Reviewerly/exHarmony huggingface dataset:
Internal Auditor Transformation Strategy in the Industrial Revolution 4.0 Era: Literature Review

This paper is intended to identify a transformation strategy that can be applied by the Government Internal Supervisory Apparatus (APIP) to face audit challenges in the industrial revolution 4.0 era.In line with the influence of industry 4.0 on audit activities, APIP must quickly adapt to technological developments.Utilization of technology 4.0 places APIP as a business analyst to find errors in business processes and determine solutions to these errors.So, in order to face the challenges of industry 4.0, an APIP transformation strategy is needed.The author reveals that the APIP transformation strategy in facing industry 4.0 such as (1) APIP must be able to use data collecting equipment, such as sensors and software, to collect data, (2) APIP must have characters that can be their hallmark in completing their audit tasks.These characters include cognitive abilities, ability to solve complex problems, communication skills, understanding of their position in the internal control system, and agility (3) APIP must be professional, millennial, innovative, and not afraid of failure while still prioritizing integrity, objectivity, and professionalism.
Implementasi Metode Steam Di Taman Kanak-kanak

STEAM is important in AUD because the STEAM method is an active learning and triggers children to solve problems. So here can be achieved an effort to implement STEAM-Based Learning. So that many schools have used the STEAM method, one of which is Tiara Bunda Kindergarten, here are some aspects of development that have been developed using this STEAM method, for that the author is interested in exploring and analyzing the process of implementing the STEAM method in Tiara Bunda Kindergarten. The research method used in this research is descriptive qualitative. This research was conducted at Tiara Bunda Pesisir Selatan Kindergarten. Informants or respondents in this study were the Principal and Teachers. Data collection techniques were carried out through observation, interviews and documentation. The data obtained are described in accordance with the existing reality. Data analysis in the form of descriptions in the form of words and data validity techniques using data validity techniques using data reduction, data presentation, and drawing conclusions. The results of this study indicate that Tiara Bunda Pesisir Selatan Kindergarten has implemented or implemented learning using the STEAM method well. This can be seen from how the learning process takes place and the material provided is in accordance with the form of learning using the STEAM method, be it Science, Technology, Engineering, Arts, and Mathematics has been carried out properly and in accordance with the provisions
Analisis Sentimen Tweet Tentang UU Cipta Kerja Menggunakan Algoritma SVM Berbasis PSO

Support Vector Machine (SVM) is one of the most widely used classification algorithms for sentiment analysis and has been shown to provide satisfactory performance. However, despite its advantages, the SVM algorithm still has weaknesses in selecting the right SVM parameters to optimize the performance. In this study, sentiment analysis was done with the use of data called tweets about Undang-Undang Cipta Kerja which reap many pros and cons by the people in Indonesia, especially the laborers. The classification method used in this study is the Support Vector Machine algorithm which is optimized using the Particle Swarm Optimization method for the SVM parameters selection in the hope of optimizing the performance generated by the SVM algorithm in sentiment analysis. The results of the study using 10 k-fold cross-validations using the SVM algorithm resulted in an accuracy of 92,99%, a precision of 93,24%, and a recall of 93%. Meanwhile, the SVM and PSO algorithms produce an accuracy of 95%, precision of 95,08%, and recall of 94,97%. The results show that the Particle Swarm Optimization method can overcome the weaknesses of the Support Vector Machine algorithm in the problem of parameter selection and has succeeded in improving the resulting performance where the SVM-PSO is more superior to SVM without optimization in sentiment analysis.
Application of Support Vector Machine (SVM) Algorithm in Classification of Low-Cape Communities in Lampung Timur

Classification is a technique for grouping and categorizing specific standards as material for compiling information, making conclusions, or making decisions. This paper discusses data classification for underprivileged communities in Tanjung Inten, Purbolinggo, East Lampung using the Support Vector Machine (SVM) algorithm, then grouped into two label classes, namely the less fortunate and capable label classes. From the data that has been collected, 1154 data. The data goes through processing, scoring, labeling, and testing, producing two classes of results, namely less fortunate and capable. From the test data using the Support Vector Machine (SVM) method, the accuracy score is 97%, the precision score is 97%, the Recall score is 100%, and the F1-Score is 98%. This test resulted in a proportion of classification with the capable label is 87% and less fortunate label is 13%
Gerakan Literasi Finansial di SMA Kabupaten Kubu Raya Kalimantan Barat

The purpose of this study was to determine how the financial literacy movement with indicators of class basis, school cultural basis and community basis in Senior High School Kubu Raya Regency, West Kalimantan. The method used was a descriptive method with a survey form. The research subject was an economic teacher, data collection was done by interview and a questionnaire using google form. The data analysis step used the Interactive Analysis Model from Miles and Huberman. The technique of checking the validity of the data used source triangulation, technique triangulation, and participant extension. The results showed that there was no financial literacy movement in Senior High School Kubu Raya, West Kalimantan. In the school-based indicator there has never been any financial literacy training and there has been no application of the value of financial literacy in learning. On the school cultural basis indicator, there were no variations in books and financial literacy props, the frequency of borrowing financial literacy reading materials is limited to borrowing economic textbooks in the library, there were no financial literacy activities and policies, the presentation of financial literacy information was only on economic subjects, there were no sites related to financial literacy, there were no school bank while only a small number of school cooperations are active. In the community-based indicator, there were no supporting tools and media for financial literacy and there was no involvement of parents and the community in developing financial literacy.
Knuth Morris Pratt String Matching Algorithm in Searching for Zakat Information and Social Activities

Algorithms are one of the components that need to be considered in the development of information systems. Determination of the algorithm is adjusted to the purpose of the system to be built. One algorithm that can be used is string matching. The string matching algorithm will play a role in searching for a string consisting of several characters (usually called a pattern). The method used in this research is string matching knuth morris pratt (KMP) which is used to search zakat information and social activities in the search engine system. KMP is a string matching algorithm with good performance. The results showed the performance of string matching using the KMP algorithm with 5 trials of input pattern on zakat information with execution times of 0.03 ms, 0.03 ms, 0.02 ms, 0.02 ms and 0.03 ms. And 5 times the input pattern experiment on social activities with execution time of 0.02 ms, 0.02 ms, 0.03 ms, 0.03 ms and 0.02 ms. Thus the average execution time of the KMP algorithm in string matching is 0.026 ms and 0.024 ms.
Real Time Indoor Object Detection Aid for Blind

Our proposal accentuates to help blind people to navigate independently using real-time indoor object detection and identification model.The project aims to help blind and visually impaired people to detect and recognize objects around them, through a small camera that is fixed on the glasses.The device setup gives an audio output that is sent to an earphone placed on the person's ear to help him/her find various items easily and independently.All the captured data will be fed to raspberry pi that will have an inbuilt code for object detection in python language and will contain Opencv and TensorFlow files in it.The unit will analyze the image based on the ssd_mobilenet network and custom data-set and the processed data that is the name of the object will come as output.This output will be heard by the user in voice format by incorporating TTS in our model.This model will act as an aid for blind people and will help them to do the daily chores easily and independently.
IMAGE COMPRESSION USING DISCRETE WAVELET TRANSFORM IN SIMULINK

With the advancement of technology and the entry into the digital era, world now have to deal with a massive amount of data on a regular basis, which can be tough. As a result, in order to be put to practical use, digital information must be stored and retrieved in an efficient and effective manner. Wavelets are a mathematical encoding technique that layer’s information according to its level of detail. Approximations at various intermediate levels are made easier with this stacking. These approximations take up a fraction of the space that the genuine data does. A low-complex 2D image compression method employing wavelets as the basis functions is described, as well as a method for assessing the compressed image is presented.
Non-generational Geometric Semantic Genetic Programming

Geometric Semantic Genetic Programming (GSGP) has been shown to outperform conventional Genetic Programming (GP) in symbolic regression problems. GSGP and its variants rely on the iterative and stochastic production of linear combinations of programs that appear in the initial population and the search process, and the adjustment of their coefficients. However, those core procedures include inefficiency. That is that programs to be combined linearly are increasing with generations. In this paper, we propose Non-generational GSGP (Ng-GSGP), which generates a linear combination of programs in a single step, instead of iterative operations as in GSGP. We compare Ng-GSGP with the conventional GSGP and its variant on 10 symbolic regression problems, and demonstrate that Ng-GSGP is able to generate better programs with much fewer fitness evaluations on most of the problems.
Bad Speech, Good Evidence: Content Moderation in the Context of Open-Source Investigations

Abstract This article explores how content moderation on social media platforms impacts the work of open-source investigators through its routine removal of content having evidentiary value. These practices have rendered social media platforms susceptible to public criticism and scrutiny. However, these criticisms have largely been levied by a community who cares about content removal’s impact on free expression online. This swath of concerns does not comport with those of international criminal investigators who have increasingly turned to platforms for evidence gathering. Rather than confronting the issue, investigators have absorbed the costs by downplaying the impact of content removal on their work and by seeking to preserve the content on their own. I examine the disconnect between these two groups in their respective approaches to the problem of content removal and argue that both communities can stand to benefit from joining forces and taking notice of the convergence of their respective concerns.
Research on Entrepreneurial Ability Model of College Students in Big Data Era—— A Case Study of “San Xun Flower Shop”

Innovation and entrepreneurship education is a new requirement for education under the situation of rapid social development in the new era. It is an important quality education in the current education system, and its essence is a skill education. Since the concept of "mass innovation, national entrepreneurship" was put forward, the innovation and entrepreneurship education for college students has been carried out in China, and some results have been achieved. But from the overall point of view, the innovation and entrepreneurship education of college students in China should be improved, and a specific, complete and scientific education system has not yet been formed. On this basis, this article analyzes the current problems in the education of cultivating college students’ innovation and entrepreneurship ability according to the experience of the project of “San Xuan Flower Shop”, and proposes some suggestions for reference.
Self-testing two-qubit maximally entangled states from generalized Clauser-Horne-Shimony-Holt tests

Device-independent certification, also known as self-testing, aims at guaranteeing the proper functioning of untrusted and uncharacterized devices. For example, the quality of an unknown source expected to produce two-qubit maximally entangled states can be evaluated in a bipartite scenario, each party using two binary measurements. The most robust approach consists in deducing the fidelity of produced states with respect to a two-qubit maximally entangled state from the violation of the CHSH inequality. In this paper, we show how the self-testing of two-qubit maximally entangled states is improved by a refined analysis of measurement statistics. The use of suitably chosen Bell tests, depending on the observed correlations, allows one to conclude higher fidelities than ones previously known. In particular, nontrivial self-testing statements can be obtained from correlations that cannot be exploited by a CHSH-based self-testing strategy. Our results not only provide insight into the set of quantum correlations suited for self-testing, but also facilitate the experimental implementations of device-independent certifications.
Coastal Students’ Perspectives on Digital Reading Comprehension: A Rasch Model Analysis

The purpose of this study was to determine the coastal students' perspective on digital reading comprehension.The study was conducted at Universitas Maritim Raja Ali Haji in the department of English Education in 2021.A descriptive quantitative method using questionnaires was applied to collect data from 70 second-semester students who participated in this exercise.The data collected was analyzed quantitatively using the Rasch model called Winsteps version 3.73 software.The results revealed that most coastal students had a good perception of digital reading comprehension.Furthermore, they believed digital reading greatly improved their reading comprehension than traditional methods.
The Effectiveness of E-learning in Saudi Arabia During the Spread of COVID-19

E-learning is becoming increasingly popular, and learners are being offered expanded opportunities to continue their education at a wide range of ages. No geographical boundaries prevent them from learning and various other benefits based on their situation and needs. The purpose of the study is to evaluate the effectiveness of e-learning in Sadia Ariba during COVID-19. Three hundred thirty-two respondents took part in the survey, with different grade levels, ages, and locations in the country. Among the respondents, 28.6% were males, and the females were 71.4%. The majority reported that e-learning is effective; according to the findings, 72.3% accessed the material easily. However, 23.2% and 29.2% responded naturally and disagreed regarding experiencing a good internet connection. In addition, 25.6% were not satisfied with teachers' skills in designing electronic learning content.41% accounted for natural and disagreed with receiving information through electronic learning, the same as traditional learning. The ministry of education should invest in electronic learning to utilize it even after overcoming COVID-19.
Bitcoin Selfish Mining Modeling and Dependability Analysis

Blockchain technology has gained prominence over the last decade. Numerous achievements have been made regarding how this technology can be utilized in different aspects of the industry, market, and governmental departments. Due to the safety-critical and security-critical nature of their uses, it is pivotal to model the dependability of blockchain-based systems. In this study, we focus on Bitcoin, a blockchain-based peer-to-peer cryptocurrency system. A continuous-time Markov chain-based analytical method is put forward to model and quantify the dependability of the Bitcoin system under selfish mining attacks. Numerical results are provided to examine the influences of several key parameters related to selfish miners’ computing power, attack triggering, and honest miners’ recovery capability. The conclusion made based on this research may contribute to the design of resilience algorithms to enhance the self-defense and robustness of cryptocurrency systems.
Using a social robot for different types of feedback during university lectures

In this paper we present a long-term study in which a social robot was used as an embodied feedback channel during a series of university lectures spanning over one academic year. We used a Pepper robot from Softbank Robotics within an enactive didactics framework in order to reinforce the structural coupling between the teacher, the students and the content of the lecture. The robot provided different types of feedback during the lectures. In this paper we will focus on feedback that informed the students of their learning progress and that helped the teacher to understand how the students were able to follow each lecture. At the end of the lecture series we used questionnaires as qualitative measures for how the students perceived the feedback of the robot. Our results show a positive response of the students to the robot. We asked the students also how they thought the robot's feedback affected their learning progress. The vast majority of the students reported that the robot indeed helped them to reflect about their level of understanding of the content of the lecture and facilitated the initiation of interventions to improve their learning.
Naïve Hyper-heuristic Online Learning to Generate Unfolded Population-based Metaheuristics to Solve Continuous Optimization Problems

Optimization is a field that never runs out nor becomes irrelevant. Nowadays, it is pretty hard to find a solver from the overpopulation of metaheuristics that properly deals with a given problem. This is even considered an additional problem. In this work, we propose a novel and simple methodology for solving the Metaheuristic Composition Optimization Problem, which involves designing heuristic-based procedures that solve continuous optimization problems. This methodology implements a naíve online learning that identifies the most relevant search operators to include in the candidate heuristic-based procedures. For representing these procedures, we adopt our previously proposed unfolded metaheuristic model. We prove the feasibility of this approach via a two-fold experiment employing several continuous optimization problems. Our data revealed that the learning procedure is worthwhile, finding adequate solutions for problems in up to 50 dimensions.
Reliability and performance analysis of a mini solar home system installed in Indonesian household

During the COVID-19 pandemic since early 2020 in Indonesia, the demand for electrical energy in the housing sector has increased significantly. This is due to the government’s recommendation to reduce activities on the outside and work from home, specifically for educational and entertainment activities. Those are almost recommended to be done online. Many people complain about the increase in monthly electricity payments compared to before the pandemic. The construction of solar power plants in housing/solar home systems (SHS) will reduce the electricity consumption from the public grid. This SHS installation can be used to supply some household electricity needs, such as computers, televisions, internet facilities, lighting, et cetera. In this article, the researchers discuss the performance testing of SHS with a capacity of 300 Wp. It is installed in the house buildings accompanied by the design and measurement of solar energy potential.
Application of Hash Sha-256 Algorithm in Website-Based Sales Software Engineering

Rapid technological developments can spur changes in the cycle of human activities, one of which is software engineering activities that continue to develop in accordance with technological developments, the development of software engineering activities is also developing methods of data security to withstand attacks from irresponsible parties. answer. This research was conducted to analyze the performance and robustness of the sha-256 data security method with ciphertext customization. The steps that the researchers took in conducting the analysis were collecting theory and case examples, designing programs, implementing programs, testing and saving the results. Based on this process, it can be concluded that ciphertext customization on sha-256 is needed to strengthen security and resistance to attacks from irresponsible parties, besides that the performance of sha-256 calculations with customization on ciphertext and without ciphertext is not too much different where only 65 ms difference based on the results of performance testing that researchers did.
IT EDUCATION: LEARNING TO CREATE NEW PRODUCTS

The article deals with the introduction of a special discipline into the educational process of universities aimed at developing competencies in creating new products in the field of high technology and not only. The focus of the discipline is on the main issues that must be resolved even before making a decision on the production of a product: the search for potential consumers, the formation of a target market, the identification of consumer preferences and unmet needs. Mastering the necessary competencies to solve these issues opens the way to the right attitude to the issues of creative activity both in the field of high technology and in other areas.
The Mode Exploration of Industry-Education Integration of Graduate Education in China

Graduate education is regarded as an important component of China's innovation driven development strategy.In the era of innovation, how to deepen industry-education integration, accordingly, improving the innovative ability of postgraduates and cultivating high-level innovative talents needed by the country and the industry, is the current goal of Chinese educators.This paper introduces the connotation of industry-education integration, focuses on the analysis of the difficulties encountered in the process of promoting industryeducation integration in China and gives suggestions.It is essential to build a complete system of policies and lows with a comprehensive evaluation system.In addition, the important role of the enterprise should be properly brought into play.
Agriculture data sharing: Conceptual tools in the technical toolbox and implementation in the Open Ag Data Alliance framework

Abstract Data privacy has become a critical issue within the agriculture and food industry. The real‐time conversion of data to information has been shown to be incredibly valuable to the industry but often requires sharing data with software, platforms, customers, and regulators outside the data owner's control. While much work in this area has focused on legal protections for data privacy, less has been devoted to technical architectures to support different sharing models. This paper defines some “tools in the toolbox” for designing such systems that are accessible to both technical and nontechnical audiences as well as several “sharing design patterns” using the Open Ag Data Alliance (OADA) framework. These tools and patterns are helpful in classifying and understanding both existing and future data flows in agriculture and their privacy implications.