Reviewerly/exHarmony huggingface dataset:
Efektivitas Metode Bisik Berantai dalam Meningkatkan Keterampilan Menyimak di Kelas 6 SD 010140

The Purpose of this study wa to determine the effectiveness of the chain method in impoving listening skill ini 6 th SD 010140. the subject of this research is Mrs. Widiati a grade 6 teacher at SD 010140 Perk. Gunung Melayu Kecamatan Rahuning, Kabupaten Asahan, Provinsi Sumatera Utara. In this study researchers used qualitative methods, namely research and interpretation techniques that prodused descriptive data in the form of writing and word. The result of the research that has been done show that a chain of whispering games on listening skill in Bahasa Indonesia subjects in grade 6 greatly influences the learning process, which can make students happy and enthusiastic in learning. However this method also has disadvantages of students who are not conducive to making this method applied.
Penerapan Media Belajar Berbasis Digital Google Site Dalam Pembelajaran Lingkungan

Information technology-based learning has become important in the world of modern education. In this digital era, Google has become a service that almost everyone must have. However, in practice, there is a problem with the various conveniences that Google offers, which are open source and should be used as a solution in the transformation of conventional learning environments to digital learning. This research aims to develop Google Site-based digital learning media as a solution to the transformation of conventional learning to digital learning. The R&amp;D method involves needs analysis, media development, UI/UX evaluation, and increasing learningefficiency. The study population consisted of 30 lecturers and students from the Plantation Management Study Program, with 27 people as samples using the random sampling method and Krejcie and Morgan table calculations. The results of the study show the high need for digital media in the post-pandemic era, where online learning is dominant. The development and implementation of open-source Google site-based learning media increases learning efficiency compared to the direct presentation of material through online presentations. The accessibility and features provided by the Google site add value to the UI and UX evaluation for users.
NEGATIVE POLITENESS STRATEGIES IN BATAM COMPANIES' ENGLISH BUSINESS LETTER

This research aimed to the being pessimistic politeness strategy in the text of business letter from several Companies in Batam, Riau Island, Indonesia. This study includes multiple companies, with three companies chosen at random. Brown and Levinson (1987) define negative politeness methods as displaying restraint, formality, and distance. A descriptive qualitative method was used in analyzing the data because it would be explained by words, phrases, and sentences. The researcher employed the Sudaryanto (2015) observational method to obtain data. Brown and Levinson identified five negative politeness methods; however, in this study, the researchers focused solely on the pessimistic strategy. Pragmatics identity method was applied in analyzing the data. it was found that there were nine strategies of being pessimist politeness in the text of business letters. There are 2 data of being pessimistic in Letter 1 by PT. Vancouver Manufacturing Company, 4 data of being pessimistic in the Letter 2 by ABC Software Company, and 3 data of being pessimistic in Letter 3 by Mass Airlines Company.
An Analysis of Teachers’ and Parents’ Perceptions on English Online Learning at Junior High School

Teachers are one of the main factors for the success of education. Parents play an important role in the task and are responsible for the formation of children's character both physically and spiritually. As educators, teachers are the main actors who walk side by side with parents and other important elements. This research analyzes the teachers' perception about English online learning design and the parents' perception about English online learning design at SMP Negeri 01 Seputih Surabaya. This research used a qualitative approach. The results showed that: 1) The teacher's perception of the implementation of online learning in English shows that the teacher feels that online learning is difficult to apply especially in shaping the character of students because teachers are less able to monitor and supervise students directly, lack facilities that support online learning, and teachers also complain that in delivering learning materials, students find it difficult to understand the lessons being taught. 2) Parents' perceptions of the implementation of online English learning show the ineffectiveness of online learning, this is due to parents who feel that their children are not optimal when studying and are still having problems while studying. Keywords: Teachers' Perceptions, Parents'Pperceptions, English Online Learning
Gerga Orange Quality Using Naïve Bayes Based on Feature Extraction

In an effort to increase the number of sales, the process of classifying the type of Gerga citrus fruit is very necessary. The problem that often occurs is the mixing of various types of fruit from the storage warehouse so that the quality of the fruit will be mixed and it will be difficult to determine the selling price because the quality of the fruit itself is not evenly distributed so that a sorting process is needed. There are still many sellers or growers of citrus fruits who sort the quality of the fruit manually so that it can take a very long time. Given these problems, it is necessary to classify the quality of Gerga oranges automatically with the Naïve Bayes Classifier algorithm with GLCM feature extraction and HSV color characteristics. as a method for classifying the quality of Gerga citrus fruit and as for the media used, there is digital image media. From the experiments that have been carried out the use of angles in the formation of co-occurrence matrices with the best accuracy values reaching 80% are found at angles of 0°, 45°, and 135°, while the lowest accuracy values are found at angles of 90°. It was concluded that the Gerga citrus fruit quality classification system using the Naïve Bayes method was categorized as good with an AUC value of 0.8.
Educational Financing Management: Analysis of Sources and Use of Educational Budgets in Elementary Schools

The importance of financing in education brings school principals to try to manage the available budget properly. Significant to improve the quality of education. This study aims to determine the management pattern of education costs in elementary schools in Bogor. This research method is a case study. Data was collected through interviews and documents on primary school financing. Data analysis using the Miles &amp; Huberman model includes (1) data reduction, (2) data display, and (3) concluding. The results of the study illustrate that as much as 70% of the source of income for elementary schools in Bogor comes from the government, namely in the form of BOS funds, while the remaining 30% comes from tuition fees and foundation funds for private elementary schools. The Education Budget pays salaries and procures infrastructure, office stationery, student activities, and school operations. The results of this study indicate that there is still a lack of attention from schools to developing the quality of human resources, which is indicated by the absence of an allocation of education funds that leads to the competence of teachers, staff, and students.
The Influence of the Role Playing Method on the Speaking Ability of Lower Grade Elementary School Students in East Jakarta

The results of observations of third-grade students at SDS Bina Siswa East Jakarta found that students' speaking ability tends to be low because of a lack of self-confidence, low understanding, and the inaccuracy of the learning methods used, especially to improve speaking skills. In connection with this problem, appropriate learning methods are needed to improve students' speaking skills. The use of appropriate learning methods will encourage the creation of meaningful learning and make students actively involved in learning in the future, one of which is the role-playing method. Based on this, this study aimed to determine the effect of the role-playing method on the speaking ability of third-grade students at SDS Bina Siswa East Jakarta. Quantitative research methods with quasi-experimental research types and research design posttest control group design. Data was collected using a performance test to measure students' speaking ability in the form of a speaking ability assessment sheet and then analyzed by t-test. Based on the calculation of the t-test, a significance value of less than 0.05 is obtained; this proves that there is a difference in the results of the speaking ability performance test between the experimental group and the control group. With these differences, role-playing can affect the speaking ability of class III students at SDS Bina Siswa East Jakarta.
Let’s Get Ready for Work – Employability Skills Development in an IS Capstone Project

Aim/Purpose This study aims to explore undergraduate IS students’ employability skills development while performing their final capstone project during their academic studies. Background The importance of soft skills in the Information Systems industry is not an arguable fact and has been broadly discussed both in the industry and the academic literature. The ability of professionals to collaborate, communicate, manage time, negotiate, solve problems, make decisions, and self-learning, called employability skills, are essential skills needed in today’s industry. The development of these skills during undergraduate studies is essential for graduate students’ readiness for work. Methodology A mixed methods approach was employed using exploratory research de-sign, including qualitative and quantitative approaches. First, a qualitative analysis of 156 reflections was performed, resulting in the conceptual framework of facets. Then, a quantitative analysis of the data was per-formed to examine the facets and the differences between the stages of the capstone project. Contribution This study contributes to both academy and industry. The former may use this study’s findings to upgrade academy courses and capstone projects in order to raise students’ readiness for the industry. The later may learn the approaches the academy use and give appropriate feedback. Findings The results showed that students’ reflections on their motivation, knowledge, and skills (teamwork, time management, and inter-communication) demonstrate the importance of those facets in the process they underwent, especially since the reflections collected were unstructured. Recommendations for Practitioners Information Systems undergraduate academic programs should develop structured capstone projects to provide the students with a better platform to learn and experience the employability skills the industry requires. Recommendations for Researchers The study presents a conceptual model based on students’ reflections on their experience performing a capstone project. The impact and influence of each of the model’s components should be further researched and measured. Impact on Society Moreover, it is very important to prepare the students for employability by including a “real-life” capstone project at the end of their undergraduate studies to prepare them to be valuable in the workforce, even at their start point as juniors. Future Research To evaluate the process of employability skills development, a further study can examine students’ perceptions prior to the capstone, during, and after to assess the progress and changes. To generalize the results, it would be valuable to investigate whether the findings of this study are consistent across different institutions and disciplines. Keywords employability skills, capstone projects, soft skills, motivation, information systems studies, student reflections
Alogrithms for the ACD Problem and Cryptanalysis of ACD-based FHE schemes, Revisited

The security of several full homomorphic encryption (FHE) schemes depends on the hardness of the approximate common divisor (ACD) problem. The analysis of attack and defense against the system is one of the frontiers of cryptography research. In this paper, the performance of existing algorithms, including orthogonal lattice, simultaneous diophantine approximation, multivariate polynomial and sample pre-processing are reviewed and analyzed for solving the ACD problem. Orthogonal lattice (OL) algorithms are divided into two categories (OL-$\land$ and OL-$\vee$) for the first time. And an improved algorithm of OL-$\vee$ is presented to solve the GACD problem. This new algorithm works well in polynomial time if the parameter satisﬁes certain conditions. Compared with Ding and Tao's OL algorithm, the lattice reduction algorithm is used only once, and when the error vector $\mathbf{r}$ is recovered in Ding et al.'s OL algorithm, the possible difference between the restored and the true value of $p$ is given. It is helpful to expand the scope of OL attacks.
Unsupervised Low-Light Image Enhancement via Virtual Diffraction Information in Frequency Domain

With the advent of deep learning, significant progress has been made in low-light image enhancement methods. However, deep learning requires enormous paired training data, which is challenging to capture in real-world scenarios.To address this limitation, this paper presents a novel unsupervised low-light image enhancement method, which first introduces the frequency domain features of images in low-light image enhancement tasks. Our work is inspired by imagining a digital image as a spatially varying metaphoric “field of light”, then subjecting the influence of physical processes such as diffraction and coherent detection back onto the original image space via a frequency-domain to spatial-domain transformation (inverse Fourier transform). However, the mathematical model created by this physical process still requires complex manual tuning of the parameters for different scene conditions to achieve the best adjustment. Therefore, we proposed a dual-branch convolution network to estimate pixel-wise and high-order spatial interactions for dynamic range adjustment of the frequency feature of the given low-light image. Guided by the frequency feature from the “field of light” and parameter estimation networks, our method enables dynamic enhancement of low-light images. Extensive experiments have shown that our method performs well compared to state-of-the-art unsupervised, and its performance approximates the level of the state-of-the-art supervised methods qualitatively and quantitatively. At the same time, the light network structure design allows the proposed method to have an extremely fast inference speed(nearly 150 FPS on an NVIDIA 3090 Ti GPU for an image of size 600×400×3 ). Furthermore, the potential benefits of our method to object detection in the dark are discussed.
Utilizing Machine Learning to Predict the Number of Bikes in an Area

Machine learning is a type of Artificial Intelligence that uses data to make predictions and improve the accuracy of its outcomes. In this article, the problem discussed is classified as supervised learning and the technique utilized is Logistic Regression. After a description detailing what supervised learning and logistic regression are, using a data set to develop a model which predicts the number of bikes a rental bike company should provide based on certain conditions is discussed. The accuracy of this model is also communicated and the challenges and how the final estimations were reached are covered.
Visual Computing Models in Cancer: PET/CT, CAD, CNN, and ST-Net

Visual computing is a discipline in computer science that allows computers to acquisite, process, and analyze visual data. In the application field of medicine, it enables to development of new methods for the visualization, detection, and analysis of diseases. Therefore, it plays a significant role in developing the understanding of diseases. Taking the fact that cancer is currently one of the deadliest and most frequent diseases around the world into consideration, it is crucial to generate effective methods for the study of cancer in order to provide appropriate management strategies for the disease and treatment methods. Research has shown that methods based on visual computing can detect, classify, and analyze the cancerous tissues in a patient successfully with high accuracy. This paper focuses on the PET/CT, CAD, CNN, and ST-Net visual computing models by evaluating their working mechanisms, their efficacy in the use of cancer with the help of previous research made in the literature, and their limitations in a medical approach.
Convolutional Neural Network Approach to Classifying the CIFAR-10 Dataset

Convolutional neural network (CNN) is a powerful tool that can be used in many applications of machine learning. This paper demonstrates the effectiveness of using a CNN to classify images in the CIFAR-10 dataset. The model achieved an accuracy of 0.6276 and a loss of 1.116452 on the validation set. It was observed that the accuracy of predictions varied from class to class, and this paper discusses the potential causes for this variation, such as similar classes sharing common features. Further research in this field could lead to improvement in driving assistance technology and eventually automated driving.
Natural Language Processing used in sentiment analysis of poetry: a study of six common techniques

This paper explores and compares the accuracies of six different NLP model techniques when applied to analysis of English poetry. It was found that bigram-based and word embedding-based models were the most accurate in deriving emotions from the bodies of text in the corpus, with respective accuracies of 61.67% and 61.68%. The least accurate models were the unigram-based model and distributed dictionary-based model, constructed using the traditional approach rather than the new methodology, and had accuracies of 11.173% and 48.17% respectively. Most models passed the benchmark accuracies of 49.42% and 47.86%, the higher accuracy one being a word count model and lower one being a sentiment model. The need for newer methodologies that allow for higher dimensional levels of semantic analysis to be performed is also discussed in this paper, along with the potential impacts of this research to the field of Natural Language Processing.
Catch Me If You Can: Deceiving Stance Detection and Geotagging Models to Protect Privacy of Individuals on Twitter

The recent advances in natural language processing have yielded many exciting developments in text analysis and language understanding models; however, these models can also be used to track people, bringing severe privacy concerns. In this work, we investigate what individuals can do to avoid being detected by those models while using social media platforms. We ground our investigation in two exposure-risky tasks, stance detection and geotagging. We explore a variety of simple techniques for modifying text, such as inserting typos in salient words, paraphrasing, and adding dummy social media posts. Our experiments show that the performance of BERT-based models fine-tuned for stance detection decreases significantly due to typos, but it is not affected by paraphrasing. Moreover, we find that typos have minimal impact on state-of-the-art geotagging models due to their increased reliance on social networks; however, we show that users can deceive those models by interacting with different users, reducing their performance by almost 50%.
THE Minahasan Art and Culture

Tourism will grow into an industry that is very profitable and has very bright prospects in the future for national development. In addition, Tourism can provide employment and business opportunities, foster culture and arts and for domestic tourists and Tourism, it is useful to hone the love of the homeland and improve National Discipline. Tourism has become one of the largest industries in the world and is a major mainstay in generating foreign exchange in various countries. Cultural Tourism Development is one of the strategies pursued to encourage an increase in the tourism sector in addition to cultural tourism as one of the factors that greatly influence the increase in tourism in the region. During this time the field of Cultural Tourism has not been much raised on the matter with the development of the field of Cultural Tourism in the form of art, dance, and various regional cultures that are expected to be able to improve the image destination of the tourism sector.
THE USE OF ARTIFICIAL INTELLIGENCE IN DIGITAL FORENSICS

&lt;p&gt;Digital forensics is a vital field in the IT industry that deals with the identification, collection, preservation, and analysis of electronic data. This paper explores the fundamental aspects of digital forensics in the IT industry, including its importance, key challenges, and various techniques used in the investigation process. Furthermore, the paper provides insights into the various tools and technologies that have been developed to aid in digital forensics investigations. Finally, the paper concludes by highlighting the significance of digital forensics in the IT industry and the need for professionals to stay up-to-date with the latest trends and practices in the field. &lt;/p&gt; &lt;p&gt;GENERAL TERMS:&lt;/p&gt; &lt;p&gt;Digital forensics, Incident response, Evidence collection and preservation, Data analysis, Cyber security, Investigation, Cybercrime &lt;/p&gt;
New Image Encryption Method Based on two Stage Scrambling

The purpose of digital image scrambling technology is to put a meaningful image into a disordered one to enhance the resistance ability against illegal attacks. This paper proposed an image scrambling algorithm based on idea of movement of elephant in the chess board the system consist of two main steps the first one rotate each diagonal by key generated from computing the standard deviation the second step include exchange the upper half of image with the lower half of image the proposed system shows a good result and we reach 100 percent accuracy in decryption thus the proposed system can be used by any application for secure transmitting.
Dietry Monitoring System Using Decision Tree to Control Human Obesity

Nowadays, obesity is one of the dangerous diseases in the world. Lack of dietary monitoring system will make it difficult for people with obesity to reduce their weight problems. The main objective of this project is to develop a dietary monitoring system that can be used by everybody especially for obesity’s people. The method used in this study is to identify the strength and weaknesses of the existing system which involves reviewing some articles, journals, magazines, and books. The survey was conducted which involves 10 people answering the questionnaire. Respondent answered was used to improve the quality of the system. Next method is utilizing a waterfall model as a method to develop a dietary monitoring system. The system applied the decision tree technique to a classified food calorie. Therefore, the decision tree technique was used in developing this system. The last method used in this study involves the participation of three respondents to evaluate the usability of the system. Respondents need to answer whether they satisfied with the system or they can give suggestions for future improvement. The results of this study show that obesity is a public health issue that is rapidly increasing and must be addressed seriously by developing the system. Significant by developed this system such as helping obesity’s people to diet by giving them the guideline. In conclusion, this system will help people to diet using the decision tree technique for classifying food calories.