Reviewerly/exHarmony huggingface dataset:
STUDI KOMPARASI METODE IQRO� DAN METODE SEPULUH JAM BELAJAR MEMBACA ALQURAN DALAM PEMBELAJARAN BACA TULIS ALQURAN

Reading the Qur'an properly is an obligation for a Muslim. Therefore, every Muslim needs guidance in reading the Qur'an from an early age. However, reality shows that not a few adults are not able to read the Qur'an in accordance with the rules of recitation. In an effort to improve the ability to read and write al-Qur'an, the Institute for Islamic Studies and Practicing has used several methods, namely the Iqro method and the ten-hour of reading Qur�an learning method. This study aims to: first, determine the effectiveness of the Iqro and the ten-hour of reading Qur�an learning method on the reading and writing Qur�an ability of Faculty of Engineering students. Second, the difference in the influence of the two methods on the reading and writing Qur�an ability of Faculty of Engineering students. This study uses a quantitative approach with a different test technique using the Mann-Whitney test because the normality test shows abnormal data. The results showed that H1 was accepted, namely the Iqro method and the ten-hour reading Qur�an learning method significantly in improving the literacy skills of Faculty of Engineering students Muhammadiyah University, Yogyakarta. A comparison test between the two methods also shows that H1 is accepted, which is the ten-hour reading Qur�an learning method more significantly in improving the ability of reading and writing the Qur'an.�Keywords: Iqro� method, Ten-hour of reading Qur�an learning method, reading and writing Qur�an learning
HUBUNGAN ANTARA PENGUASAAN KOSAKATA (WORTSCHATZ) DENGAN KEMAMPUAN MEMBACA MEMAHAMI (LESEVERSTEHEN) TEKS BAHASA JERMAN SISWA KELAS XI

Abstract. This study aims to obtain data and information about the relationship between vocabulary mastery and reading comprehension skills of students in class XI SMA Negeri 1 Palopo. This research is descriptive. The population of this study was all students of class XI, totaling six classes with a total of 208 students. The sample of this research is class XI IPA 3, amounting to 25 students selected through a random sampling technique. The research data were collected through a written test and analyzed using the Product Moment correlation. The result of rcount = (0.411)&gt; rtable = (0.396). The results of the data analysis show that there is a significant relationship between vocabulary mastery and reading comprehension skills of students in class XI SMA Negeri 1 Palopo.
Effectiveness of i-SMART Learning Model Using Chemistry Problems Solving in Senior High School to Improve Metacognitive Skills and Students’ Conceptual Understanding

This study presents i-SMART learning model (Identifying and representing problems, Selecting strategies and plans, Making solutions with monitoring strategies used, Analyzing and evaluating, Reflecting, and Transferring). I-SMART effectiveness in improving students‘ metacognitive skills and conceptual understanding is analysed. The application of i-SMART learning model in metacognitive activities made concepts easier for students to learn, therefore made it positively responded by students.
Scalable Asymmetric Security Mechanism for Internet of Things

The Internet of things stances rigorous demands on excellence of quality and the vitality of security.It becomes vital to provide an extremely reliable encryption algorithm with less complexity and computational expense in IoT paradigm.Most of the protocols designed in past for communication between sender and the receiver based on asymmetric cryptography algorithms poses high computational cost.Therefore, this paper presents a less complex and more secure and fast encryption algorithm for communication between devices i.e.Asymmetric Scalable Security between sender and the receiver of the information.We present a reliable, secure, scalable and efficient communication protocol that used asymmetric algorithm for securing the exchange of information between sender and the receiver.The proposed communication protocol is lightweight encryption method that does not require complex resources to perform the computations involved for using the asymmetric cryptography.The simulation results also show that the proposed method is efficient in terms of time and space and ensures confidentiality.Therefore, the proposed scheme is beneficial for providing the secure communication for the power and resource constrained IoT devices.
Prudently Secure Information Theoretic LSB Steganography for Digital Grayscale Images

The endangerment of online data breaches calls for exploring new and enhancing existing sneaky ways of clandestine communication to tailor those to match the present and futuristic technological and environmental needs, to which malicious intruders wouldn't have an answer.Cryptography and Steganography are the two distinct techniques that, for long, have remained priority choices for hiding vital information from the unauthorized.But the visibility of the encrypted contents makes these vulnerable to attack.Also, the recent legislative protection agreed to law enforcement authorities in Australia to sneak into pre-shared cryptographic secret keys (PSKs) shall have a devastating impact on the privacy of the people.Hence, the need of the hour is to veil in the encrypted data underneath the cover of Steganography, whose sole intent is to hide the very existence of information.This research endeavor enhances one of the most famous images Steganography technique called the Least Significant Bit (LSB) Steganography, from the security and information-theoretic standpoint by taking a known-cover and known-message attack scenario.The explicit proclamation of this research endeavor is that the security of LSB Steganography lies in inducing uncertainty at the time of bit embedding process.The test results rendered by the proposed methodology confers on the non-detectability and imperceptibility of the confidential information along with its strong resistance against LSB Steganalysis techniques.
ALTERNATIVE MODELS OF UNIVERSITIES OF THE FUTURE: ON THE BOOK «ALTERNATIVE UNIVERSITIES: SPECULATIVE DESIGN FOR INNOVATION IN HIGHER EDUCATION» BY DAVID J. STALEY (BALTIMORE, USA: JOHNS HOPKINS UNIVERSITY PRESS, 2019)

David Staley, Director of the Humanities Institute at OhioStateUniversity, historian and futurologist, summarizes his ideas about the possible paths to the development of higher education. He invites everyone interested to immerse into alternative worlds of the future, where education transforms in quite a radical way after the universities having acquired new models, whose prototypes we can find in today’s reality. Using his historical imagination, redirected from the past to the future, Staley describes 1) Platform University, an analogue of a supermarket; 2) a system of Microcolleges based on the authority of central professors; 3) the Humanities Think Tank, giving a new role to the social sciences and humanities; 4) Nomad University, located everywhere and nowhere at the same time; 5) the Liberal Arts College, radically developing the ideas of liberal arts; 6) Interface University, built on the interaction of human and artificial intelligence; 7) the University of the Body, aiming to promote information processing by all human senses; 8) the Institute for Advanced Play, which relies on games, imagination, and the construction of alternative worlds; 9) Polymath University, which implies mastering three different specialties at a time and forms different types of thinking; 10) Future University, teaching both pure and applied futurology. The book was published in 2019 and accumulated all the advanced ideas in the sphere of higher education development paths, which makes it extremely relevant in the era of active reforms in this field.
Design Interval Type-2 Fuzzy Like (PID) Controller for Trajectory Tracking of Mobile Robot

One of the major problems in the field of mobile robots is the trajectory tracking problem. There are a big number of investigations for different control strategies that have been used to control the motion of the mobile robot when the nonlinear kinematic model of mobile robots was considered. The trajectory tracking control of autonomous wheeled mobile robot in a changing unstructured environment needs to take into account different types of uncertainties. Type-1 fuzzy logic sets present limitations in handling those uncertainties while type-2 fuzzy logic sets can manage these uncertainties to give a superior performance. This paper focuses on the design of interval type-2 fuzzy like proportional-integral-derivative (PID) controller for the kinematic model of mobile robot. The firefly optimization algorithm has been used to find the best values of controller’s parameters. The aim of this controller is trying to force the mobile robot tracking a pre-defined continuous path with minimum tracking error. The Matlab simulation results demonstrate the good performance and robustness of this controller. These were confirmed by the obtained values of the position tracking errors and a very smooth velocity, especially with regards to the presence of external disturbance or change in the initial position of mobile robot. Finally, in comparison with other proposed controllers, the results of nonlinear IT2FLC PID controller outperform the nonlinear PID neural controller in minimizing the MSE for all control variables and in the robustness measure.
Improving Software Defect Prediction using Generative Adversarial Networks

This paper discusses Generative Adversarial networks, one of the latest techniques to solve the problem of data imbalance for software defect prediction tasks.When the data available is not enough in a task to frame a machine learning model, it is difficult to construct an accurate model.Generally Software engineering activities like defect prediction, effort estimation etc., were done on data available from open source datasets which had less data.The software defect prediction data available are not only smaller in size, but also imbalanced in nature with very less data found in the defective class.In order to overcome this data imbalance, artificial data generation techniques have been employed.In this work we try to improve the software defect prediction performance in projects, where the data available is less and imbalanced, using Generative Adversarial Networks (GANs).
INTERACTING WITH 3D MODELS – 3D-CAD VS. HOLOGRAPHIC MODELS

Abstract. A problem with 3D models is that devices used to display them are typically two-dimensional, i.e., computer monitors or printed maps. User interfaces of computer software are based on mouse, touchscreen, keyboards, etc. and are optimized for this dimensionality. However, this causes problems when working with 3D models and the user must adapt her actions by interpreting the missing third dimension. While this might not necessarily pose a problem for frequent users, infrequent users may find this quite challenging. Holographic models, on the other hand, float in front of the user, providing a 3D perspective. Interaction with this kind of models may thus be more intuitive than traditional interaction. In the paper we present the results from a first user test. 15 participants tested interaction with a holographic model visualized using Augmented Reality (AR) technology. The results were compared to those of 15 participants using a traditional 3D-CAD. It was found that the holographic approach is more intuitive leading to a lower frustration level although it is still restricted by technical limitations.
Cryptocurrencies Accounting under International Standards

The use of cryptocurrencies is actively spreading in a lot of countries around the world on the basis of economic and technological progressive development.Cryptocurrency attracts investors to launch the initial coin offering (ISO).Cryptocurrency has important features: it is not controlled by the state, does not require the participation of a third party in the calculations.Cryptocurrency transactions are confidential.However, the lack of legal regulation and a unified approach to determining the economic essence of cryptocurrency makes it difficult to reflect in the accounting.Purpose.The purpose of the article is to deepen of the theoretical foundations and formulating of the proposals for the cryptocurrency presentation in the accounting according to International Financial Reporting Standards.Results.The results of the study showed that cryptocurrencies are considered as a type of digital currency that uses cryptography to ensure security and protection against counterfeiting.Cryptocurrency transactions are spreading rapidly around the world.The number of cryptocurrency users is growing rapidly.National and regional authorities around the world are trying to establish certain legal norms and determine its economic essence for further monitoring and taxation.Regulators use different terms to denote cryptocurrencies in regulatory statements and publications.For example, virtual currency, digital currency, digital asset, e-currency, virtual asset and others.The approaches of different countries to the regulation and taxation of cryptocurrency transactions have been analyzed and it has been found that governments and regulators of a significant number of countries respond positively to the emergence and use of cryptocurrency.However, there is no single definition of the economic essence of cryptocurrency.The identification of the cryptocurrency was performed on the IFRS Conceptual Framework basis.It was found 1
Implementasi Algoritma K-Medoids untuk Pengelompokkan Sebaran Mahasiswa Baru

The existence of new students at a tertiary institution is a routine activity every year in a tertiary institution and can also see the sustainability of the tertiary institution. The variety of regional origin of new students makes the party from the university want to see the distribution of new students based on the origin of the school and its place of residence. STIKOM Tunas Bangsa is one of the tertiary institutions in Pematangsiantar. It aims to promote the university. K-Medoids is able to group data on the distribution of new students in STIKOM Tunas Bangsa Pematangsiantar. The clusters produced in this study are of three clusters. The validity used in this study is the validity of Silhoutte Coefficient. The validity value generated in the K-Medoids algorithm produces a validity value of -116.47 by assuming that if the non-medoids value produced S
On Distributed SPARQL Query Processing Using Triangles of RDF Triples

Knowledge Graphs are providing valuable functionalities, such as data integration and reasoning, to an increasing number of applications in all kinds of companies. These applications partly depend on the efficiency of a Knowledge Graph management system which is often based on the RDF data model and queried with SPARQL. In this context, query performance is preponderant and relies on an optimizer that usually makes an intensive usage of a large set of indexes. Generally, these indexes correspond to different re-orderings of the subject, predicate and object of a triple pattern. In this work, we present a novel approach that considers indexes formed by a frequently encountered basic graph pattern: triangle of triples. We propose dedicated data structures to store these triangles, provide distributed algorithms to discover and materialize them, including inferred triangles, and detail query optimization techniques, including a data partitioning approach for bias data. We provide an implementation that runs on top of Apache Spark and experiment on two real-world RDF data sets. This evaluation emphasizes the performance boost (up to 40x on query processing) that one can obtain by using our approach when facing triangles of triples.
Simulasi Monte Carlo dalam Memprediksi Tingkat Pendapatan Advertising

Fulfilling consumer needs is the goal of every business. Owned business capital will affect the readiness to serve consumer demand. The purpose of this study is to predict the level of advertising revenue at Vand Advertising Printing in order to facilitate business owners in preparing business strategies quickly and optimally. This research data is income data from January 2017 to December 2019 which is modeled using the Monte Carlo method. Income level prediction will be carried out annually. Based on the results of the tests that have been done, it is found that the system used to predict the level of advertising revenue with an average accuracy of 90%. The high level of accuracy means that the application of the Monte Carlo method is considered able to predict the level of advertising revenue each year. So that it can make it easier for business owners to choose the right business strategy to increase advertising revenue.
An Analysis of Teacher’s Strategies in Teaching Reading Comprehension

This study was raised due to problems in learning reading. The researchers saw that teachers and students experience constraints in the learning process. The problem is when students do not understand the content of the reading because students only learn to translate word by word and do not understand the contents of the reading. The purpose of research is to know the strategies used by English teachers and the reasons why did the English teacher choose those strategies to teach English reading comprehension and describe the application using the strategies chosen by English teachers in reading understanding learning. This research is used with research objects of English teachers. The location of this research was at SMK Dharma Bakti 1, Medan. The method of the research was qualitative research. The Instruments of this research were observations and interviews. The results of this study using the strategy of Directed Reading Activity (DRA). DRA is a strategy used to expand and strengthen students’ reading skills. In short this strategy guides students to get information from a text read. So that in its implementation students can more easily understand the text of connecting the various student knowledge that students have. Before it was to build its own understanding and this assumption, this strategy was considered effective because it was able to build a teaching learning process. Making classes more conducive, students are also trained to build good cooperation, students capable of discussion and critical thinking as well as developing understanding after reading.
Using Reader’s Theatre Strategy in Learning English Poetry: How Effective it Could be?

The purpose of this study was to investigate whether using Reader’s Theatre starategy could improve students’ comprehension level or not and exore students’ perception about the imlementation of Reader’s Theatre in learning English poetry. A total of eight participants from the same program in Kolej University Islam Perlis (KUIPs), Perlis were involved in the research. This study used Embedded Mixed Method in which preexperimental research was conducted in the quantitative stage of data collection, where the quantitative data were gained from students’ pre-test and posttest. Meanwhile the qulitative data were gained from the interview conducted at the end of experimental study. The data collected from the results of students’ pretest and posttest were analyzed by using paired samle T-Test, while thematic analysis was used to analyse the responses from interviews. The results of the analysis showed that 1) Reader’s Theatre strategy was able to enhance students’ comprehension level and 2) students showed positive perception that the learning activities with the implementation of Reader’s Theatre strategy brought three benefits; first, the activity was interesting and enjoyable, secondly, the activity made it easy to comprehend English literatures and thirdly, the activity made students work collaborativey in groups.
Blur - Map Estimation and Deblurring of Degraded Image by Non - Convex Regularization Approach

We in this work proposed a new algorithm for blur-map estimation of space variant degraded image using a graduated non convex discontinuity adaptive Markov random field (DAMRF) frame work.First we estimated to find the blur-map and then restore the blurred image in.We use a GNC optimization based framework, wherein we assume the latent image and blur map as DAMRF prior.We show that the estimated blur-map is utilized for image restoration application such as image in-painting, depth estimation, image denoising, super resolution, haze removal etc. Robust estimation of the non-uniform blur-map of a natural scene is obtained produces better qualitative and quantitative results compared to the few state-of-the method
Multischeme feedforward artificial neural network architecture for DDoS attack detection

Distributed denial of service attack classified as a structured attack to deplete server, sourced from various bot computers to form a massive data flow. Distributed denial of service (DDoS) data flows behave as regular data packet flows, so it is challenging to distinguish between the two. Data packet classification to detect DDoS attacks is one solution to prevent DDoS attacks and to maintain server resources maintained. The machine learning method especially artificial neural network (ANN), is one of the effective ways to detect the flow of data packets in a computer network. Based on the research that has carried out, it concluded that ANN with hidden layer architecture that contains neuron twice as neuron on the input layer (2n) produces a stable detection accuracy value on Quasi-Newton, Scaled-Conjugate and Resilient-Propagation training functions. Based on the studies conducted, it concluded that ANN Architecture sufficiently affected the Scaled-Conjugate and Resilient-Propagation training functions, otherwise the Quasi-Newton training function. The best detection accuracy achieved from the experiment is 99.60%, 1.000 recall, 0.988 precision, and 0.993 f-measure using the Quasi-Newton training function with 6-(12)-2 neural network architecture.
Leadership Via 5 Factor Model and Roles of Cyber Security, IT Risk Management – A Case of Alphabet , Google in the US

Today, businesses want to grow, they must build their own "ecosystem", not only multi-industry but also diverse in terms of people, views, cultural characteristic Also, they need to pay attention to IT system and IT risk management program.After restructuring, Google manages Google Search, Maps, YouTube, Android and advertising.Meanwhile, other businesses such as Nest, Fiber, Google Capital, Google X are separated as subsidiaries under Alphabet's management. Google technologies that use cloud computing (including Gmail, Google Calendar, Google Docs, Google App Engine, Google Cloud Storage among others) and The development of Google News and Gmail are two examples of successful projects that emerged from 20% time. Multitasking but not hugging, it is the pinnacle of organizational management science when the division of labor is almost perfect at Google. Movement of net profit in giant firms such as Alphabet & Google will reflect the business health of technology system and the whole economy. Good business management requires us to consider the impacts of multi macro factors on net profit, and it contributes to promoting business plan and economic policies for economic growth and stabilizing macroeconomic factors. The results of quantitative research, in a seven factor model, show that the increase in inflation,GDP (increasing too much) and reducing cost has a significant effect on reducing Google net profit with the highest impact coefficient, the second is decreasing the net sale.This research finding and recommended policy also can be used as reference in policy for industrial technology system in many developing countries.