Reviewerly/exHarmony huggingface dataset:
Hubungan Motivasi Belajar dengan Hasil Belajar Siswa pada Pembelajaran Tematik di Kelas IV Sekolah Dasar

The research aim to know there is or no correlation motivation in learning with student learning outcomes in thematic learning of four grade of primary school on cluster two in subdistrict Enam Lingkung regency Padang Pariaman. This type of research is quantitative research with correlation research methods. The amount of sample is 26 students, four grade of primary school 16 Enam Lingkung. The result of the research there is positive correlation an significant students motivation in learning with student learning outcomes in thematic learning of four grade of primary school on cluster two in subdistrict Enam Lingkung regency Padang Pariaman. This was proven from rhitung = 0.533 &gt; rtabel = 0.404, and significance value 0.000 &lt; 0.005. which means that Ha is accepted and Ho is rejected , so the hypothesis says "there is a correlation in learning motivation with student learning outcomes in thematic learning in of four grade of primary school on cluster two in subdistrict Enam Lingkung regency Padang Pariaman" accepted.
Peningkatan Hasil Belajar Siswa pada Tematik Terpadu dengan Menggunakan Model Quantum Teaching di Sekolah Dasar

Describing the improvement of student learning outcomes using the Quantum Tecahing model in integrated thematic learning in grade IV elementary schools is the aim of this study. Integrated thematic learning is learning that uses themes in the learning process. This research method, using classroom action research methods with qualitative and quantitative approaches. Where this research was conducted on the fourth grade students of SDN 03 Pasaman, amounting to 20 people consisting of 12 male students and 8 female students. The results showed an increase in student learning outcomes in integrated thematic learning using the Quantum Tecahing model. From the average value of 73.85% in the first cycle to 87.95% in the second cycle.
Analisis Pemanfaatan Macromedia Flash 8 sebagai Upaya Pengembangan Media Pembelajaran Tematik Terpadu di Sekolah Dasar

The 2013 curriculum which applies to elementary school education, is a curriculum that emphasizes integrated thematic learning from class I level to class VI. It is integrated thematic learning then combined with a saintifical approach. Merging integrated thematic learning with a saintifical approach should provide students with a meaningful learning experience through the full delivery of learning materials without feeling a barrier between matter one to the other through scientific learning activities. But in reality, the process of corresponding learning is still hinted at by the inadequate use of the learning media for unified thematic learning. Thus, there is a learning medium that can convey a unified, comprehensive, unified thematic learning material that is needed. To that end, this research aims to review the Macromedia Flash 8 development of integrated thematic study-based Macromedia Flash 8 at elementary school. The method of this research used is the literature study obtained through searches of relevant journal articles, books, and other scientific sources. Analysed studies have proved that the unified thematic media based Macromedia Flash 8 is characterized by quality, fun, effective, and practical learning media.
PENINGKATAN HASIL BELAJAR MATEMATIKA MENGGUNAKAN MODEL PROBLEM BASED LEARNING (PBL) DI KELAS IV SD

This study aims to describe the application of the Problem Based Learning (PBL) model to improve learning outcomes on fraction material in grade IV elementary schools. This type of research is Classroom Action Research (PTK) using qualitative and quantitative approaches. The research subjects were 16 students in grade IV SD N 01 Ladang Laweh. The results showed an increase. In the first cycle, the RPP observation results were from 83.7% to 93% in the second cycle. Implementation in the aspects of teachers and students in cycle I 81.7% to 92% in cycle II. The average assessment of student learning outcomes in cycle I was 75.5% to 86.8% in cycle II.
Pengaruh Pendekatan Pendidikan Mate matika Realistik Indonesia (PMRI) Terhadap Hasil Belajar Penyajian Data di Kelas V Sekolah Dasar

This study aims to determine the effect of student learning outcomes on learning mathematics for data presentation material in class V of Elementary School for the 2019/2020 academic year. The population in this study were all elementary schools in the Cluster II of Lubuk Kilangan District, which consisted of 7 schools (3 schools were groups). The samples of this research were class V SDN 08 Padang Besi, totaling 28 people as the experimental class, and class V SDN 06 Padang Besi, totaling 30 people as the control class. The instrument used in this study was an objective test in the form of multiple choices. The data analysis technique used was the t-test. The results showed that the average score for the experimental class that applied learning with the Indonesian Realistic Mathematics Education (PMRI) approach was 86.7 higher than the average value for the control class that applied conventional learning was 73.2. This proves that there is a significant influence on student learning outcomes in mathematics learning in elementary schools using the Indonesian Realistic Mathematics Education approach.
Effectiveness of Video Education in Efforts to Prevent Diarrhea in Class 3 Children at Madrasah Hasyim Asyari Pulosari Tulungagung

Diarrhea is a disease based on environment and hygiene. Therefore, there is a need for education that can accelerate the increase of knowledge effectively through electronic media, namely video. This study aims to determine changes in the level of knowledge about prevention of diarrhea in grade 3 children before and after education using video media. This study has a sample of 30 respondents in Madrasah Hasyim Asyari RT 02 RW 19 Pulosari Village, Ngunut District, Tulungagung Regency, the research was carried out on 18 and 20 March 2022. The research instrument used a questionnaire to examine data on diarrhea prevention, the data were analyzed using the Wilcoxon Singned Test. rank test. The results showed that the knowledge of respondents in the good category increased from 0 Percent before treatment to 100 Percent, while the knowledge of respondents in the moderate category decreased from 26.66 Percent before treatment to 0 Percent after treatment. The results of data analysis showed that there was an effectiveness of health education using video media on knowledge of diarrhea prevention in grade 3 children of Madrasah Hasyim Asyari, p value 0.00 which means there was an increase in knowledge of diarrhea prevention in children using video media. The conclusion is that there is an increase in children's knowledge about diarrhea prevention after attending education using video media. Video education media can be used as an alternative teaching material for teachers to students to improve health information
Synthetic Minority Oversampling Technique Pada Model Logit dan Probit Status Pengangguran Terdidik

Educated unemployment is caused by a misalignment of educational development planning and employment development, resulting in underemployed graduates from various educational institutions. Unemployment data in DKI Jakarta shows an unequal class. Unbalanced data is a severe problem of modeling because it can cause prediction errors that affect the accuracy of the resulting model. Using SMOTE to handle unbalanced data will likely increase the model’s accuracy. This study aims to find the best model for identifying the factors influencing the status of educated unemployment using logit and probit models and handling unbalanced data using SMOTE. The results showed that the independent variables that affect the status of educated unemployment in the logit and probit models are the same: age group and participation in training. The independent variables that affect the status of educated unemployment in the logit and probit models with SMOTE are also the same: age group, marital status, and participation in training. Unbalanced data handling using SMOTE can increase the balanced accuracy value significantly. Balanced accuracy values for the logit and probit models with SMOTE are higher than the logit and probit models without SMOTE. The logit model with SMOTE is the best because it has the highest balanced accuracy value compared to other models. According to the logit model with SMOTE, the educated unemployed in DKI Jakarta are young and have never married. There is a need for the government to play a role in improving the quality of educational institutions in producing graduates who meet company qualifications and can be hired by employers. Unemployed people who have attended the training, despite having a higher education, may also become unemployed. The training provided has not been able to reduce the unemployment rate. As a result, the government should be able to provide training to improve entrepreneurship skills while also providing capital in the form of business loans to reduce educated unemployment.
Pengaruh Motivasi Belajar dan Dukungan Sosial Teman Sebaya Terhadap Self Regulated Learning di Sekolah menengah Atas

This study aims to examine the effect of learning motivation and peer social support on self-regulated learning in high school students. This study uses a quantitative approach with multiple regression analysis techniques. Using 40 students for scale trials and sampling techniques with cluster random sampling obtained as many as 112 students. Data collection techniques used three scales, namely the scale of learning motivation, peer social support, and independent learning. The results are (1) there is a significant positive effect between learning motivation and self-regulated learning where the correlation rx1y = 0.621 with p &lt;0.05, the value of the predictor determinant coefficient (R2) is 0.386 which means learning motivation contributes to influencing oneself. organize learning by 38.6%. (2) There is a significant positive influence between peer social support and self-regulated learning where the correlation rx1y = 0.329 with p &lt;0.05, the value of the predictor determinant coefficient (R2) is 0.257 which means learning motivation contributes to influencing independent learning by 25.7 %. (3) There is a significant influence of learning motivation and peer social support on self-regulated learning, based on the coefficient F reg = 38.550 with p &lt; 0.05, and the correlation coefficient R = 0.644 with p &lt; 0.05 and R2 = 0.414, which means meaning that the contribution of both affects self-regulated learning by 41.4%.
Metode AdaBoost dan Random Forest untuk Prediksi Peserta JKN-KIS yang Menunggak

The contribution of participants, employers, and/or the government is one of the most important things in the National Health Insurance Program-Healthy Indonesia Card (JKN-KIS) implementation. All Indonesian residents were required to participate in the JKN-KIS program which is divided into four types of participation, one of which is Non-Wage Recipient Participants (PBPU) whose contributions are paid independently. However, based on December 2021 data, 60% of PBPU participants were late in paying monthly until they were in arrears. Arrears in payment of contributions cause several problems, including payment of claims to deficits. This research utilized big data owned by the Healthcare and Social Security Agency (BPJS Kesehatan) and machine learning based on ensemble trees, namely AdaBoost and random forest to get the predictions of participants in arrears. The results showed that machine learning based on an ensemble tree was able to predict PBPU participants in arrears with high accuracy, as evidenced by the AUC values in both models above 80%. The random forest model has an F1-score and the AUC value is better than the AdaBoost, namely the F1-score of 85,43% and the AUC value of 87,20% in predicting JKN-KIS participants who are in arrears in payment of contributions.
Pola Faktor Keragaman pada Respons Dikrit

In social research, respondents are usually given several questions or indicators for assessment. Responses between respondents may differ even if the same questions or indicators are given. This is one of the causes of the diversity of responses. The diversity of responses is one of the factors that cause response bias in conducting social research. The diversity of responses can come from differences in the thought processes of each respondent. There are three main aspects in the thought process, namely cognition, affection, and conation. This paper aims to analyze the source of the diversity of responses in the aspects of cognition, affection, and conation. The first thing to do in this research is to design a questionnaire by developing indicators into three aspects (cognition, affection, and conation). The study involved 100 respondents using OVO with a purposive sampling method. Respondents assess indicators of aspects of cognition, affection, and conation. The assessment options given are discrete assessments 1-5 with a description of the assessment adjusted to the indicators. Then, the respondent's assessment data were analyzed by calculating the standard deviation, analysis of variance, further test (Tukey HSD) and the distribution of the assessment of each indicator. The main result obtained is that there are three consecutive indicators with the largest standard deviation values in each aspect. These indicators are the source of the diversity of responses in aspects of cognition, affection, and conation. The results of the analysis also show that the conation aspect is the most diverse aspect with the largest standard deviation value. This research is useful as a reference for making social research questionnaires in measuring aspects related to cognition, affection, and conation.
Model Regresi Kuantil Spline Orde Dua Dalam Menganalisis Perubahan Trombosit Pasien Demam Berdarah

Quantile regression can be used to analyze data containing outliers including DHF data. The spline is able to identify several patterns of change in the regression model, so this study uses a second-order quantile spline regression model in analyzing DHF data that occurred in Makassar City. In this article, the authors analyze the pattern of changes that occur in platelets based on changes in the hematocrit content of DHF patients. The selected quantiles are quartiles 0.25; 0.50; and 0.75 with 3-knot points. Based on the results of the analysis, the minimum GCV value obtained at the use of knot points is 30.30; 44.80; 47.10 for the 0.25 quartile; 0.50; and 0.75. This shows that in each quartile, there are four patterns of quadratic changes that occur in the platelet count of DHF patients. The parabolic curve formed in each pattern segmentation shows that there are times when platelets are increasing and there are times when platelets are decreasing. However, the average platelets decreased drastically, especially when the hematocrit reached 47.10%.
Peramalan Data Cuaca Ekstrim Indonesia Menggunakan Model ARIMA dan Recurrent Neural Network

Extreme weather modeling is a challenge for modeling experts in Indonesia and the world. Extreme weather prediction is a complex problem because the chances of it happening are very small, so the developed models often have a low level of accuracy. The purpose of this research is to combine the classic model, Autoregressive Integrated Moving Average (ARIMA), recurrent neural network (RNN) model using Adam and SGD estimation (RNN-Adam and RNN-SGD) with the reLU, tanh, sigmoid and gaussian activation functions. In addition, the ARIMA-RNN mix model was also demonstrated in this study. These models are applied to monthly period extreme weather data obtained from the Meteorology, Climatology and Geophysics Agency (BMKG) of West Sulawesi Province which are converted into training data and test data. The RMSE value is used to see the level of prediction accuracy in both training data and test data. Based on the research results, the best model obtained for modeling Indonesia’s extreme weather is the ARIMA-RNN-Adam mix model with the reLU activation function based on the RMSE value on the training and test data. At n = 50, the smallest RMSE and MSE values of the third model are the ARIMA-RNN-Adam model which is 0.23212 using the reLU activation function, then the ARIMA-RNN-SGD model which is 0.25432 with the same activation function, while the ARIMA value is 0.3270. At n=100 it can be seen that the smallest RMSE and MSE values of the three models are the ARIMA-RNN-Adam model which is equal to 0.25149 using the reLU activation function, then the ARIMA-RNN-SGD model which is equal to 0.25256 with the same activation function, while the ARIMA value is 0.2644.
Janaka: Aplikasi Android Pembelajaran Menulis Teks Anekdot Kurikulum SMK Pusat Keunggulan

This research was carried out with the aim of producing "Janaka," an android application on anecdotal writing material in the vocational school. The method used in this research is ADDIE which consists of five stages analysis, design, development, implementation, and evaluation. This research produces an android application for learning to write anecdotes. The resulting media product has an apk format (android application package) which is a program package that can be run on smartphones with the android operating system that has gone through a series of validations with 87.5% scores from material experts and 74.4% scores from media experts and a trial with the use response value of 81.43% of students and 77.3% of teachers. The material for writing anecdotal texts is divided into three parts: simple research as anecdotal writing materials, writing anecdotes based on facts and data, and turning anecdotes into comic strips. Meanwhile, the media product component as an exercise in writing anecdotal text is divided into an interactive quiz component, an image component, a text and video component for learning materials, and a task collection platform component.
Image Denoising Method Based on Harmonic Filtering and Non-Subsample Shear Wave Block Matching in Wavelength Domain

&lt;p&gt;Efficient noise filtering is the difficulty of image denoising on the premise of preserving the edge and internal texture information of the image. Therefore, this paper focused on adaptive Gaussian variational model and block matching image denoising method in the wave domain from the non-local point of view. At first, a 3D block match harmonic filtering model was establish in that wavelet domain, 3D transform was use to represent that real signals in the match block group in a sparse form, then the shrinkage threshold was used to achieve the purpose of pre-denoising, and the wavelet transform was then used to extract the high frequency part of the predictor image for filtering. In order to avoid edge blurring, Laplace-Gaussian algorithm was used to construct a new operator into the diffusion model, and the wavelet coefficients were reconstructed to obtain the final approximation of the original image. Secondly, a block matching denoising model based on shear wave was proposed. In order to avoid ill-conditioned problem, The multi-scale geometric analysis method using shearlet transform can improve the edge protection ability, and a block matching denoising model based on shearlet is proposed. The new model predicts the scaling threshold according to the statistical characteristics of the histogram, performs hard threshold filtering on the high-frequency sub-band to obtain the processed sub-band coefficients, and performs block matching 3D filtering on the decomposed low-frequency sub-band coefficients to obtain the processed coefficients. All processed subband coefficients are inversely transformed and reconstructed to obtain a denoised image. The analysis and simulation results showed that the two new models can effectively suppress noise and improve the clarity, and the block matching denoising based on shear wave had more advantages.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Predicting Online Fraudulent Transaction Using Machine Learning

Abstract The authors have requested that this preprint be removed from Research Square.
Performing High Quality Reports Of Suspected Child Maltreatment By Using An Innovative Toolkit

Background and objective: Child maltreatment is a major cause of direct and indirect injuries, trauma and latent health problems associated with adverse childhood experiences, such as obesity, health risk behaviors, and mental health problems. Lack of recognition and reporting of suspected maltreatment may leave children vulnerable to continued victimization that can lead to devastating consequences for children and their families. As per Wisconsin law, medical providers and social workers are among those professionals mandated to report to Child Protective Services (CPS) when child abuse is suspected. Issues arise from the starting point of making the decision to report all the way to the communication of pertinent information to CPS. A better understanding of these barriers represents an opportunity for improvement and system change with the ultimate purpose of improving children safety. We aim to improve the mandated reporting process via use of the Safety Advocates for Endangered children toolkit (SAFE children) so that 95% of medical providers in Children's Wisconsin (CW) urgent care centers will report high confidence on making high quality reports of suspected child maltreatment and at least 95% will report an increase in efficiency when reporting. METHODS: Our QI team outlined our theory for improvement, and multiple plan-do-study-act cycles will be conducted to test interventions aimed at key drivers. Interventions include the use of the SAFE children toolkit, targeted medical provider education, and integration of an electronic mandated reporting check list into the electronic medical record system (EMR) to facilitate high quality mandated reporting. Our primary outcome is the increase in percentage of medical providers reporting improved confidence and efficiency in performing high quality reports. RESULTS: We will apply structured surveys to gather data on improvement while testing the use of the SAFE children toolkit. We will also perform data analysis on consistency in high quality reporting via the implemented electronic checklist. CONCLUSIONS: Using improvement methodology, we hope to successfully facilitate and standardize performance of high-quality reports in urgent care centers. Targeted education, the use of a mandated reporting toolkit and EMR check list will be associated with improvement in confidence and efficiency when performing high quality suspected child maltreatment reports.Performing High Quality reports: Overview of the projectPerforming high Quality Mandated Reports: Key Driver Diagram
A Case Study of Children Language Acquisition: The Form of Questions-Making Processes Employed by Preschoolers

This study shows the forms of questions making by 3 and 5 years old children. Purposive sampling was used to determine the objects of the study.. The forms were found through descriptive qualitative approach by implementing three methods, observation, interview, and note taking techniques to collect the data. To analyze the data, the researchers used data reduction, categorization, and conclusion. The researchers confirmed that there were four kinds of questions-making processes employed by Preschoolers. They were sign form, single word form, double word form or phrase, and clause or sentence. It can be concluded that the differences between those two ages were in term of the frequency of using the forms. The 3 years old child used single and double word forms frequently, while the 5 years old child used double word form or phrase and clause frequently.