of 88% by Likert scale. The error factor receives the lowest rating due to incomplete information about the SFMR. From all overall calculation can be concluded that it can be accepted and appropriately used by the SFMR management. In the next research, it can improve the error factor based on respondents’ comments.
New Method Based Pre-Processing to Tackle Missing and High Dimensional Data of CRISP-DM Approach
Authors: Suntoro Joko , Ilham Ahmad , Rani Handini Arga Damar 
Published: March 2020

Abstract
The kidneys are one of the most important organs including the excretion system in humans. The kidneys are responsible for maintaining blood concentrations to remain constant (homeostatic) and help to control blood pressure (BP). If the task of the kidney is not functioning properly it will cause kidney failure. In the past decade, data mining methods have been used to diagnose kidney failure. The dataset used to predict kidney failure was successfully summarized by Soundarapandian, and was named the Chronic Kidney Disease (CKD) dataset. But the data in the CKD dataset contains missing value and high dimension data (original data) so that it affects the evaluation results on classification. This research proposes methods in preprocessing data, namely modus in every class (MEC) method to solve missing value problems, and the weight information gain (WIG) method for solving high dimensional data problems, the proposed method is named the MEC + WIG method. The MEC + WIG method will be compared with the original method and the MEC method and evaluated based on the accuracy of the traditional classification method (k-NN, Naïve Bayes, C4.5, and CART). The results showed that the average accuracy of the MEC + WIG method was better than the original method and the MEC method, with the average accuracy of the MEC + WIG method at 98.13%, while the average value of the accuracy of the original method and MEC respectively amounting to 88.56% and 92.88%. There were significant differences between the three methods when tested using Friedman test with a p-value of 0.02. It can be concluded that the MEC + WIG method can improve the performance of traditional methods k-NN, Naive Bayes, C4.5 and CART by overcoming the problem of missing value and data high dimension.
Classification of Apples based Leaf Using K-Nearest Neighbors and Moment Invariant Extraction
Authors: Huda Walidini Syaihul , Rosadi Muhammad Imron , Khambali  , Radian Muhammad Syah , Hudaa Syihaabul 
Published: March 2020

Abstract
Apples are one of several fruits that are widely favored and cultivated in various regions, in Indonesia many regions cultivate them and serve as the main source of livelihood. From the many types of apples that thrive, it is not difficult for the owner to recognize one type of apple that they planting, because everything looks the same. In previous studies a classification of apple plants using themethod K-Nearest Neighbor (K-NN) with RGB extraction on a dataset of 50 data and in this study an accuracy rate of 93.33% in terms of homogeneity features, texture features was 73, 33% and reaches 100% in terms of Red, Green, Blue (RGB) features. In another study, researchers used the method K-Nearest Neighbor (K-NN) with extraction using histrogram, producing 90% accuracy with 90 data training and 10 data testing using apples as research objects. In contrast to some previous studies, in this study will be carried out on the object image of an apple leaf with a dataset of 750 images. In this study, the author will examine the method K-Nearest Neighbor for the classification of apples based onleaf with the extraction feature moment invariant. The results of this study showed an accuracy of 74.93% for the classification of apple based on leaf which was carried out using the K-NN method with moment invariant for feature extraction method
Implementing of Data Warehouse Data Alumni using the Single Dimensional Data Store method
Authors: Asroni Titis , Arimbi Bimbi , Riyadi Slamet 
Published: March 2020

AbstractData is Information that has not been processed or manipulated, which is not enough for some users. So that the info is useful, the data needs to be prepared and integrated first to become Information. Universitas Muhammadiyah Yogyakarta has a tool to monitor data on Alumni, namely Tracer Study. The data currently available is still not integrated and processed correctly. Now there is a solution for processing data and data by making base data. The purpose of creating this database is to facilitate users in checking data, data that will be stored neatly and integrated into the computer. The method in this study uses the Single DDS method. Methodology This research starts from determining the subject of investigation, primary needs, creating baseline data, analyzing results. The backstage of need is carried out with two data analyzes, and interviews with LPKA (Lembaga Pengelola Kemahasiswaan dan Alumni) or Students and Alumni Management Institutions. Baseline data making in this study is single DDS, which has two data stores, namely Stage and DDS. Data analysis is done by creating reports with Microsoft Office Excel according to user needs. The testing phase is carried out with two processes, namely: ETL Testing and Functional Testing.
Effective Marketing Strategy Determination Based on Customers Clustering Using Machine Learning Technique
Authors: Andi Purnomo Muhammad Ridwan , Azzam Abdullah , Uswatun Khasanah Annisa 
Published: March 2020

Abstract
Marketing is one of the high cost activities in product sales. Therefore, effective marketing is a must in a company and it should be able to encourage customers to purchase more products. One of the efforts to determine effective marketing strategies is clustering the customers and formulating correct actions for every customer cluster. Today, most of companies have digital data including customer transaction data. Techniques to analyse digital data to discover knowledge behind the data is also developed from time to time. One of the techniques in digital data analysis that receives major attention from researchers is machine learning; a technique to enable computer to do learning in analysing the data. This study presents the process of customer clustering to determine effective marketing strategy using a machine learning technique. Customers would be analysed based on 3 parameters, which are last date of coming (recency/R), purchase frequency (frequency/F) and total money spent for product purchased (monetary/M). Such method is known as RFM method. Result of this study shows that the proposed machine learning could be used to cluster the customers and the customer clusters could be used as the basis for marketing manager to determine suitable marketing strategy for every customer clusters.
E-Learning as Connector among Education Institution in the 4th Industrial Revolution
Authors: Yuhasriati  , Jasmaniah  , Azhari Budi , Ma’awiyah Aisyah , Zulkifli  , Syabuddin  , Hamid Marwan , Hamidansyah  , Ridhwan Muhammad , Hambali  , Ilyas  , Bahri Samsul 
Published: March 2020

Abstract
This paper presents the possibility of e-learning as connector among education institutions in the fourth industrial revolution. Since industry started emerging in this world, the industrial journey has reached level four that is currently well known as the fourth industrial revolution. Each stage of revolution has its own impact on education. The fourth industrial revolution requires educational sector synchronize the educational process in order for students or graduates to smoothly interact to the revolutionized changes. E-learning is one among educational entities that is relevant to the fourth industrial revolution in the area of education. With the connectedness as the main characteristic of the fourth industrial revolution, it gives a wide range of opportunities among education institutions particularly for higher education institutions to work, collaborate, and help each other within the platform of e-learning. Besides that, e-learning also enable the developed higher education to help primary and secondary schools at low cost and energy, particularly for professional development of teacher.
Exploring Personality, Grit and Organizational Citizenship Behavior at Higher Education : The Mediating Roles Of Job Involvement
Authors: Puteri Hesi Eka , Arifin M. 
Published: March 2020

Abstract
This study investigates whether personality and grit affect the Organizational Citizenship Behavior (OCB) and if so, whether this relationship is mediated by job involvement or not. This study was a survey at the Industrial Vocational Higher Education of the Ministry of Industry in Indonesia in 2018, with a sample of 217 of lecturers. Data collected by using the questionnaire and analyzed by PLS Model with single-mediator. This research reveals that personality and grit have a positive direct effect on the organizational citizenship behavior. The influence of personality on organizational citizenship behavior is partially mediated by job involvement, but job involvement does not mediate the influence of grit on organizational citizenship behavior. Theoritically, the study extends the current theory by exploring grit as an important predictor that influences organizational citizenship behavior and this relationship is not mediated by job involvement.
Cooperative Learning Approach Applying Jigsaw Strategy to Enhance Students’ Comprehension Skill
Authors: Baneng Mariyae 
Published: March 2020

Abstract
Reading is an important skill in learning new languages as it is a receptive skill in the language competence despite of listening. Reading process requires learners to decode the symbols, interpreting the meaning and applying the ideas derives from the symbols (Herber 1978). However, to understand the reading material seems to be the main obstacle among language learners including Thai students. To help students increase their comprehension, the cooperative learning approach is an effective approach to deal with reading comprehension crisis as it contains the element of collaborative working required for 21st century learners. Jigsaw reading is presented here as the strategy to increase students’ comprehension in while reading stage. It is an activity designed for reading class based on cooperative learning elements.
Design of Baby Box for Early Detection Based on Microcontroller
Authors: Prasojo Ipin , Megantoro Prisma , Raharja Nia Maharani 
Published: March 2020

Abstract
In general, baby nurses in the hospital, if the baby cries and bedwetting can not immediately find out because there is no completeness or tool to inform / monitor the baby’s condition by using several indicators. Therefore, this article discusses the design of automatic baby box device. In the planning and making of paper modules, the writer has problem boundaries, namely planning and making baby boxes equipped with bedwetting sensor, crying sensor accompanied by musical rhythm