Reviewerly/exHarmony huggingface dataset:
A Method for Perception and Assessment of Semantic Textual Similarities in English

This research proposes a method for the detection of semantic similarities in text snippets; the method achieves an unsupervised extraction and comparison of semantic information by mimicking skills for the identification of clauses and possible verb conjugations, the selection of the most accurate organization of the parts of speech, and similarity analysis by a direct comparison on the parts of speech from a pair of text snippets. The method for the extraction of the parts of speech in each text exploits a knowledge base structured as a dictionary and a thesaurus to identify the possible labels of each word and its synonyms. The method consists of the processes of perception, debiasing, reasoning and assessment. The perception module decomposes the text into blocks of information focused on the elicitation of the parts of speech. The debiasing module reorganizes the blocks of information due to the biases that may be produced in the previous perception. The reasoning module finds the similarities between blocks from two texts through analyses of similarities on synonymy, morphological properties, and the relative position of similar concepts within the texts. The assessment generates a judgement on the output produced by the reasoning as the averaged similarity assessment obtained from the parts of speech similarities of blocks. The proposed method is implemented on an English language version to exploit a knowledge base in English for the extraction of the similarities and differences of texts. The system implements a set of syntactic and logical rules that enable the autonomous reasoning that uses a knowledge base regardless of the concepts and knowledge domains of the latter. A system developed with the proposed method is tested on the “test” dataset used on the SemEval 2017 competition on seven knowledge bases compiled from six dictionaries and two thesauruses. The results indicate that the performance of the method increases as the degree of completeness of concepts and their relations increase, and the Pearson correlation for the most accurate knowledge base is 77%.
Website Dinamis Experience Center Untuk Menampilkan Interplay Di Bidang Infrastructure Service &amp; Reseach (ISR) PT. Telkom Indonesia, TBK

PT. Telkom Indonesia in an effort to transform into a digital telecommunication company, TelkomGroup implements a customer-oriented company business and operational strategy. One of them is by creating a Website Experience Center to display the interplay made in the Infrastructure Service &amp; Research IRA Unit. In making it the author uses the Extreme Programming Method which is considered appropriate because it is an adaptive and flexible method in its stages. The results obtained after analysis and design, as well as implementation of the Website Experience Center, Website Experience can be made as expected even though there are several obstacles in its manufacture. Where it is necessary to use adequate devices in its manufacture in order to produce maximum results as well
Pengembangan Media Pembelajaran Display Board Berbasis Discovery Learning Pada Tema 6 Subtema 2 Kelas V SD Negeri 040452 Kabanjahe T.A 2022/2023

This study aims to determine the validity that is validated by the media validator, material validator, and test instrument validator, find out practicality by teacher education practitioners and students, and find out the effectiveness as seen from the results of the pre-test post-test scores on display board learning media based on discovery learning on theme 6, sub-theme 2 class V at SD Negeri 040452 Kabanjahe, the number of which is 25 people. This research is research and development which leads to the ADDIE development model which consists of 5 stages, namely the analysis, design, development, implementation, and evaluation stages. Based on the results of the research, the display board media developed showed results, including: (1) The results of the validity by each validator obtained the final results of media validation with a percentage score of 92% (Very Eligible), material validation with a percentage score of 90.66% (Very Eligible). Feasible), test instrument validation with a percentage score of 94% (Very Feasible). (2) The results of practicality by teacher education practitioners obtained results with a percentage score of 96% (Very Practical), the results of the overall response of students obtained results of 82.4% (Very Practical). (3) The results of the effectiveness through the pre-test post-test obtained the final score with a percentage of 88% (Very Effective). After obtaining the overall results of research and development, the researcher drew the conclusion that discovery learning-based display board learning media is valid, practical, and effective in the teaching process in schools.
Classification Of Lung and Colon Cancer Histopathological Images Using Convolutional Neural Network (CNN) Method An A Pre-Trained Models

Cancer is a severe illness that can affect many young and older people. In Indonesia, lung cancer is the leading cause of cancer-related death, whereas colon cancer, with more than 1.8 million cases worldwide in 2018, is the third most common cancer. This study intends to create a model to categorize histological images of lung and colon cancer into five labels to aid medical professionals' categorization job. This study uses a pre-trained model idea known as VGG19 in its CNN (Convolutional Neural Network) technique. The dataset uses 25,000 histological graphic pictures with a ratio of 80% training data and 20% testing data. The classification system for lung and colon cancer contains five categories: lung benign tissue, lung adenocarcinoma, lung squamous cell carcinoma, colon adenocarcinoma, and colon benign tissue. The training result revealed a 99.96% accuracy rate and a 1.5% loss rate. The model can be rated as excellent based on these results
Development and Validation of E-Books Based on Socio-Scientific Issues to Improve The Argumentation Skills of High School Students

This study aims to develop and analyze the validity of the e-book on environmental pollution based on socio-scientific issues to improve students' argumentation skills. The development of the e-book uses the ADDIE design (Analysis, Design, Development, Implementation, and Evaluation), but this research has only reached the development stage (Development/D). This study used a qualitative descriptive analysis using a validation sheet instrument in the form of a questionnaire by two experts: material experts and technology/application experts. Data analysis technique using Content Validity Ratio (CVR). The validation results of material experts got a score of 98.38% in the very feasible category, while the application/technology expert for evaluating the application of content and language feasibility, respectively, got a score of 85.94% and 81.58% in the very feasible category. Based on the assessment results of the two validators, the e-book on environmental pollution based on socio-scientific issues was declared valid and suitable for use in the learning process. The conceptual implication of this study is that environmental pollution e-books based on socio-scientific issues can facilitate students in developing argumentation skills. As for the practical implications, the e-book can be used as an innovation as a Biology learning resource that makes it easier for students to learn independently and streamlines the delivery of material in learning activities in the classroom for teachers.
Pengembangan Media E-Pop untuk Meningkatkan Kemampuan Membaca Permulaan Anak Usia 5-6 Tahun

The purpose of this study was to determine the development and suitability of electronic media to improve early reading skills in children aged 5-6 years. The research method used is Research and Development (RnD) which produces products and can test the effectiveness of products. The data analysis technique used by researchers inthis study is a quantitative descriptive analysis technique. Analysis of product feasibility data is carried out by valuating the results determined by learning media experts and material experts in the form of a questionnaire (questionnaire). The resulting development product is in the form of e-pop media consisting of an electrical circuit controlled by the Android system and packaged in a box as a learning tool to develop early reading skills for children aged 5-6 years. The data analysis technique used is a quantitative descriptive analysis technique. from the research it can be concluded that the validation of material experts is 88% "very feasible", the validation of media experts is 87% "very feasible" and the validation of educators is 96% "very feasible". The percentage of results of limited trials conducted was 89%. The results of the study show that e-pop media can be used as a learning tool to improve the beginning reading skills of children aged 5-6 years.
Pengaruh Penggunaan Media Video Pembelajaran terhadap Hasil Belajar Siswa Kelas IV SD Negeri 097323 Dolok Hataran

The problem in this study is the low IPS scores obtained by students, the lack of learning media used by teachers at SD Negeri 097323 Dolok Hataran. This study aims to find out how the influence of the use of learning video media on social studies learning outcomes for class IV students. The subjects in this study were all of class IV, where the number of students was 30 people consisting of 18 boys and 12 girls. This type of research is quantitative research with a pre-experimental approach. This research started from pre-test to post-test. There were 30 students who did the pre-test and post-test, where the average pre-test score was 64 and the post-test average score was 80. he results of the N-gene test obtained an N-gene score of 0.65 in the moderate or quite effective category. Based on the acquisition of pre-test and post-test data, it can be concluded that learning video media has an effect on student learning outcomes and can improve social studies learning outcomes for class IV students at SD Negeri 097323 Dolok Hataran.
DETEKSI PENYAKIT BERCAK COKLAT, COKLAT SEMPIT DAN HAWAR MELALUI SPEKTRUM WARNA CITRA DIGITAL DAUN PADI MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK

Rice is a prominent food crop commodity and has high potential in the agricultural sector, where rice is a staple food source for Indonesian people. This rice plant certainly has several obstacles, one of which is the presence of rice plant disease attacks through rice leaf spot which can cause crop failure, causing farmers to experience many losses and resulting in poor crop quality, namely empty or empty rice. The long identification process and if the treatment for this disease is very slow will cause the cost of treatment to swell. The use of digital image processing technology in solving problems in this study is to identify rice diseases through digital images based on the morphology of rice leaf spots. One way is by image classification or object classification in the image. The method that can be used in classifying this image is the Convolutional Neural Network (CNN). The accuracy obtained from the Convolutional Neural Network method is based on the 2 types of architecture used, namely the Letnet-5 architecture produces an accuracy of 85% and the Custom architecture produces an accuracy of 90%.
Detailed Process for Developing an Efficient Anomaly Detection Algorithm for Real-Time Streaming Data in Large-Scale Industrial Systems

Anomaly detection plays a critical role in large-scale industrial systems, where real-time streaming data is generated at high volumes. This research journal presents an in-depth study on developing an efficient anomaly detection algorithm specifically designed for such industrial systems. The goal is to identify abnormal patterns and deviations from normal behavior, enabling proactive maintenance, improved operational efficiency, and reduced downtime. The proposed algorithm leverages machine learning and stream processing techniques to handle the challenges associated with real- time streaming data analysis. The research covers algorithm design, implementation, evaluation, and performance analysis using large-scale datasets from industrial domains. Keywords: anomaly detection, real-time streaming data, large-scale industrial systems, machine learning, stream processing
Layout Cross-Browser Failure Classification for Mobile Responsive Design Web Applications: Combining Classification Models Using Feature Selection

Cross-browser incompatibilities (XBIs) are defined as inconsistencies that can be observed in Web applications when they are rendered in a specific browser compared to others. These inconsistencies are associated with differences in the way each browser implements its capabilities and renders Web applications. The inconsistencies range from minor layout differences to lack of core functionalities of Web applications when rendered in specific browsers. The state of the art proposes different approaches for detecting XBIs and many of them are based on classification models, using features extracted from the document object model (DOM) structure (DOM-based approaches) and screenshots (computer vision approaches) of Web applications. To the best of our knowledge, a comparison between DOM-based and computer vision classification models has not yet been reported in the literature, and a combination between both approaches could possibly lead to increased accuracy of classification models. In this article, we extend the use of these classification models for detecting layout XBIs in responsive design Web applications, rendered on different browser viewport widths and devices (iPhone 12 mini, iPhone 12, iPhone 12 Pro Max, and Pixel XL). We investigate the use of state-of-the-art classification models (Browserbite, CrossCheck, and our previous work) for detecting layout cross-browser failures, which consist of layout XBIs that negatively affect the layout of responsive design Web applications. Furthermore, we propose an enhanced classification model that combines features from different state-of-the-art classification models (DOM based and computer vision) using feature selection. We built two datasets for evaluating the efficacy of classification models in separately detecting external and internal layout failures using data from 72 responsive design Web applications. The proposed classification model reported the highest F1-score for detecting external layout failures (0.65) and internal layout failures (0.35), and these results reported significant differences compared to Browserbite and CrossCheck classification models. Nevertheless, the experiment showed a lower accuracy in the classification of internal layout failures and suggests the use of other image similarity metrics or deep learning models for increasing the efficacy of classification models.
Impact of Buyer's Ethical Environment on Supplier's Performance: A Trust-based Mediation Model

This research aims to analyze the impact of buyer ethical environment on supplier performance with mediating role of trust.For this purpose, 177 responses were collected by surveying employees of procurement departments of the manufacturing and service industry.The finding of this research shows that buyers' ethical environment has a strong positive impact on supplier performance, considering trust as a mediator.Similarly, the buyers' ethical environment has a positive impact on the trust in a buyer-supplier relationship.The findings of this research can help procurement managers and executives to enhance supplier performance in their procurement department by facilitating suppliers and strengthening their trust in buyer-supplier relationships.
The industries of the future – businesses durability in the digital era

Digital products are the most successful on the market, because they can be accessed from any corner of the world, they can be ordered and downloaded from any corner of the world, and the delivery time is measured in seconds. The demand for digital products will always be active, and the companies that develop and maintain such products will operate for a very long time, until the demand is exhausted. The digital products that will be developed must generate as much dopamine as possible for the user. The more actively will use digital products, the more data will be collected from the user in exchange for new strategies to keep the user active with the help of artificial intelligence. To protect the Big Data collected, we will call on cybersecurity to protect the servers where the data is stored. The aim of the research is to bring to light new opportunities for sustainable business design in a world that is constantly changing and to highlight the role of artificial intelligence in the success of companies. The research methods used were observational research. The most relevant results show that the demand for cybersecurity will increase by 2027 to a value of 346 billion US dollars. Digital products will continue to use artificial intelligence to process Big Data. Technology companies will operate for a long time, because humanity needs them.
MODERN TRENDS TO COMBAT AGAINST CYBERCRIME

Cybercrime is an important challenge faced by specialists in international and criminal law, because of the difficulty in determining their nature and elements, and the consequent criminal, civil, or international responsibility, as some states resort to them to have dominance over the armed conflict issue, or to pose political or military threats. The researcher indicated the difficulty to include cyber crimes in the current international legal framework due to their nature and the absence of a formal and final legal declaration agreed on. The researcher recommends the establishment of public-private sectors partnerships, at multi levels to fight cybercrime, as they are transnational crimes.
THE EFFECT OF USING FACEBOOK VOCAB-DEVELOPER ON IRAQI EFL LEARNERS' VOCABULARY DEVELOPMENT

The study aims to find out if there is any effect of using Facebook on students' performance in vocabulary development. Vocab-Developer (a Facebook webpage group created by the researcher to implement the experiment to the EG through uploading educational videos and audios, drills and other educational materials) group has been assigned to the experimental group to check the progress of lexical competence while they take the treatment. Whereas the control group students are presented to the traditional way in language teaching. A mixed-methods have been implemented including pretest-posttest design and a questionnaire. After applying the intervention, the researchers found statistically significant differences between the experimental group and the control group in their vocabulary development. This means that the students who took the treatment had better vocabulary development compared with those who were assigned to the traditional way of teaching. It can be inferred that using Facebook in the educational settings can serve as a beneficial and useful device for language learning and teaching.
AGRICULTURE 4.0: IMPACT AND POTENTIAL CHALLENGES OF BLOCKCHAIN TECHNOLOGY IN AGRICULTURE AND ITS MANAGEMENT

Information technology can be used to make the best use of things like water, fertilizer, and pesticides in agriculture. Farmers can make better decisions about how to use their resources, reduce waste, and have less of an effect on the environment by using sensor-based monitoring, data analysis, and precision farming techniques. Information technology can make the agricultural supply chain more open, so that consumers and other stakeholders can find out where agricultural products come from and how they are made. The authors looked at articles that had been published in journals before and gave up-to-date information about how blockchain technology could affect agriculture and how it is run. The authors did a descriptive narrative evaluation of how blockchain technology affects agricultural business. They looked at the challenges and benefits of blockchain technology in agriculture. The writing process took four months (between January 2023 and April 2023). We searched databases such as PubMed, Z-library, Publons, Medline, JSTOR, and Google Scholar and obtained original and review articles published in various journals, textbooks, and review papers. Conclusively, one of the primary challenges in agricultural business management is ensuring that farmers, especially those in remote or economically disadvantaged areas, have access to the necessary technology. This includes access to affordable hardware, software, and internet connectivity. Unequal access to technology can result in a digital divide, where some farmers are unable to take advantage of the benefits of information technology in agriculture. This review demonstrated that farmers and agribusinesses need to implement robust data privacy and security measures to protect their information from cyber threats and ensure compliance with relevant data protection regulations.&#x0D;
The SDLC Analysis for Implementation Document Management System at IPR Center of Universitas Jenderal Soedirman

The Document Management System (DMS), the Center for the Development of Intellectual Property Rights, is a web-based document management information system developed by the Center for Intellectual Property Development at Universitas Jenderal Soedirman. This system is used to archive documents digitally. However, because it did not work as intended by the user, the DMS Intellectual Property Rights Center did redesign both appearance and database relations. After the redesign process is complete, the SIMD Intellectual Property Rights Centre’s development results from the redesign need to be implemented in a production environment. For the implementation process to run well, it is necessary to analyze the factors that affect the deployment process with the implementation process in the widely used System Development Life Cycle (SDLC) model. By mapping these factors with the characteristics, advantages, and disadvantages of each SDLC implementation process, the V-shaped model's deployment process is more effective and efficient in its execution in a production environment. The results show that the results of this redesign procedure can solve the problems that have occurred so far.
INTERNET FINANCIAL CRIME SECURITY PREVENTION AND CRIMINAL LAW REGULATION OPTIMIZATION PATH

Since the advent of the Internet, Internet and finance are becoming more and more closely integrated. In 2014, the banking industry paid around $65 billion in regulatory penalties, with misbehavior and anti-financial crime failures acting as key prosecution justifications. Many financial institutions are finding that it is difficult to properly handle growing requirements with their current processes and infrastructure, leading to significant increases in associated operational expenses. Recent improvements in data analytics, which allow a speedier analysis of larger, more thorough, and more diversified data sets, appear to have the potential to ease some of the key pain points in this context. This paper investigates the rise of Big Data in this sector, concentrating on use cases where advanced analytics is presently being applied, as well as its long-term potential.