Reviewerly/exHarmony huggingface dataset:
PEMBELAJARAN MATEMATIKA PADA LMS CHAMILO UNTUK MENINGKATKAN KEMANDIRIAN BELAJAR SISWA

This research aims to develop content of learning management system (LMS) chamilo based smartphone and computer as a media for learning mathematics and to know effectivity of learning management system (LMS) development in enhances self regulated learning of the students. This research is a research and development (R&D) with ADDIE development models. The steps that have been taken in this research are analysising of school’s condition and finding the potential and problems of learning media, designing learning media in appropiate to the result of analysis, developing the result of design that have been made, implementation of learning media to the masters, they are master of learning media and master of mathematics education, and evaluation of learning media that be feasible according to the masters to students. To see the feasibility of learning media, its did validation first product of learning media. In the implementation step, its did validation that had been made, and there is quality level of learning media based on assessment of learning media : 1) Master of Learning Media obtained a percentage of 84% with a very good category, 2) Master of Mathematics Education obtained a percentage of 91 % with a very good category. Effectivity of learning media based on evaluation of learning media by the students, the result are Student’s responses of learning media obtained a percentage of 8 0 , 03 % with a very good category . Beside it, too see self regulated learning of the students has increase from 54,26%to 72,56%. Therefore, learning media that proved is effective used in learning mathematics to enhance self regulated learning of the students. Keywords :  Self Regulated, LMS Chamil o.
PELAYANAN DOKUMEN KAPAL TB. PRIMA 1201 OLEH PERUSAHAAN PT. TERA LOGISTIC BATANG

PT. Tera Logistic Indonesia Batang branched is a shipping company engaged in ship agency and unload cargo of Fertilizer. PT. Tera Logistic Indonesia Batang branch responsible for providing operational services .This paper uses qualitative research methods that are ready to get the results of data through direct sources with instruments from the researchers themselves. Interview Analysis, Observation, Document and Library Studies. From this method can help the writing of this paper with lancer and good.The result of this paper is an agent role in serving the arrival and departure of vessels owned by PT. Tera Logistic Indonesia Batang branch is less than the maximum in preparation of the required documents. This is due to the filing of documents by the company is not placed by the place, causing the possibility of the name of the document tucked. The anticipation of the company is to re-check the documents to be prepared in. Keyword : Service Document, Clearance In and Out
Sticky Existential Rules and Disjunction are Incompatible

Stickiness is one of the well-known properties in the literature that guarantees decidability of query answering under sets of existential rules, that is, Datalog rules extended with existential quantification in rule heads. In this note, we investigate whether this remains true in the case when rule heads are allowed to be disjunctive. We answer this question in the negative, providing a strong undecidability result that shows that the concept of stickiness cannot be extended to disjunctive existential rules, even when considering only fixed atomic queries and a fixed set of rules. This provides evidence that, in order to keep query answering decidable, a stronger property than stickiness is needed in the disjunctive case.
Students’ Knowledge of the Readiness to Use E-Learning

E-learning has become a new norm in the world of education nowadays.Rapid development in educational technology leads to the improvement and simplification of traditional teaching and learning methods.Furthermore, today's learners want relevant, mobile, and self-paced content.This need is fulfilled with the online learning platform, allowing students to learn at their comfort and pace.E-learning helps teachers in preparing, distributing, and evaluating the assignments given to students.Teachers and lecturers have now become the facilitator to their students in the learning process.This study was conducted to identify the level of knowledge on the readiness to adopt e-learning among form six students in the science stream at a form six college in Selangor.This study follows the quantitative research approach, and a questionnaire was used as the instrument to collect the data.31 respondents were involved in this research.The findings show that the level of knowledge of the readiness to use e-learning among science students in Tunku Abdul Rahman Putra Form Six College (KiSTARP) is high, with the mean score at 3.82.Elearning makes it easier for teachers to give students assignments, thus enabling teachers to monitor students' presence and readiness to learn.This limitless technology allows the teaching and learning process to occur at any time and improves the two-way communication between teachers and students.It also helps create meaningful learning experiences, which will benefit both teachers and students.
Penerapan Data Mining Untuk Clustering Data Penduduk Miskin Menggunakan Metode K-Means

Poverty that occurs in the community is a major problem that must be an important concern for the government in any country in various provincial, district and city governments, such as providing assistance to the poor in the form of allowances that can relieve the community and help the community, Community Health Insurance, Rice for the Poor (Raskin), Education Cost Assistance for Academic Achievement Improvement (BBP-PPA) Tuition Fee Assistance which is only intended for prospective students who are unable or poor (BIDIKMISI), and other programs that can help the poor, but in reality the problem of poverty cannot be overcome. Suka Bhakti Village carried out grouping of poor and non-poor communities based on basic determinant variables, namely the latest education of members or family heads, ownership of several family assets, total family income from both the head of the family and a combination of family members, the area of the building owned, the type of floor used, and the type of wall. The use of data mining with cluster techniques through the K-Means method can group community data to get clusters that should be able to receive social assistance from the government. The results of the validity calculations carried out, the results obtained for the number of cluster 1 are 130 data and for cluster 2 are 682. Testing this data is carried out using the Davies-Bouldin Index (DBI) method. The resulting number of suitable clusters is 2 clusters with a value of 0, 1643 which means that the cluster is suitable for grouping community data.
A shot in the dark: Australia's proposed encryption laws and the 'disruption calculus'

In December 2018, in response to several foiled terrorist attacks, Australia passed some of the most intrusive telecommunications interception legislation in Australian legal history. Yet the response of the Australian Government is not a cohesive strategy designed to deal with the disruption caused by the emergence and abundance of encrypted messaging. This article deals with the legislative amendments encapsulated in the Telecommunications and Other Legislation Amendment (Assistance and Access) Bill 2018 (Cth) ('the Bill'), and addresses the issues of scope and scale which remain unresolved in spite of these changes. It then reflects upon a new concept - the 'disruption calculus' - to illustrate that the new amendments are unlikely to achieve the regulatory aims sought by intelligence and police forces in Australia. Finally, the article uses Israel's model of encryption regulation to illustrate that a more varied and holistic approach in line with the disruption calculus can provide an effective alternative for regulatory authorities in Australia
Review of Energy Efficiency in Security of 5G Internet of Things (IoT) Applications

5G will be quickly become the new standard for cellular networks. The Internet of Things (IoT) is rapidly developing and expanding. 5G will increase cellular bandwidth by huge amounts, making it much easier for the Internet of Things to network large numbers of devices together. 5G will be 10 times faster than current LTE networks. This increase in speed will allow IoT devices to communicate and share data faster than ever. The security is a major concern of digital communication, as the technology enhances the security concern is also enhancing to meet the requirement of the 5G-IOT communication. This paper includes the energy efficiency of the nodes in security for 5G-IOT applications.
THE CHANGE IN THE METHODS OF SMISHING IN SOUTH-KOREA AFTER THE ONSET OF COVID-19

This study aims to figure out the change in the techniques of smishing in South Korea after the onset of COVID-19 by identifying smishing modus operandi. Smishing is a serious SMS fraud in which criminals achieve profits by deceiving victims through SMS. Even though the damage of smishing is increasing each day after the onset of COVID-19, there are few papers on the change in the smishing methods after COVID-19. To fill this gap, the researchers collected smishing cases online and employed content analysis and crime script analysis to figure out the modus operandi of smishing in detail. The researchers classified the types of smishing after the start of COVID-19 by utilizing content analysis and identified the progress of smishing through crime script analysis. The findings demonstrated that the modus operandi of smishing in South Korea after COVID-19 consists of pre-preparation, preparation of smishing attack, sending of smishing message, downloading of malicious application onto victims’ smartphone & theft of victims’ information and storing it, attempt at financial gain through utilization of attained victims’ information, charging of transaction/payments to the victims.
Deep Learning Network Model Studies for Adversarial Attack Resistance

In the last decades, deep learning neural networks have taken several steps toward higher pattern recognition accuracies. Face recognition is one of the popular topics that have drawn much attention and it is now frequently used in everyday lives. However, the recognition performance suffers easily by irregularities and disturbances. The focus of this work is to explore the security performance of deep learning neural networks by using an adversarial attack approach. The ResNets is the framework of the proposed system and its recognition behaviors under the adversarial attacks are investigated. The experiments are performed by using MNIST and CIFAR-10 datasets and the detection and recognition errors are evaluated. The results show that the proposed systems can be an alternative that can resist perturbations better than the conventional models.
RANCANGAN SISTEM INFORMASI PENJUALAN BERBASIS WEBSITE (STUDI KASUS: RUMAH MAKAN BARESOLOK)

Baresolok Restaurant is a simple restaurant engaged in the culinary field that sells Padang specialties, various drinks, and other dishes. Baresolok Restaurant is famous for its distinctive dishes, so it's no wonder Baresolok Restaurant has many loyal customers. However, sales administration activities are still done manually. This results in frequent data discrepancies and consumes a lot of time. Not only that, some problems occur because they still use books and calculators to record transactions, such as price placement errors, calculation errors, and sometimes restaurant employees commit fraud. Based on the existing problems, a web-based sales information system was created for Baresolok Restaurant. This sales information system is built using the PHP programming language and MySQL DBMS (Database Management System) with the help of the Laravel framework. This system was developed using the Prototype method. The final result obtained is a web-based sales information system used by Baresolok Restaurant. This system is able to provide food menu promotions, sales and food orders.
A criança na perspectiva da Biblioteconomia e da Ciência da Informação: a contribuição dosestudos de usuários para odesenvolvimento da competência informacional infantil

portuguesO universo infantil tem sido objeto de estudo por meio de metodologias especificas em varios campos, dentre os quais a Educacao, a Psicologia e o Marketing. Todavia, nota-se uma carencia de estudos na area da Ciencia da Informacao e, consequentemente, na Biblioteconomia. Desta forma, o trabalho ora realizado intenta, por meio de levantamento bibliografico e estudo bibliometrico, demonstrar a necessidade de reflexao sobre as melhores praticas de realizacao de estudos com o publico infantil em unidades de informacao. Os resultados da analise bibliometrica realizada na base de dados BRAPCI destaca a ausencia de trabalhos na area de Ciencia da Informacao sobre a tematica, demonstrando a relevância de novas pesquisas que desenvolvam praticas capazes de descobrir as necessidades informacionais das criancas, favorecendo a criacao de novos produtos e servicos de informacao em bibliotecas infantis e escolares para desenvolver a competencia informacional infantil. EnglishThe children's universe has been the object of study through specific methodologies in several fields, including Education, Psychology and Marketing. However, there is a lack of studies in the area of ​​Information Science and, consequently, in Librarianship. In this way, the work now attempted, by means of bibliographic survey and bibliometric study, to demonstrate the need for reflection on the best practices for conducting studies with children in information units. The results of the bibliometric analysis carried out in the BRAPCI database highlights the absence of work in the area of ​​Information Science on the subject, demonstrating the relevance of new research that develop practices capable of discovering the informational needs of children, favoring the creation of new products and information services in children's and school libraries to develop children's information competence.
Management Information Technology for Depression Strategies during COVID-19 Using by Data Mining Technique

The impact of the COVID-19 pandemic in universities profoundly influences the quality of learners' education. Thus, the research goals were to examine attitudes to the impact of the COVID-19 pandemic in universities and to study the influencing effects on college students’ depression. The scientific novelty was the integration of artificial intelligence technology to manage education in the COVID-19 pandemic proactively. The research sample consisted of 2,624 students from ten faculties and one institution. Basic statistics and data mining techniques are used in the analysis of research. It consists of frequency, mean, percentage, standard deviation, k-Means, k-Determination. The results of the study revealed that the students had a severe attitude towards the COVID-19 epidemic situation. The impact that students are most concerned about is the online learning management process. In addition, the overall opinion of the respondents had a high level of anxiety about learning management. In addition, the data-mining analysis showed that it was consistent with most normal levels of depression, anxiety, and stress among students. In future research, the researcher plans to develop an application program to support organization management with modern technology and to prepare students for the future of learning. Keywords: management information technology, data mining, depression strategies, COVID-19.
Small Computers in the Internet

IT professionals must be forced to determine what their performance requirements are; for example, certain hardware platforms consider virtualization, while others function as stand-alone systems. Furthermore, some apps and operating systems may be incompatible with certain hardware. In recent years, the term has come to be used to describe almost anything that having to do with computers and networks, particularly in the security industry. Another growing topic of study is monitoring Internet conflicts, such as state-on-state cyber warfare, cyber terrorism, cyber militias, and so on.
Multi-Stream Fusion Network for Multi-Distortion Image Super-Resolution

Deblurring, denoising and super-resolution (SR) are important image recovery tasks that are committed to improving image quality. Despite the rapid development of deep learning and vast studies on improving image quality have been proposed, the most existing recovery solutions simply deal with quality degradation caused by a single distortion factor, such as SR focusing on improving spatial resolution. Since very little work has been done to analyze the interaction and characteristics of the deblurring, denoising and SR mixing problems, this paper considers the multi-distortion image recovery problem from a holistic perspective and introduces an end-to-end multi-stream fusion network (MSFN) to restore a multi-distortion image (low-resolution image with noise and blur) into a clear high-resolution (HR) image. Firstly, MSFN adopts multiple reconstruction branches to extract deblurring, denoise and SR features with respect to different degradations. Then, MSFN gradually fuses these multi-stream recovery features in a determined order and obtains an enhanced restoration feature by using two fusion modules. In addition, MSFN uses fusion modules and residual attention modules to facilitate the fusion of different recovery features from the denoising branch and the deblurring branch for the trunk SR branch. Experiments on several benchmarks fully demonstrate the superiority of our MSFN in solving the multi-distortion image recovery problem.
Local Word Discovery for Interactive Transcription

Human expertise and the participation of speech communities are essential factors in the success of technologies for low-resource languages. Accordingly, we propose a new computational task which is tuned to the available knowledge and interests in an Indigenous community, and which supports the construction of high quality texts and lexicons. The task is illustrated for Kunwinjku, a morphologically-complex Australian language. We combine a finite state implementation of a published grammar with a partial lexicon, and apply this to a noisy phone representation of the signal. We locate known lexemes in the signal and use the morphological transducer to build these out into hypothetical, morphologically-complex words for human validation. We show that applying a single iteration of this method results in a relative transcription density gain of 17%. Further, we find that 75% of breath groups in the test set receive at least one correct partial or full-word suggestion.
Optical 3D scanning methods in biological research – selected cases

Shape measurement by optical methods is more and more often used in research both in human and veterinary medicine. As a result of the measurement, a set with marker positions in space or a cloud of points representing a scanned surface is obtained. The collected data contains useful information, but to extract it, it is necessary to process the data using appropriate algorithms. The aim of this study was to present the algorithms that the author used to process data for the purposes of analyzes which results and conclusions were included in four articles published earlier. The algorithms concern the determination and identification of markers on the body when measuring the posture of soccer players and the analysis of the cloud of points for determining the angles describing the base and surface of the hoof bones in the polar coordinate system. The measurement systems in which data were collected are also described. Sample results obtained with the presented analysis methods are shown. For the first case these are given directional views of the markers determined in 3D space, while for the other two the result containing information about the calculated angles in the form of a table and a graph are presented. The presented data processing methods and algorithms are not only applicable to the cases on which they were tested. Directly or after a small modification, they can be applied in another area.
Design of Novel Benchmarking System for Power-Efficient Face Detection Algorithm (PE-FDA) in Artificial Intelligence (AI) based Security System

Recently, there have been active studies of video surveillance using artificial intelligence (AI) and security that operates with face detection algorithms (FDA), such as face identity matching system (FIMS) and pedestrian tracking system (PTS). Benchmarking an optimal FDA is one of the important tasks for designing the AI-based security system. However, this AI-based security system suffers from enormous power consumption due to a high frame rate of multiple cameras. For this reason, the AI-based security system needs to find a power efficient face detection algorithm (PE-FDA). To the best of our knowledge, the conventional FDA benchmarking systems (such as using Iou metric) are not optimized with respect to the power efficiency of FDAs. In this paper, we propose a novel benchmarking system for PE-FDA, including power consumption in AI-based security system. We will define the design of benchmarking system and describe its spatial and temporal challenges. (1) In order to solve the spatial challenges, we propose a novel evaluation score, unitized-distance (UD) metric. (2) In order to improve the temporal challenge, we will introduce frame mapping algorithm. (3) our benchmarking system is designed for PE-FDA in AI-based security system. We validated our benchmarking system of PE-FDA using actual video data obtained from a state-of-the-art security system. Thus, this study of our benchmarking systems can allow FDA to be utilized in AI center monitoring system for the future security system.
The Art of Storytelling in Academic Writing

Academics are extremely fortunate. Our job is to (1) think of questions other people haven’t thought of and identify questions that haven’t been answered, (2) figure out how to answer them, (3) do it, and then (4) tell the story. The bulk of the training we receive in doctoral programs focuses on parts two and three (i.e., research design and analytical techniques), with a reasonable amount of attention given to part one in theory and content seminars; however almost no attention is given to part four—storytelling. Our symposium will address the under-discussed “art” of storytelling that helps make some articles so much more influential than others. In particular we will focus on the structure of storytelling, storytelling techniques, language use, and the writing process. Our panelists are OB, Strategy and Organization theory scholars who are well known for their storytelling styles, and will create a unique and meaningful session on the art of storytelling.
Information System Strategy Planning Using Swot Analysis Method

Business competition in the era of globalization, supported by rapid technological advances, requires companies to facilitate their companies with information technology to facilitate their work. Toko Asshar as a company engaged in the product must be ready to face this challenge. To become a company that excels in competing and surviving in the future, the role of information systems and technology is needed as a support for business strategies. Information system strategic planning needs to be done to help the company achieve its goals. This study was conducted to analyze the company's internal and external business environment. The research method used is a SWOT analysis with a qualitative approach carried out with several stages consisting of literature study, observation and interviews. The results of this study will produce a portfolio of information systems in the form of recommendations for companies by improving existing systems and adding new systems to meet the company's business needs