Reviewerly/exHarmony huggingface dataset:
PERANCANGAN MEDIA INTERAKTIF PERUBAHAN ENERGI SISWA SD MENGGUNAKAN ADOBE FLASH CS3

The teaching and learning process during the pandemic is where schools must continue to deliver material even though it is online because students study at home. The teacher's learning process still uses a conventional learning system, which is dominated by text and reading, the delivery of material like this causes students to be less enthusiastic and difficult to understand the material being taught. Multimedia that supports interactive-based learning is currently growing, so it can be an option for schools to build interactive learning media. Multimedia can create dynamic and interactive presentations by combining text, graphics, animation, audio, and video images. The research aims to produce interactive multimedia learning energy changes. The method used in conducting this research is a field study with interview and observation data collection techniques. The results are in the form of interactive animation applications for learning energy changes which are expected to increase understanding of the material as well as facilitate the teaching and learning process during the online learning period.
A REVIEW ARTICLE: USE OF SENTIMENT ANALYSIS IN SOCIAL MEDIA

As a result of the growth of online social networking platforms and applications, a sizeable amount of user-generated text content is created daily in the form of comments, reviews, and short text messages. Users can write messages, share them, and add images and videos to social networking sites like Twitter, Facebook, and others. Consequently, a significant volume of sentiment-rich data is generated. Sentiment analysis then comes into play in this scenario, which evaluates opinions as positive, neutral, or negative by extracting, recognizing, or representing them from various sources, including social media, news, articles, and blogs. This study aims to analyze the results from different sentiment analysis models and technologies that combine natural language processing. Case studies of various industries that can benefit or have been benefiting from sentiment analysis are also discussed to provide an approachable pathway for anyone who wishes to go more deeply into this field. For example, the business world has used it to learn what customers think of a certain company or brand. The impact of profanity on how readers interpret tweets and other social media messages are studied in sociology and psychology. Political scientists are trying to anticipate election results based on tweets to evaluate answers, among other things, and to look for trends, ideological bias, and opinions. Researchers have previously evaluated numerous models using well-known techniques like Naive Bayes, support vector machines, etc., and the findings have been compared with promising outcomes.
Investigating Problems Encountered By The Test Takers During Taking Toefl Test

One of standardized test that measure students’ proficiency level in English which is called as Test of English as Foreign Language (TOEFL) has been used worldwide by more than 9.000 colleges, universities and agencies in more than hundreds countries in the world. Nowadays, English proficiency test is taken not only on purpose of pursuing study abroad but also as a prerequisite to complete college, especially in institutions. Further, it is also used in the admissions process of applicants to get a job especially in companies where English is used to communicate. However, to pass the TOFL test is not an easy task and even there are many test taker failed the test though they had spent months preparing for the test. There are many problem happened during the test that caused the test taker into failure. This research aimed to investigate problems that occur during the test. This study used descriptive qualitative design and the subjects were ten college students who had taken TOEFL prediction test in the Language Center of Mandalika University of Education (UNDIKMA). The instrument used in this study was an interview which then the result of interview was analyzed in three steps, i.e. data condensation, display, and conclusion. The result of the study showed that most of the test taker failed and made a bad score due to some problems, i.e. less practice, lack of vocabulary, bad time management, feeling nervous, etc. It was noted that those who had minimum problem scored higher than those who had various problem.
SIGN LANGUAGE RECOGNITION USING LSTM DEEP LEARNING MODEL

Speech impaired people use hand signs and gestures to communicate. The problem is translator needs every time to translate sign language. Artificial Intelligence capture hand expression with the help of camera show us what a person says and result shown in the text format. In the starting stage we provide the data for sign language for better result with good accuracy and testing this model. Various deepmachine learning algorithms are applied on the datasets, including Long Short-Term Memory (LSTM) RNN.
DESPECKLING OF MEDICAL IMAGES BASED ON GAUSSIAN MEMBERSHIP FUNCTION AND GRUNWALD-LETNIKNOV DERIVATIVE

Noise removal of Ultrasound (US), Computerized Tomography (CT) and Magnetic Resonance (MR) images are really challenging task in medical point of view. As the nature of the tumor, it can present any part of these images with any shape, size and contrast that creates the de-noising process further complicated. To overcome these issues, the proposed work presents an efficient Filter for image classification and de-noising based on Gaussian Membership Function and GrunwaldDerivative. The performance of the proposed filtering method is compared with Two Step Algorithm (TSA) which classifies the image region into three different regions and utilized suitable filters on these regions to partition the unwanted noise from the classified pixels. Simulation result shows the performance of proposed filtering process.
AN ARTIFICIAL INTELLIGENCE-BASED SPEAKING SYSTEM FOR DUMB PEOPLE

For deaf-mute people all around the world, Gestures are the main mode of communication for DeafMute people worldwide. In this gesture-based voice system, machine learning presents a real-time vision-based system for monitoring hand finger gestures. It was developed in Python using Raspberry Pi along with a camera module, which is compatible with the Open CV library for computer vision. The Raspberry Pi includes an image processing technique that monitors the fingers of the hand using the extracted attributes. The main purpose of a gesture based speaking system is to develop control communication between humans and computers. This leads to a system that can recognize and monitor known objects and has surveillance and application capabilities. The major goal of the suggested work was to allow the system to function properly. The main objective is to enable the system to recognize and monitor certain properties of objects specified by the Raspberry Pi along with camera module using an appropriate image processing technique. The Open CV library's feature extraction technique of the Open CV library for Python programming runs on Raspberry Pi using an external camera. A gesture based speaking system using machine learning provides a new, intuitive, and simple way to communicate with computers that are more human-like.
Pembelajaran Berbasis Audio Visual pada Materi Teks Laporan Hasil Observasi Kelas X SMA Budi Agung Medan

This study examines Indonesian language learning in class X SMA Budi Agung Medan, focusing on the development of audiovisual-based learning media using Macromedia Flash software. The 2013 curriculum necessitates adaptable learning media to facilitate students' independent learning with teachers as facilitators. However, the current text-based learning approach is limited. The research used the research and development (R&amp;D) method with the ADDIE development model. Data were collected from media and material experts, as well as lecturers and teachers in Indonesian language studies and learning media. The results showed that the audiovisual-based learning media received a feasibility value of 84.0% (appropriate) for media and 81.0% (adequate) for material. The teacher's response to the media was 80.76%, while the student's response was 80.2%. This study highlights the importance of implementing effective learning media in line with the 2013 curriculum to enhance the learning experience.
Pengembangan Bahan Ajar Berbasis Media Interaktif Materi Teks Ceramah Kelas XI

&#x0D; &#x0D; &#x0D; &#x0D; This study aimed to develop and test the feasibility and determine the effectiveness of interactive media-based on teaching materials for class XI. The population from class XI SMAS Bani Adam Mabar as 79 students and the sample as 21 students. This study used development research that ausually called R&amp;D (Research and Development) with 4D model. The procedure used four stages: (1) Define, (2) Design, (3) Develop, (4) Disseminate. The results indicated that Interactive Media-Based Teaching Materials for Class XI are very suitable in learning by previously through a validation test of 2 material experts and 2 media experts. The result of material expert I is 77%, material expert II is 89%, media expert I is 85% and media expert II is 75%. Furthermore, interactive media-based teaching materials for class XI were tested on 1 teacher of Indonesian language studies and 21 students of class XI in SMAS BANI ADAM Mabar. For trials on teachers in the field of study, the results were 83% or very good criteria, and for trials on students, the results were 92% or very good criteria. In addition, after the effectiveness test was carried out by providing evaluations to students, it was obtained that the students' scores reached the Minimum Completeness Criteria (KKM). Then it can be concluded that interactive media-based teaching materials for class XI are very feasible and effective to be used in learning.&#x0D; &#x0D; &#x0D; &#x0D;
GLUformer: An Efficient Transformer Network for Image Denoising

In this article, we introduce GLUformer, an efficient image denoising network based on Transformer. The architecture of our network is a layered encoder-decoder. In order to further reduce the amount of computation and lower the computational cost, we propose a new Global-Local Window Transformer block (GLWin). Different from the traditional global self-attention, it performs the calculation of non-overlapping window self-attention, this can effectively reduce the computational complexity of the feature map. At the same time, it combines local window division and global window division, which can effectively capture the context relationship of the image color blocks. In addition, we add dynamic position bias (DPB) to the (GLWin) block, which address the issue of limited input image size. With the support of these two designs, GLUformer shows an excellent image noise reduction effect. Our network also achieves good results on the SIDD dataset with a relatively small amount of computation.
A Time-Aware Graph Attention Network for Temporal Knowledge Graphs Reasoning

Temporal Knowledge Graphs (TKGs) have been widely used in various domains to describe dynamic facts using quadruple information (subject, relation, object, timestamp). The TKG reasoning task aims to predict missing entity, i.e., “?” in the quadruple (entity, relation, ?, future time) from known facts. Although existing temporal knowledge graph reasoning models consider the quadruple information of each timestamp separately, they fail to fully exploit the temporal information as well as the hidden information in the known graph structure. To address the above issue, we propose an end-to-end encoder-decoder framework that incorporates temporal information and two-hop neighbor information into the entity embedding representation. Specifically, we design a time-aware graph attention network (TA-GAT) as an encoder. Unlike existing models that deal with each quadruple independently, we integrate two-hop neighbor nodes into TA-GAT to capture the hidden properties of the target entity domain. To further improve our model, we enhance the convolutional neural network-based knowledge graph embedding model ConvTKB as a decoder. Experimental results show that our model TA-GAT outperforms the state-of-the-art models on three datasets, i.e., WIKI, YAGO, and ICEWS14.
Development of a Mobile-Based Student Grade Processing Application Using the Waterfall Method

One of the public elementary schools in Medan is SDN 064017. At SDN 064017, the procedure for processing student grade data is not yet computerized. Gradebooks are used to track and process student grade information. There are still certain problems that arise with this method. SDN 064017 requires a lot of time and effort to process and find information on student grades. The purpose of the author's research is to develop a mobile-based application that will simplify and speed up SDN 064017 in processing and searching for student grade data. The system development method used by the author is the waterfall method, consisting of requirements analysis, system design, implementation, testing, deployment, and maintenance stages, while the system testing method uses the black box testing method. In the process of developing a mobile-based application, the author uses the Kodular framework and the Airtable database. With the information system, it is hoped that it can help SDN 064017 in processing and searching student grade data at SDN 064017 to be more effective and efficient through an Android mobile.
Comparative Study of Robot Framework and Cucumber as BDD Automated Testing Tools

Automation testing is much more efficient and accurate, the script is easy to document, and update compared to manual testing. Testing a website may necessitate time and effort to learn the tools to be used. Cucumber and Robot Framework are well-known open-source frameworks, according to Stack Overflow and GitHub. Cucumber and Robot Framework are known on an international scale, especially Robot Framework, which is often used by large companies. Each uses the Java and Python languages, which both support BDD. The comparative efforts of the two tools aim to help testers compare and determine automated testing tools in the BisOps Logee Port Web Admin case study based on the effectiveness and efficiency of the tools and create specific test cases as test documentation so that testers do not need to spend time analyzing both. Because this research involves evaluation and comparison, several criteria were chosen to support the evaluation process, namely functionality, reliability, usability, performance efficiency, and portability. The results of this study show that both tools can be recommended for novice QA's who want to learn the basics of automation by implementing BDD. Meanwhile, for QA's who have done automation before and want to do more in-depth configuration and reporting, it is recommended to use Robot Framework because the syntax is short, has lots of keywords that make it easier for testers, and can make the testing system shorter but more specific.
Gamification to Study Machine Learning using Octalysis Framework

Machine learning is an area of study that enables computers to learn and improve their performance without explicit programming. Its primary application is assisting humans in processing vast amounts of data. Machine learning is a crucial area of study, and to assist students in learning about it, a gamification application has been developed using the Android platform. The aim of this research is to not only provide knowledge to students but also make the application interesting by using the octalysis framework. The application's level of acceptance will be tested on students at Multimedia Nusantara University who are taking machine learning courses. The Unified Theory of Acceptance and Use of Technology Model (UTAUT) method will be used to evaluate the application, which received an average score of 86.77%. This score indicates that students strongly agreed that the gamification approach using the octalysis framework and Android platform for machine learning was well-received.
E-Commerce System for Media Group Cooperative

E-Commerce is a way to shop online where it is easier for us to process transactions between sellers and buyers without having to face to face, at this time we are required to reduce face-to-face to reduce the spread of covid which is high. Based on these problems created a website that can make sales online. The method used in the system is the SDLC waterfall method to find suitable and appropriate features. The tools used are visual studio code, and Heidi SQL. The result of this research is the website is made using PHP, JavaScript, Bootstrap and CSS for the frontend and the backend of the website. The website created can help make sales online and reduce sales data loss in cooperatives.
Analyzing Level of International Humanitarian Law Knowledge and its Compliance Through Military Simulation Game

International humanitarian law in armed conflicts, the majority of whose contents originate from the results of the Geneva Convention, is the law used to protect human rights during an armed conflict. Based on research conducted by the International Red Cross Committee, video games that are now popular among the public, especially in the military genre, often ignore or contradict aspects of international law. This research was conducted to determine the knowledge of international law in armed conflict and its relationship to the level of compliance through military simulation video game scenarios. The scenario-based framework is a method used to develop game scenarios. The scenario was developed using an ARMA 3 video game editor and created to describe a situation of armed conflict where the respondent will take action whose results reflect the respondent's level of compliance with international law. Each respondent obtained two types of scores, the first is knowledge scores obtained from filling out questionnaires, and the second is compliance scores obtained from the results of running scenarios in the game. The score is divided into 12 parameters relating to aspects of international law in armed conflict. After the two types of scores are obtained, an analysis is carried out to determine whether the respondent's knowledge level influences the compliance level. The study's results showed that the respondent's knowledge and compliance levels were very high. The results of the comparative analysis show that only ten parameters have a level of knowledge that influences the level of compliance.
Implementing the Chaotic Permutation Multicircular Cryptography Technique using Asymmetric Key

In digital computing, cryptographic methods considers performance in both speed and security. This study aims to explore and improve a permutation-based symmetric chaotic cryptography technique called Chaotic Permutation Multicircular (CPMC). In this study, a method is proposed to implement asymmetric key system from CPMC technique by generating a reverser key for reverting the permutation result of CPMC encryption back to its original arrangement using the same function as encryption. The reverser key alongside the CPMC key act as encryption and decryption key pair. The pair key generation and cryptographic function utilizes the encryption function of CPMC technique dubbed CPMC Shrinking algorithm. Asymmetric implementation can simplify CPMC technique by also using CPMC Shrinking algorithm for decryption, therefore enabling it as a single function for encryption and decryption. The asymmetric single function cryptography test show improvement in speed from faster cryptographic speed in decryption compared to initial implementation by average of 75.87%
Automatic Portal Access Application Using Static Qr Code Reading

This study is a study that aims to determine the results of the automatic portal access application using a static QR Code reading based on the results of the ISO 25010 testing standard and to find out the results of using an automatic portal access application using a QR Code reading. The development model used in this research is the Rapid Application Development (RAD) model and the application quality test is based on the ISO 25010 quality standard. Data were collected using documentation and observation techniques. The instrument and system were validated by two system experts. Data were analyzed using descriptive statistical analysis techniques. Based on the test results using the ISO 25010 quality standard, the automatic parking application using QR Code reading has met the standards where: a) testing the functionality suitability aspect Testing the application is carried out by involving 2 (two) expert validators who are experienced in the field of application programming, the percentage is obtained in the category Very Good and has met the functionality suitability aspect; b) testing the performance efficiency aspect of the application can run well without experiencing a memory leak which results in a force close and launch fail so that the application is said to be successful and has met the performance efficiency aspect; c) Testing the maintainability aspect From the test results on the maintainability aspect, it shows that the maintainability aspect test has met three aspects of the test, including instrumentation, consistency, and simplicity, so the results of the maintainability aspect test can be said to meet the maintainability standard.
Learning Activities of Indonesian Language Content Using The Project Based Learning Model

The purpose of this study was to determine teacher and student activities as well as to improve student learning outcomes. This research used Classroom Action Research (CAR). This research was conducted in two cycles. This research was conducted in class IV-A of SDN Melayu 2 with 22 students. The data were analyzed qualitatively, namely teacher and student activities, and quantitatively, namely student learning outcomes. The data generated from the instrument sheet, observation sheets and learning outcomes tests were then analyzed using descriptive techniques and described in the form of tables and graphs, then students understood using the criteria for each indicator of the achievement of teacher activities and activities, as well as the achievement of mastery learning and individually classic. The study's findings showed that the teacher's activity in cycle 1 obtained a score of 19 "Good" criteria, increasing in cycle 2 to 22 with "Very Good" criteria. Student activity also increased in cycle 1, obtaining 55% with the criteria of "Enough Active" and increased in cycle 2 to 86% with the "Very Active" criteria. Likewise, student learning outcomes in cycle 1 obtained 64% of students who completed and increased in cycle 2 to 86% of students who completed. Based on the results of this study, there was an increase in teacher activities, students’ activities, and learning outcomes.
Kahoot: Let’s Have Fun in English Class with It!

&#x0D; Motivation is required to have satisfying learning echievement in English because it drives students to study seriously without being forced. To improve students’ learning motivation, English teachers can integrate the use of technology in their teaching. One of applications which is considered to improve students’ leaning motivation is Kahoot, a game-based application. This research aimed to investigate learning motivation of students of SMA N 1 Belitang after experiencing Kahoot in learning English and English teacher’s perception toward the use of Kahoot. Questionnaire was administered to 43 second grade students and interview was done with one English teacher who used it in English class. It turned out that almost all students gave positive responses on the questionnaire and after being analyzed, students’ learning motivation was categorized into high category. Moreover, the English teacher claimed that students showed more interest in English after being introduced to Kahoot and their English scores were improved. The students’ improvement in motivation and achievement were resulted from competitive atmosphere on games and interesting display on Kahoot so that they argued that learning English is a fun activity.