Reviewerly/exHarmony huggingface dataset:
Pengembangan Aplikasi Kuliah Kerja Nyata Pada IAIN Salatiga Dengan Metode Prototype

During this time the management process of managing Kuliah Kerja Nyata at IAIN Salatiga still uses the conventional way by involving documents manually so it takes a long time. The purpose of this study is to build applications that are useful for handling the process of managing Kuliah Kerja Nyata (KKN) at IAIN Salatiga starting from registering data management, KKN supervisor lecturer management, to reporting the results of KKN. The application development method used in this study is the prototype method and in testing its application using the BlackBox testing method. From the results of the Blackbox, The Testing test shows that the application of a Kuliah Kerja Nyata on the Salatiga IAIN as a whole the functionality can run well.
The Shallow Gibbs Network, Double Backpropagation and Differential Machine learning

We have built a Shallow Gibbs Network model as a Random Gibbs Network Forest to reach the performance of the Multilayer feedforward Neural Network in a few numbers of parameters, and fewer backpropagation iterations. To make it happens, we propose a novel optimization framework for our Bayesian Shallow Network, called the {Double Backpropagation Scheme} (DBS) that can also fit perfectly the data with appropriate learning rate, and which is convergent and universally applicable to any Bayesian neural network problem. The contribution of this model is broad. First, it integrates all the advantages of the Potts Model, which is a very rich random partitions model, that we have also modified to propose its Complete Shrinkage version using agglomerative clustering techniques. The model takes also an advantage of Gibbs Fields for its weights precision matrix structure, mainly through Markov Random Fields, and even has five (5) variants structures at the end: the Full-Gibbs, the Sparse-Gibbs, the Between layer Sparse Gibbs which is the B-Sparse Gibbs in a short, the Compound Symmetry Gibbs (CS-Gibbs in short), and the Sparse Compound Symmetry Gibbs (Sparse-CS-Gibbs) model. The Full-Gibbs is mainly to remind fully-connected models, and the other structures are useful to show how the model can be reduced in terms of complexity with sparsity and parsimony. All those models have been experimented with the Mulan project multivariate regression dataset, and the results arouse interest in those structures, in a sense that different structures help to reach different results in terms of Mean Squared Error (MSE) and Relative Root Mean Squared Error (RRMSE). For the Shallow Gibbs Network model, we have found the perfect learning framework : it is the $(l_1, \boldsymbol{\zeta}, \epsilon_{dbs})-\textbf{DBS}$ configuration, which is a combination of the \emph{Universal Approximation Theorem}, and the DBS optimization, coupled with the (\emph{dist})-Nearest Neighbor-(h)-Taylor Series-Perfect Multivariate Interpolation (\emph{dist}-NN-(h)-TS-PMI) model [which in turn is a combination of the research of the Nearest Neighborhood for a good Train-Test association, the Taylor Approximation Theorem, and finally the Multivariate Interpolation Method]. It indicates that, with an appropriate number $l_1$ of neurons on the hidden layer, an optimal number $\zeta$ of DBS updates, an optimal DBS learnnig rate $\epsilon_{dbs}$, an optimal distance \emph{dist}$_{opt}$ in the research of the nearest neighbor in the training dataset for each test data $x_i^{\mbox{test}}$, an optimal order $h_{opt}$ of the Taylor approximation for the Perfect Multivariate Interpolation (\emph{dist}-NN-(h)-TS-PMI) model once the {\bfseries DBS} has overfitted the training dataset, the train and the test error converge to zero (0).
LEVERAGING THE INTERNET OF THINGS BASED ON THE ANALYTICAL STUDY OF THE SKELETON JOINT POSITION IN RECOGNISING THE QUALITY OF HUMAN ACTIVITY

To give consequently dissecting and identifying human exercises to offer better help in the medical services area, security reason and so on Strategy: We have utilized UTKinect-Action 3D dataset containing the Position of 20 body joint caught by Kinect sensor. We chose two arrangement of joints J1 and J2; after that, we have shaped a few principles for movement grouping then we have applied SVM classifier, KNN classifier utilizing Euclidean distance and KNN classifier using Minkowski distance for action order. At the point when we have been used joint set J1 we got 97.8% exactness with SVM classifier, 98.8% precision with KNN classifier utilizing Euclidean distance, and 98.9% exactness with KNN classifier utilizing Minkowski distance and for joint set J2 we got 97.7% exactness with SVM classifier, 98.6% exactness with KNN classifier using Euclidean distance, and 98.7% exactness with KNN classifier utilizing Minkowski distance. We have arranged four exercises hand waving, standing, sitting and picking. In future, more exercises can likewise be remembered for this examination. IoT alongside this action acknowledgement strategy can be utilized to lessen overheads
Corruption in Africa: The Way Forward

How do I tell a story and contribute to restrict a monster that causes trillions of dollars that could have been used for national development, to be lost to private individual pockets, leaving most of the populace in abject poverty and lack of basic needs?That is the question I ask myself every day as an individual from an African country, Ghana.Corruption has gained global attention and researchers and international organizations have attempted to define and measure it.One of such organizations is the Transparency International (TI).TI is the most widely used corruption indicator and it uses a scale of 0 to 100 to rank countries, where 0 is highly corrupt and 100 is very clean.TI [1] defines corruption as "the abuse of entrusted power for private gain."Macrae [2] uses the term "arrangement" to define corruption.The arrangement involves a private exchange between two parties (the demander and the supplier) which has an immediate or future influence on resource allocation, and the use of public office for private means.The basic assumption of his definition is that, corruption is a rational calculus and often deeply-rooted method by which public officials take decisions in soft-states of Third World countries.Shleifer and Vishny [3] define government corruption as "the sale by government officials of government property for personal gain."Forexample, a military official selling military equipment procured by the government, for his personal gains.This is also manifested in trade, where custom officials working for the government often take bribes from companies at the ports and harbors.Treisman [4] also follows up and defined corruption as "the misuse of public office for private gain."Jain [5] agrees on the definition of corruption as being acts in which the power of public office is being used for personal gains in a way that goes contrary to the rules of the game.He goes further to point out three elements that are required for corruption to thrive in a country: discretionary power, economic rents, and weak judicial system.Aidt [6] views corruption as a persistent feature of human societies over time and seems to be occurring in many societies due to three factors: discretionary power of government agents, economic rents, and weak political and administrative institutions.Svensson [7] also defined corruption as the misuse of public office for private benefits and can be a response to either beneficial or harmful laws.By this definition, the sale of government property by public officials, receiving of kickbacks in public procurement, and bribery and embezzlement of state funds, will all qualify as corruption.He went further to indicate that corruption is an outcome from a reflection of a country's legal, economic, cultural and political systems.Bardhan [8] further defined corruption as the use of public office for private gains.Akçay [9] also defined corruption as the misuse of public office for private benefit.This abuse emerges when a public official has monopoly power over a good or service and uses that power at his/her own discretion to accrue rent for him/
ANALISIS KUALITAS SISTEM APLIKASI DAPODIK PADA KOORDINATOR WILAYAH BIDANG PENDIDIKAN KECAMATAN KUTAWALUYA MENGGUNAKAN MODEL WEBQUAL 4.0

AbstractDapodik application is a web-based data collection application which is one of the main sources in the formulation of government policies. In the Dapodik application, there are some managed data including school data, infrastructure, students, teachers and education personnel. The data or information generated is influenced by the quality of the Dapodik application itself. Therefore this study aims to analyze the quality of the Dapodik application system using the Webqual 4.0 model. This research is quantitative descriptive. From the results of the study showed that the ease of users (usability), the quality of information (information quality) and the quality of service interactions (service interaction) on the Dapodik application has been very well felt by users.Keyword: Dapodik, Webqual, System Quality
Preprocessing Big Data for Efficient Storage and Research

Big Data refers to large datasets and so it is not possible to store, manage and analyze it using commonly used software systems. The emergence of smart phones, social networks and online applications has led to the generation of massive amounts of structured, unstructured and semi structured data. Big data analytics has received sizeable attention since it offers a great opportunity to uncover potentials from heavy amounts of data. Data preprocessing techniques, when applied prior to analytics, can substantially improve the overall quality of the patterns mined and/or the time required for the actual mining. Thus this paper presents an efficient method for preprocessing data and also partitioning big dataset based on sensitivity parameters. The partitioned dataset can be uploaded to public and private cloud based on the importance of data in the partition. Thus hybrid cloud storage and processing of big data is supported by this approach. The experimental results show that the proposed method preprocesses and partition data with high accuracy and reduced processing time.
Unsupervised learning of seismic wavefield features: clustering continuous array seismic data during the 2009 L'Aquila earthquake

Earth and Space Science Open Archive This work has been accepted for publication in Journal of Geophysical Research - Solid Earth. Version of RecordESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary. Learn more about preprints. preprintOpen AccessYou are viewing the latest version by default [v1]Unsupervised learning of seismic wavefield features: clustering continuous array seismic data during the 2009 L'Aquila earthquakeAuthors Peidong Shi iD Léonard Seydoux Piero Poli iDSee all authors Peidong ShiiDCorresponding Author• Submitting AuthorInstitut des Sciences de la Terre (ISTerre), Université Grenoble AlpesiDhttps://orcid.org/0000-0001-5782-245Xview email addressThe email was not providedcopy email addressLéonard SeydouxInstitut des Sciences de la Terreview email addressThe email was not providedcopy email addressPiero PoliiDUniversité Grenoble-Alpes, Isterre LaboratoryiDhttps://orcid.org/0000-0002-6493-5142view email addressThe email was not providedcopy email address
The Effect of Mind Mapping-Aided Scientific Approach and Learning Style on Student’s Reasoning

This study aimed at analyzing: (1) the effect of mind mapping-aided scientific approach on student's reasoning, (2) the effect of learning style on student's reasoning, and (3) the effect of the interaction between mind mapping-aided scientific approach and learning style on student's reasoning.This study used a quasi-experiment non-equivalent posttest only control group design.The data were collected by using reasoning test and the data on learning style by using a standard test.The data were analyzed the two-way ANOVA statistical analysis.Based on the analysis it was found out that 1) there was a significant effect of the mind mapping-aided scientific approach on the student's reasoning (p<0.05).2) there was a significant effect of field independent and field dependent learning styles on the student's reasoning (p<0.05).3) there was no significant effect of the interaction between mind mapping-aided scientific approach and learning style on the student's reasoning (p> 0.05).
Choosing the best Bin Packing Algorithm for Replica Placement in Multi-Tenant Cloud System

Of late, Cloud Computing is visibly seen to reduce infrastructure costs with high data availability and performance conforming to service level agreement for both the service providers and the users. With the rapid and explosive growth of the number of cloud users, Cloud Data Management System must serve an array of different analytical and transactional workloads. Hence, to ensure the scalability in a multi-tenant system, replica placement algorithms always come into the picture appropriately. In our work, we have vividly analyzed various replica placement algorithms in terms of their performance and tried to find the beneficial aspects to be the fittest one to tackle the situation when the actual observed workloads are immensely deviated from the estimated workloads.
Development of High Quality Color Image Compression using Block Transformation

The upcoming era of social media will be highly equipped with the images and the videos. Images or multimedia content sharing and storing services are still costly for common man which is need to be resolved to cover all the users either middle class or high society users. Various online platforms have filled the gaps for freedom of expression for everyone. demand of the multimedia data sharing telecommunication networks has increased. images has changed the requirements for effective transmission and storage media. With the convenience of accessibility of press tools and digital image web exchange, there has been a dramatic increase. Image is the least component of multimedia information and includes a important portion of the velocity of communication for multimedia data Developments in image compression techniques have therefore developed potential requirement. For all pictures, a fundamental concept of image formation is that the pixels are linked and comprise extremely useless data afterwards. The primary objective of this job is to discover in the image reduced associated pixel intensities. In this work an adaptive frequency domain block processing for color image compression has developed and simulated.
Detection of Video and Multimedia Copy-Move Forgery using Optical Algorithm and GLSM Clustering

Digital Videos and multimedia copy-move forgery detection is a trending topic in multimedia forensics. Protecting videos and other digital media from tampering has become a cause of concern. Video copy-move forgery has increasingly become a type of cybercrime that is employed to using videos for various malicious purposes such as providing fake evidences in court rooms, spreading fake rumors, using it to defame a person. A lot of approaches have been proposed for detecting the traces left by any forgery caused due to the copy-move operation. In this paper, we conduct a survey on these existing approaches which are applied for the detection of copy –move videos and also for the identification forgery in the images. In some of the existing methods, the problem of copy-move video forgery has been addressed using different techniques. Techniques such as noise residue, motion and brightness gradients, optical flow techniques solve only part of the whole problem. This survey analyses the current solutions and what they offer to address this problem
Pengembangan Media Pembelajaran Elektronik Berbasis Masalah pada Mata Pelajaran Komputer dan Jaringan Dasar

This study aims to obtain valid, practical, and effective problem-based electronic learning media on the computer and basic network subjects. Problem-based electronic learning media is designed to be able to improve student understanding and activities so as to improve learning outcomes. This research uses Research and Development (R and D) research method with 4-D development procedures (define, design, develop, and disseminate). Data analysis techniques used descriptive analysis techniques to describe the validity, practicality, and effectiveness of problem-based electronic learning media. The results obtained from this development research: (1) the validity of problem-based electronic learning media is declared validly on media aspects and material aspects (2) the practicality of problem-based electronic learning media based on teacher and student responses is declared very practically (3) the effectiveness of learning media Problem-based electronics are declared effective in improving learning outcomes and learning motivation. Based on the findings of this study concluded that the problem-based electronic learning media is declared validly, practical and effective to be used as teaching materials in the Computer and Basic Network subjects.
ANALYSIS ON FUNDAMENTAL ALGEBRAIC CONCEPTS AND INFORMATION SECURITY SYSTEM

Cryptography plays a key role to protect the data from unauthorized access. Nowadays various cryptographic algorithms are used. It is not meant of information technology to secure proposed work main target to achieve these tasks and goals. In research study related to any field of science is based on some basic definitions and understandings of some previous results. Therefore we introduce the basic definitions of Algebra and information security system in this chapter which is important to understand the dissertation of the coming chapters. This chapter is further divided into sections which explain the various concepts comprehensively.
Performance Optimization of network using load balancer Techniques

Load Balancer helps in increasing the speed of transmission of data across the web. It increases the performance of the network by reducing network traffic and increasing the responsiveness of the application. Two devices can connect and communicate data to one another thanks to a set of standardized rules. Participants on the internet or their service providers are assigned IP addresses by address registries. In certain conditions the protocol performs better by managing the throughput and connectivity.Cloud computing is a pioneer among the rising technologies in the IT world today. Even though cloud computing has been around for a few years, the globe has yet to reap the full benefits of this technology. Among the many revolutionary effects envisaged as a result of theThere have been few successes with cloud computing technology, and the rest of the goals are currently being worked on.research. Cloud Security and Performance are two of the most significant barriers to cloud computing adoption.stability. One of the variables that has an impact on cloud performance stability is load balancing.computing.
Framework of diacritic segmentation for Arabic handwritten document

&lt;span lang="EN-US"&gt;In &lt;span&gt;recent Arabic standard language and Arabic dialectal texts, diacritics and short vowels are absent. There are some exceptions have been made for the Arabic beginner learner scripts, religious texts and as well as a significant political text. In addition, the text without diacritics is considered ambiguous due to numerous words with different diacritic marks seem identical. However, this paper we present a framework for segmenting diacritics from Arabic handwritten document by using region-based segmentation technique. Since Arabic handwritten and Mushaf Al-Quran contain many diacritical marks. Hence, the diacritics must be properly extracted from Arabic handwritten document to avoid losing some good features. Furthermore, the proposed framework is devised specifically to segment diacritics from Arabic handwritten image, thus there will be no feature extraction, feature selection, and classification processes included. Besides, we will present the methodology that is used to fulfil the objectives of this paper. The pre-processing phases will be explained and more specifically segmentation phase for segmenting diacritics which is the phase we concentrate more in this article. Lastly, we will identify the proposed technique region-based segmentation to facilitate our development throughout the experimental process.&lt;/span&gt;&lt;/span&gt;
A Robust Hybrid Biometric Face Recognition Payment System

Modern civilization has always been endeavoring to achieve a cashless and digital society. The emergence of payment methods like cards, net banking, and digital wallets have enabled the possibility of cashless and cardless online and offline payments. However, these payment methods are at the risk of theft and sometimes may require users to memorize different passwords. Biometric Payments may seem like a viable option but, the fingerprints can be spoofed and dirt particles may damage the fragile sensors. Face recognition payments are more frictionless than the present card, mobile and biometric payment systems as they do not require a device to carry out the transaction. It is also reliable, secure and efficient. Hence, saving time for both the customer and retailer. The previous system used Eigenfaces and Euclidean Distance for face recognition payment. Our proposed system uses Haar Cascades for face detection and Local Binary Patterns Histogram(LBPH) for face recognition. Our proposed approach is more efficient with respect to parameters such as noise reduction, threshold, training time, confidence and accuracy as it achieves a higher noise reduction and accuracy with a lower threshold, training time and confidence.
ANALYSIS OF PROBLEMS IN THE NEEDS OF LEARNING STUDENT PAPER WRITING SKILLS THROUGH JIGSAW MODEL IN THE DIGITAL ERA (Preliminary Lesson Study)

The expectation of learning to write scientific papers for students who are already on college benches is that students are fluent in writing scientific papers in the form of papers. The researcher aims to find out several factors that cause the learning problems of Indonesian Literature Education Study Program students. If they have found a problem factor, the researcher is moved to find a solution to overcome the problem of learning to write student papers. The data analysis technique used is descriptive qualitative using the Miles and Huberman models. The results of the analysis of the problems in learning needs of student paper writing skills that offer the application of jigsaw learning combined with the use of technology for learning.