Reviewerly/exHarmony huggingface dataset:
LEARNING ENGLISH VOCABULARY USING KAMPUNG INGGRIS SOCIAL MEDIA ACCOUNT

Currently learning can be done vocabulary can use social media. Social media that are widely used by the younger generation today are YouTube and Instagram, there are lots of YouTube and Instagram accounts for learning English, one of which is Kampung Inggris. Students who want to learn English in an easy and accessible way can view content on social media that has been presented by Kampung Inggris. This study aims to determine the use of social media YouTube and Instagram in Kampung Inggris as a method of learning vocabulary at SMPN 06 Bekasi. This study uses a qualitative method. In this study, interviews with English teachers will be conducted to find out more about learning English using Instagram and YouTube social media from Kampung Inggris. Questionnaires are given to students regarding the use of Instagram and YouTube social media during vocabulary learning at school, observations are made by giving some questions to find out which social media is more often used by students and documentation of student learning activities. The results of this study found that 66,66% of students prefer learning through YouTube than Instagram. Social media YouTube and Instagram also provide positive benefits for students because they can increase learning motivation and increase students' vocabulary.
THE IMPACT OF KNOWLEDGE MANAGEMENT PROCESS ON INSTITUTIONAL EXCELLENCE IN THE PUBLIC SECTOR KING FAISAL SPECIALIST HOSPITAL AND RESEARCH CENTER AS A CASE STUDY

This study aimed to identify the impact of knowledge management processes on institutional excellence at King Faisal Specialist Hospital and Research Center, and to identify the level of knowledge management processes, and institutional excellence at King Faisal Specialist Hospital and Research Center.to achieve the objectives of the study, the researcher used the descriptive analytical approach, and developed a questionnaire consisting of (30) items, and the study sample consisted of (288) workers within the following job titles (director, assistant director, doctor, nurse, technician, administrative), which were taken in the sample method. Facilitator as a representative sample of the study population by applying the questionnaire in electronic form at King Faisal Specialist Hospital and Research Center, and after analyzing the data using appropriate statistical methods. the results showed that the general arithmetic means of the level of knowledge management operations in King Faisal Specialist Hospital and Research Center came with a high evaluation, and the level of institutional excellence was also highly evaluated, And a statistically significant effect at the level of significance (a ≤ 0.05) for the dimensions of Knowledge Management on Institutional Excellence at King Faisal Specialist Hospital and Research Center.
IMPROVING LEARNING OUTCOMES OF MATERIALS ON THE DANGERS OF SMOKING FOR HEALTH THROUGH AUDIO VISUAL MEDIA IN CLASS V STUDENTS OF SD NEGERI 101776 SAMPALI

This study aims to determine the improvement of learning outcomes of hidden materials for health through audio visual media in fifth grade students of SD Negeri 101776 Sampali. The research method used is Classroom Action Research. The research subjects were fifth grade students of SD Negeri 101776 Sampali with a total of 28 students. Based on the initial test of learning outcomes of ability in the dangers of smoking for health, the percentage of students (14%) is 4 students out of 28 students. After the research, the learning outcomes test in cycle I and cycle II was carried out. And then in the second cycle of learning outcomes test, students experienced an increase in learning outcomes, namely 25 students (89%) had achieved learning mastery, while 3 students (11%) had not achieved learning mastery. Based on the results of data analysis, it can be obtained that audio-visual media can influence and improve learning outcomes of smoking material for health in fifth grade students of SD Negeri 101776 Sampali.Keywords: Dangers of Smoking, Learning Outcomes, Audio Visual Media
TIDOAA — A Temporal Anti-aliasing Method with Immutable Dynamic Objects

The main purpose of this investigation is to use information from previous frames for partial synthesis of the new one. Algorithms utilizing already calculated information have become an integral part of many interactive applications in recent years, and using of such methods allows reduces the computational load on the GPU without significantly degrading the image quality. Despite its popularity, there are still serious unresolved issues that affect image quality in many scenarios. Especially acute are the issues of artifacts and frame distortions. This paper discuss ways of counting and using information from previous frames used in image rendering applications, and proposes a new algorithm which combine best traits of the previous ones.
Pengembangan E- Comic Education pada Mata Pelajaran Ilmu Pengetahuan Alam Materi Gaya dan Manfaatnya

The purpose of the study was to determine the need for developing e- comic education learning media to improve cognitive learning outcomes for fourth grade students of MI NU Tsamrotul Wathon. The type of this research is Research and Development with ADDIE model. Data collection techniques used questionnaires, and tests. The limited scale test was carried out with 10 students and the broad scale test was carried out with 30 students. The results showed that: the results of the validation of the eligibility criteria were based on the validation media experts, material experts and practitioners. Eligibility criteria for displaying writing are 62.5% (fair enough), image eligibility 72.5% (fair enough), e-comic education media function is 91.6% (very feasible), e-comic education media benefits are 87.5%. The eligibility criteria for the content aspect are 83.92% (very feasible), the feasibility on the construction aspect is 68.75% (adequate) and the feasibility of the language aspect is 60% (fair enough). The results of the development of e-comic education media are very effective in influencing students cognitive learning outcomes as indicated by the increase in cognitive learning outcomes with α &lt; 0,05 its mean 0.00 &lt; 0.05. The gain test of 0.467 is in the medium category.
Text tasks in mathematics as a means of financial literacy improvement in primary school

The modern educational process, the purpose of which is high learning efficiency, requires new methodological approaches to acquire deep mathematical knowledge. Mathematical education contributes to the development of the basic types of students thinking. An urgent methodological issue is learning to solve text problems in mathematics, since this section causes difficulties for a large percentage of students in grades 59. In this paper, the value of learning to solve text problems is considered on the example of questions of financial mathematics. To date, the issues of financial literacy are included in the content of an exemplary program in mathematics, examination papers, and are also necessary for the successful development of the students personality. The paper analyzes the methodology for teaching the solution of text problems of a financial plot on the example of conducting a series of business games in the classroom. The approbation of the results of the study was carried out on the basis of Municipal Autonomous Educational Institution Lyceum № 5 in Orenburg. It showed that the solution of plot text problems has a positive effect on expanding the general outlook of students. The methodology for conducting business games increases students activity in solving problems, increases the effectiveness of learning as well as expands the prospects for pedagogical activity.
Game of Definitions—Do the NIST Definitions of Cloud Service Models Need an Update? A Remark

Cloud computing captured the world by storm as a cheaper, faster and safer alternative to an on-premises computing environment. Consequently, several organizations started favouring cloud computing service models over traditional on-premises hosting to offer their products or services over the Internet. As cloud computing gained popularity in the early 2000s, the National Institute of Standards and Technologies (NIST) decided to define it in 2011 formally. Since then, almost a decade has passed and cloud technology has progressed by leaps and bounds. As a result of the commercial progress that cloud computing has made as a technological offering, delivery methodologies have evolved and cloud service providers nowadays are using new service models that are not falling in the traditional service brackets of Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) as defined by the NIST. Serverless and containers are examples of such service models. Consequently, cloud service providers developed novel terminologies like Database as a Service and Storage as a Service to clearly define their offerings. After researching and studying various examples and models, we feel the times have changed. Since the NIST definitions have not been updated since 2011, a lot of confusion has emerged among services that hinder compatibility. In this paper, we put forth the argument to update the definition of cloud service models introduced by the NIST in 2011. The argument is supported by detailing two new service methodologies: serverless and containers and explaining how these do not fit in the buckets defined by the NIST in 2011.
A REVIEW OF KNOWLEDGE GRAPH AND GRAPH NEURAL NETWORK APPLICATION

Many learning activities include working with graph data, which offers a wealth of relational information between parts.Modeling physical systems, learning molecular fingerprints, predicting protein interfaces, and diagnosing illnesses all need the use of a model that can learn from graph inputs.In other fields, such as learning from non-structural data such as texts and images, reasoning on extracted structures (such as phrase dependency trees and image scene graphs) is a major topic that requires graph reasoning models.Graph neural networks (GNNs) are neural models that use message transmission between graph nodes to represent graph dependency.Variants of GNNs have recently showed ground-breaking performance on a variety of deep learning tasks.This paper represents a review of the literature on Knowledge Graphs and Graph Neural Networks, with a particular focus on Graph Embeddings and Graph Neural Networks applications as a powerful tool for organizing structured data and making sense of unstructured data, which can be applied to a variety of real-world problems.
Development of an Internet-Based Information/DataResource Platform during the COVID-19 Pandemic Using Hierarchical Clustering

There is heavy usage of Internet-based information resource platformsdue to the COVID-19 pandemic. If it can present the search results as a list of groupsof related terms and context, that would be ideal. An additional enhancement would be to display information in the search results in a classified manner. Therefore, the research is proposing an effective and efficient information retrieval system. The methodology adopted follows the conventional Information Retrieval (IR) system design except that Cosine similarity and hierarchical clustering were introduced for search result ranking. The Average Precision of the proposed system was compared with that of flat clustering such as K-means. The result of the evaluation shows that hierarchical clustering improved in precision, being10% better than flat clustering result retrieval result. This led to greater usability, userexperience,and efficiency of the system
A Novel Chaotic Image Encryption Algorithm Based on Coordinate Descent and SHA-256

In recent years, chaotic image encryption algorithms with key and plaintext association have been developed, which are essentially similar to a one-time pad at a time because each encryption requires the transmission of the key. However, some existing schemes cannot uniquely map the seed key to the initial value of the chaotic system, which leads to the reduction of the key space of the encryption system. In addition, some schemes use the same key to encrypt the same image, which does not conform to the one-time pad strategy. This paper solves these problems from two aspects. On the one hand, random pixels are inserted into a plain image and then a hash value is generated using SHA-256. Different seed keys can be obtained even if the same image is encrypted. On the other hand, the Sequential Expansion Algorithm (SEA) and Feedback Iterative Piece-Wise Linear Chaotic Mapping (FI-PWLCM) are proposed to realize the one-to-one correspondence between the seed key and the encrypted key stream. SEA can quickly generate seed key sensitive and random sequences. FI-PWLCM achieves one-to-one correspondence with the seed key through feedback iteration with more control parameters. The mapping not only has the rapidity of PWLCM, but also can produce more complex chaotic sequences. Besides, this paper proposes a Segmented Coordinate Descent (SCD) method for histogram statistical optimization of images to improve the ability of cryptosystems against statistical attacks. Experiments and security analysis show that the algorithm can resist chosen-plaintext (chosen-ciphertext) attacks, brute force attacks, statistical attacks and so on. Compared with most current algorithms, it achieves the best performance in the statistical properties of histogram and entropy.
Meningkatkan Hasil Belajar Siswa pada Mata Pelajaran IPA Menggunakan Media Pernafasan Paru-Paru

The purpose of this study was to improve students' learning outcomes in science subjects grade VI SD Negeri 02 Ujan Mas by using lung respiratory media. This research uses a type of Class Action (PTK) research conducted in 2 cycles, each cycle consists of 4 stages, namely the stage of planning, implementation of actions, observation and reflection. This research subsection numbered 19 people. Data collection techniques are carried out through tests, and observations. The results showed before learning using respiratory media (Pre-Test) learning results can be categorized as medium with a high category of 2 people, a moderate category of 15 people, and a low category of 2 people. Learning results when using respiratory media (Pre-Test) can be categorized as moderate or sufficient, this is evidenced by the results of learning in a high category of 0 people, a moderate category of 19 people and a low category of 0 people. The results of the analysis showed no significant influence of lung respiratory media on the results of science study grade VI SD N 02 this is evidenced by the results of rxy value data known correlation between variable X and variable Y of 0.061279 located at intervals of 0.00-0.20. In conclusion, there is no significant influence of lung respiratory media on the learning outcomes of science grade VI SD N 02 Ujan Mas. &#x0D; &#x0D; Keywords: Lung Respiratory Media, Learning Outcomes, Science Lessons
Review Pemanfataan Data Electroencephalogram (EEG) dengan metode Convolution Neural Network

Electroencephalogram (EEG) is a brain data signal that is captured by sensors. Many studies have used EEG to be used as a decision maker or classifying. What classification has been used most frequently in existing studies over the last 5 years? These are the questions that will be answered in this research. In addition to these questions, another question that will be answered is what is the most popular method used in processing EEG data? The final question in research is the recent development of EEG and CNN research. The results of these answers are the most popular research using the CNN method as a classification method, the application of the field of Human-computer InterfacesKeywords: Electroencephalogram, Convolution Neural Network.
MP-KMeans: K-Means with Missing Pattern for Data of Missing Not at Random

K-Means is one of the most popular clustering algorithm. It aims to minimize the sum of pair-wise distance within a cluster. It has been widely used in data analysis, image recognition and many other fields. However, traditional K-Means cannot handle missing values, which greatly limits its application scenarios. Missing values are ubiquitous in the real world due to sensor failure, high cost, and privacy protection. The appearance of missing values leads to useful information lost in the information system, and makes it difficult to perform data mining. Currently, improvements of K-Means for missing values generally based on data completion and partial distance strategy. Above methods achieve satisfied performance with random missing values, but they will fail when data is missing not at random (MNAR). Considering the effect of missing mechanism, this paper proposes an improved method of traditional K-Means for data of missing not at random, which integrating missing pattern in the distance measurement to assist clustering process. The experiment results on public datasets show that the proposed method outperforms data completion-based K-Means and partial distance-based K-Means.
ANALISIS DAMPAK KEBIJAKAN PEMBERLAKUAN PEMBATASAN KEGIATAN MASYARAKAT (PPKM) BAGI PELAKU USAHA BISNIS COFFEE SHOP DI KABUPATEN REJANG LEBONG

Based on the output of "Test Statistics", it is known that Asymp. Sig (2-tailed) feasible 0.012 is smaller than &lt;0.05, it can be said that there is an average difference between before and before the PPKM Impact, then the key H0 is rejected and H1 is accepted. In the statistical table, the calculated Z value is -2.527, while the Z table value with an alpha of 5% or 0.05 is 1.96. While the Asymp value. Sig (2 tailed) was obtained 0.012 because Z count &lt; Z table, namely -2.527 &lt; 1.96 or a significance value of 0.012 &lt;0.05 according to the statistical test used, then H0 was rejected and H1 was accepted.&#x0D; Based on the output of "Test Statistics", it is known that Asymp. Sig (2-tailed) is feasible 0.011, smaller than &lt;0.05, it can be said that there is an average difference that occurs at the Business Coffee Shop between before and before, it can be said that H0 is rejected and H1 is accepted. In the statistical table, the calculated Z value is -2.539, while the Z table value with an alpha of 5% or 0.05 is 1.96. While the Asymp value. Sig (2 tailed) is obtained 0.01 because Z count &lt; Z table is -2.539 &lt; 1.96 or&#x0D; &#x0D;
Development of Moodle-Based E-Learning at LKP TIKOM

This research is a research development. It said development research because this study concluded a product that is research using the Research and Development method. This research is directed to develop E-learning media based on a Website using Moodle platform with additional Video Conference features. This research uses the Waterfall method. This Waterfall method approaches systematically and sequentially in building software. Product trials are carried out in two ways, theoretically and empirically. Theoretically, an attempt was conducted on the feasibility test for using E-learning with the assessment of media experts and assessors/students while empirically testing the product using the black box. That the development of website-based E-learning uses the Moodle platform with additional video conference features (1) Attracting course and training participants and (2) Assisting the Instructor's task in increasing competency at LKP TIKOM
IMPLEMENTASI SUPPORT VECTOR MACHINE (SVM) DALAM MEMPREDIKSI JUMLAH PENYAKIT DEMAM BERDARAH (STUDI KASUS PENYEBARAN DEMAM BERDARAH DI SINGAPURA)

Dengue Hemorrhagic Fever (DHF) is an infectious disease caused by dengue virus infection and is transmitted through the bite of female mosquito species Aedes aegypti and Aedes albopictus. Environmental factors are one of the causes of the high prevalence of dengue fever, including the layout of buildings, water reservoirs, indentations in the soil, temperature and other things that can help the Aedes mosquito life cycle take place. The purpose of this study is to predict the spread of dengue disease using the SVM (Support Vector Machine) method with rainfall data in Singapore from 2014 to 2018, weather data and pain data, comparing this study with previous research by Adeline Ong in 2014 entitled " Predicting Dengue Cases in Singapore”, as well as knowing the results of predicting the distribution of DHF using the SVM method in the form of variance values (R2) with linear, gaussian and polynomial kernels. The results of the experiment found that the lowest error value was shown by the linear kernel with an error rate of 35.15%, with a variance value of 64.85%.
Model Pembelajaran Berbasis Masalah (PBL) Pada Mata Pelajaran Bahasa Jepang (Penelitian dan Pengembangan di Kelas IX SMAN 75 Jakarta)

In the 21st century, the role of education is becoming increasingly important in preparing the next generation who have the skills to learn and innovate, the skills to use technology and information media so that the learning model needed is an active, innovative, creative, effective. One of the learning models that are considered appropriate to meet that educational objectives is the use of problem based learning (PBL) learning models in classroom teaching.The purpose of this study was to determine the Japanese language skills of class XI students of SMAN 75 Jakarta and whether the learning model to be developed for Japanese subjects in class XI of SMAN 75 Jakarta was effective compared to the learning model carried out before the development. The research method is student-based learning with the research design being Pre-Experimental Design with the One-Group Pretest-Posttest Design model. The study included 39 students from SMAN 75 Jakarta's class XI. Data analysis in the study was carried out in several stages, namely the validity test, reliability test, normality test, and t test. The findings revealed that there was a difference after using problem-based learning model on Japanese language abilities acquisition when compared to before treatment. And the problem-based learning model is effective in developing Japanese language abilities.
ANALISIS FAKTOR PENYEBAB DAN STRATEGI PENGENDALIAAN KEKERINGAN DANAU AYAMARU KABUPATEN MAYBRAT

Drought is a natural event and attacks slowly, such as the drought that occurred in Lake Ayamaru which has had a very wide adverse impact on people in Maybrat Regency, because the function of the lake has been lost in recent years. Considering that drought is a recurring event, it is necessary to know the causes of drought and control strategies, so that the aim of this study is to conduct an analysis to determine the factors causing drought in Ayamaru Lake and the efforts made to control drought, so that it can be used as a reference to minimize the drought that occurs. The research method used is descriptive qualitative and quantitative research. The data sources used are primary and secondary data. Data collection techniques using questionnaires, in-depth interviews (indepth interview), documentation and direct observation. The data used, namely, the data that was filtered through the results of the questionnaire, was processed and analyzed by the qualitative-quantitative descriptive method using the cross tabulation approach (crosstabulation). The data collected is categorized using a Likert scale. This shows that the cause of the dryness of Lake Ayamaru is due to Rock properties factors, Rainfall factor, Topographic factors, Land use factors; and control strategies implemented to overcome drought, namely; The vegetative method is carried out with reforestation and agroforestry. The mechanical method is by constructing a sediment control building (check dam) and making a triangular terrace on the slope area.