Reviewerly/exHarmony huggingface dataset:
Correlation between ABO blood group and gestational hypertensive disorder among pregnant women in Abuja, Nigeria

Gestational hypertensive disorder (GHD) is among the major health problems in pregnant women. In this study, we assessed the relationship between gestational hypertensive disorder and ABO blood groups among women who attended the antenatal clinic at the University of Abuja Teaching Hospital, Abuja, Nigeria. Correlational study design was used on a total of 138 patients with sociodemographic characteristics and clinical data such as blood group, gestational hypertensive disorder status, maternal age at pregnancy, and parity were extracted. Descriptive statistics was carried out on the collected data and chi-square test for the test of association or Fisher’s exact where necessary. The maternal age of the women ranged from fifteen to fifty-one years old with a mean age of 30.7 ± 9.8. Clinical information revealed that 17 (12.3%) primigravida and 121 (87.7%) non-primigravida patients. The patients’ distribution by blood group revealed that 33 (23.9%), 32 (23.2%), 47 (34.1%) and 26 (18.8%) belonged to blood group A, B, AB, and O respectively. Our results showed a relationship between blood pressure and the ABO blood group but not significant with χ2 = 12.31 and p = 0.421 with blood pressure of 150/100–154/104 mmHg ranked highest in frequency among all the blood groups. Also, we observed a non- significant relationship between maternal age and the occurrence of GHD at χ2 =19.81 and p = 0.229 which implies that GHD is not associated with age but that blood pressure increases with gestational age. Interestingly, a significant relationship exists between gestational hypertension and parity at χ2 = 26.71 and p = 0.045. Blood group AB was more susceptible to gestational hypertensive disorder whereas blood groups O, A and B were less susceptible to it. We recommend increased awareness of GHD among pregnant women, all health workers, and the general public about its danger to pregnant mothers and fetuses.
Analisa Perbandingan Complate Linkage AHC dan K-Medoids Dalam Pengelompokkan Data Kemiskinan di Indonesia

The poverty rate in Indonesia has increased from 9.54 percent in March 2022 to 9.57 percent in September 2022 due to inflation and low wages and people's incomes. To overcome this problem, steps such as providing social assistance, creating decent jobs, and increasing wage standards are needed to increase people's purchasing power and reduce poverty in the future. The government needs to pay special attention to provinces with high poverty rates through special programs and efforts to increase income and the economy in these areas. Data Mining is a solution in solving this problem by utilizing the clustering method which is known as the clustering method. The clustering method used in this study is the AHC method and the K-Medoids method. In order to determine the provinces with the highest number of poor people, the AHC and K-Medoids clustering methods will be applied separately so that the final results of each will be analyzed. The results of the analysis show the formation of three clusters with different cluster locations. The application of the AHC method resulted in cluster 2 with the largest number of provinces, namely 22 provinces, followed by cluster 0 with 9 provinces, and cluster 1 with only 3 provinces. While the application of the K-Medoids method resulted in cluster 1 with the largest number of provinces, namely 22 provinces, followed by cluster 0 with 9 provinces, and cluster 2 with only 3 provinces. Although the location of the clusters is different between the two methods, the number of provinces in the cluster is the same so that a cluster with a total of 3 provinces is declared the province with the largest number of poor people.
Penerapan Data Mining dalam Implementasi Algoritma K-Means Clustering untuk Pelanggan Potensial pada Koperasi Simpan Pinjam

Apart from that, there are efforts to provide for the needs of its members as well as financial assistance for education, health and there are also concessions needed by the members. By conducting this customer cluster, it will help the company determine its potential customers so that it can implement the right marketing strategy for each type of existing customer, and will certainly provide benefits for the company in increasing the quality and loyalty of customers towards the company. Data mining has functions, namely prediction, description, classification and clustering functions. Data mining also has many methods for its application, one of these methods is K-Means. The K-Means Clustering algorithm can be implemented in grouping potential customers, especially in savings and loan cooperatives. Based on the data sampling used, the data can be grouped into 2 (two) clusterings.
Penerapan Data Mining Untuk Klasifikasi Penerima Dana Bantuan Sosial Dengan Menggunakan Algoritma K-Nearest Neighbor

The Social Assistance Fund (Bansos) is a government program carried out to assist in eradicating community poverty in Indonesia and improving the welfare of families in Indonesia. Social Assistance Funds (Bansos) are distributed from the central ministry, then forwarded to local social services and then distributed to the community through each sub-district office. After data collection is carried out, the process of determining and selecting the families who receive Social Assistance Funds (Bansos) is carried out. However, in the implementation process there were several obstacles, one of which was that the provision of Social Assistance Funds (Bansos) was still not on target for families who deserved to receive Social Assistance Funds (Bansos). This problem is an important matter that must be resolved, this is because the main aim of the Social Assistance Fund (Bansos) program is to help eradicate poverty in Indonesia. Reviewing and processing data again based on previous data can be completed using one of the computer techniques. Data mining is a technique used to reprocess data. Data processing returns to data mining based on data previously stored in a data collection or data warehouse. Classification is part of data mining which aims to find out certain models of data so that they can be divided into several classes or groups. The K-Nearest Neighbor (K-NN) algorithm is part of a data mining technique which aims to divide data into certain groups. The results obtained in the research are the K value used in the research, namely K=7, the result of the family data grouping process which has just determined that the family received Social Assistance Funds (Bansos).
Rekomendasi Content Creator Terbaik sebagai Pendukung Keputusan Penilaian pada Agensi Menggunakan Metode TOPSIS

As an agency, it is necessary to evaluate and assign value to the content outcomes that have been published by content creators periodically. Aurora News Agency, which is one of the content creator agencies for Snack Video, has over 700 member content creators. This requires specialized techniques to facilitate and expedite the assessment of the performance of these content creators. Therefore, research was conducted on a decision support system using the TOPSIS method as a decision-making tool for evaluating the best content creators within the agency. Data was collected from a total of 630 content creators, and after undergoing data cleansing processes, a total of 10,916 content items were obtained. The research results present a ranking of the top 10 content creators based on their preference scores, ranging from the highest to the lowest. Anemz Tv is the content creator with the highest preference score of 0.4368, securing the first rank. On the other hand, Talenta.TV is the content creator with a preference score of 0.3203, earning the second rank. Upon analysis, differences in strategies for each content creator became apparent, with some focusing on quantity and others placing emphasis on the quality of content. In conclusion, the application of the TOPSIS method can be implemented relatively simply, with sufficiently fast computations, and it yields a diverse range of preference scores
Penerapan Data Mining Untuk Penjurusan Kelas dengan Menggunakan Algoritma K-Medoids

Class assignments are carried out to focus students on the subjects that will be studied during Senior High School (SMA). Class majors are generally carried out in class of all the main values used in the class majoring process. This is a problem with the class majoring process, where mistakes often occur in the class majoring process. Mistakes regarding class majors made by students will have quite a fatal impact on the student, apart from not being able to change classes, it will also have a laziness effect on the student because it does not match the student's abilities. Solving this problem can be done using a technique called data mining. The solution to this problem is done using clustering. The K-Medoids algorithm is the algorithm used to solve the problems in this research. The process of grouping or forming clusters in the K-Medoids algorithm is based on calculating the closest distance to each object, calculating the closest distance is based on determining the centeroid value first. The K-Medoids algorithm can form 2 (two) clusters according to existing class majors. The results obtained show that there are 3 (three) alternatives included in cluster 1 and also 12 (twelve) alternatives included in cluster 2.
The Effect Of Role Play Strategy In Teaching Vocabulary At The Eighth Grade Of SMP Negeri 5 Pematang Siantar

The aim of this research is to look at The Effect Of Role Play Strategy In Teaching Vocabulary At The Eighth Grade Of Smp Negeri 5 Pematang Siantar. This research would employ a quasi-experimental design with a quantitative research and a "pre-test and post-test" methodology. The objective of the research was to determine whether or not eighth grade children learn vocabulary well through role-playing. The researcher used just two classes as samples. The experimental group is VIII-3, whereas the control group is VIII-4. The mean achievement of these two groups is comparable. Where each class has 31 students. The VIII-3 class was designated as the experimental group, and they would teach through Role Play Strategy, while the VIII-4 class was designated as the control group, and they would not be employing any Role Play Strategy. From the results of the data analysis in the previous study, it can be concluded that Role Play Strategy plays a key role in helping students improve their vocabulary. The use of the Role Play Strategy can help students become more proficient in vocabulary. During the vocabulary lesson in the classroom, the students are more engaged and exhibit greater creativity and innovation. T-test &gt; T-table (3.9 &gt; 1.671), based on the analysis results at the 5% significance level. It also shows that (Ho) was rejected but (Ha) was accepted. The novelty of this research is that students are more active and interested in the learning process, students understand the material more easily, and students have a greater curiosity.
Penerapan Algoritma K-Means Clustering untuk Daerah Penyebaran Sampah Kelurahan

Waste in Indonesia, especially in Magelang City, has become a serious problem due to rapid population growth. Waste management issues, including landfills and collection, need effective handling. Data mining methods, such as K-Means clustering, can help identify areas with the highest levels of waste generation. This approach provides insights for the development of a more focused and efficient waste management strategy, a significant contribution to the improvement of Magelang City. By identifying the areas with the highest waste generation, waste management measures can be directed more efficiently and effectively. This includes increasing the transparency, capacity, and role of waste banks, as well as other efforts to reduce the negative impact of waste on the environment and human health. After clustering, the waste in Magelang City was grouped into 3 clusters according to the supplier area and the volume of waste. Then after the evaluation stage with the silhouette score displays a value of 0.79 which is a good value because it is close to the value of 1.0. With this method, it is expected that the city government in handling waste in Magelang city can be done optimally, efficiently, and on target
The Quora website for students in learning the skill of Arabic Reading on the Internet (an analytical and descriptive study) | موقع كورا (Quora) للطلبة في تعلم مهارة القراءة على الوسائل الانترنت (دراسة تحليلية وصفية)

Electronic or computerized information sources have become an important part of libraries, especially those that aim to keep pace with modern developments to keep users up to date on scientific research, seminars and conferences covering all fields. This study aims to describe the Quora site as a site for students to learn in Internet-based Arabic reading skills. This research is a type of qualitative literature study with descriptive and analytical methods. Library sources are used to obtain data for scientific research. The object of this research is the Quora site. The results showed that 1) The idea of creating a Quora site is based on the fact that most human experience, knowledge, and opinions are still not available on the Internet, but can be found in people's books and experiences; 2) Quora aims to share all the knowledge available in the world through people's contributions to this knowledge base; 3) Quora allows everyone to access it.
Peran Learning Agility untuk Meningkatkan Perilaku Kolaborasi Pegawai Generasi Milenial di Pemerintahan Kota Padang

An employee nowadays is required to be able to adapt quickly to every job given, and to be able to learn from existing experience in order to compete with other workers. This research aims to determine the role of learning agility in improving the collaborative behavior of millennial generation employees in the Padang City Government. The independent variable in this research is learning agility and the dependent variable is collaboration behavior. The measuring instruments used in this research are the Learning Agility scale and the collaboration behavior scale. The sampling technique in this research is purposive sampling, namely sampling using certain considerations according to the desired criteria to determine the number of samples to be studied. The sample for this research was 266 employees in the Padang City Government. Validity and reliability testing in this research used the Cronbach Alpha technique. The results of the validity coefficient on the learning agility scale with corrected item-total correlation values ​​range from 0.316 up to 0.646, while the reliability coefficient is 0.831. The results of the validity coefficient on the Collaboration Behavior scale with corrected item-total correlation values ​​range from 0.302 up to 0.749, while the reliability coefficient is 0.853. Based on data analysis, the calculated t value of 17.309 is greater than the t table, which is 1.660. So it can be seen that the significance value is 0.001 &lt; 0.05, which means the hypothesis is accepted. This illustrates that learning agility has a significant effect on collaborative behavior. So it can be explained that H1 states that learning agility has a positive effect on collaborative behavior. The effective contribution of the learning agility variable to collaboration behaviour variable is 53%.
genpathmox: An R Package to Tackle Numerous Categorical Variables and Heterogeneity in Partial Least Squares Structural Equation Modeling

Partial least squares structural equation modeling (PLS-SEM), combined with the analysis of the effects of categorical variables after estimating the model, is a well-established statistical approach to the study of complex relationships between variables. However, the statistical methods and software packages available are limited when we are interested in assessing the effects of several categorical variables and shaping different groups following different models. Following the framework established by @Lamberti16, we have developed the Â [genpathmox](https://CRAN.R-project.org/package=genpathmox) *R* packageÂ forÂ handling a large number of categorical variables when faced with heterogeneity in PLS-SEM. The package has functions for various aspects of the analysis of heterogeneity inÂ PLS-SEM models,Â including estimation, visualization, and hypothesis testing. In this paper, we describe the implementation ofÂ genpathmoxÂ in detail and demonstrate its usefulness by analyzing employee satisfaction data.
hydrotoolbox, a Package for Hydrometeorological Data Management

The hydrometeorological data provided by federal agencies, research groups and private companies tend to be heterogeneous: records are kept in different formats, quality control processes are not standardized and may even vary within a given agency, variables are not always recorded with the same temporal resolution, and there are data gaps and incorrectly recorded values. Once these problems are dealt with, it is useful to have tools to safely store and manipulate the series, providing temporal aggregation, interactive visualization for analysis, static graphics to publish and/or communicate results, techniques to correct and/or modify the series, among others. Here we introduce a package written in the R language using object-oriented programming and designed to accomplish these objectives, giving to the user a general framework for working with any kind of hydrometeorological series. We present the package design, its strengths, limitations and show its application for two real cases.
The Implementation of Educational Games as a Digital Learning Culture in Elementary School Learning

Learning with technology content, including computer science or informatics, is a very crucial topic at this time. Unfortunately, there are still many schools that have not adapted to this digitalization culture. There are many factors behind schools not starting a digitalization culture, such as facilities and infrastructure and human resources that are not ready yet. One school that has not implemented digitalization in learning is SDN Kedungdalem. This school still does not have digital-based learning media, most of the learning activities are carried out using books and worksheets. This situation makes students not excited about learning because it is not interesting for students. The aim of this research is to analyze the description of the results of students' academic responses to ICT learning and educational games that have been given. The research method used in this activity is a qualitative approach with rural operations. The subjects of this research were 5th grade students at SDN Kedungdalem. The research results showed that students really liked the educational games provided because the games were funny, exciting and fun.
BEATS IN RHYTHM: EFFICIENCY AND INNOVATION IN COLLECTIVE PERCUSSION MUSIC IN MUSIC SCHOOLS

This article examines the importance of collective percussion in music schools and explores the effectiveness and innovations associated with this type of music education. It highlights the benefits and challenges faced by students and teachers, and discusses innovative approaches and technologies that can improve the quality and effectiveness of learning.Music has always been a magical medium of expression, and playing percussion instruments allows students to create rhythmic melodies together, developing their musical abilities and important collaborative skills. Music brings people together, teaches communication and creativity, and collective percussion music making offers students endless opportunities for development and expression.The article also addresses important aspects of collaboration and communication that are of particular importance in today's world. Collaborative percussion musicianship opens up new horizons in learning and creativity, contributing to the development of both musical and interpersonal skills.Music has always been an important part of the cultural development of society. In the world of music education, more and more attention is being paid to collective music making, and in particular to playing percussion instruments. This contributes not only to the development of students' musical skills, but also to communication and work skills, teamwork and cooperation.
Implementation Of Teacher Presence System Using Mobile-Based Geofencing &amp; Haversine Formula Methods

Implementation of a teacher presence system using geofencing and the Haversine Formula mobile-based method provides a modern solution for accurately monitoring teacher attendance. This system utilizes geofencing technology to set virtual boundaries around certain locations and the Haversine formula to calculate the distance between the teacher's current location and the school's location. If the teacher's location is within the boundaries of the area, the system assumes the teacher is present, and if outside, the system considers the teacher absent. Attendance status is regularly updated and stored in the database, providing an efficient method for administrators to monitor teacher attendance and increase accountability. The use of this system reduces the possibility of manual errors, making it a valuable tool in education. Two tests were carried out, namely testing the accuracy of the system and testing black box testing. Accuracy testing was carried out under three conditions, namely inside the presence area, at the border of the presence area, and outside the presence area. The test was carried out 30 times and resulted in 100% accuracy. then blackbox testing also concludes that the application works in accordance with the testing that has been done. The conclusion from this research is that the higher the device and network used, the more accurate it will be.
Amplifying Proficiency: Unearthing the Impact of Extensive Listening on Student Listening Skills

In conventional language education, listening often receives less attention compared to the teaching of grammar and other language skills. Nevertheless, it is crucial to acknowledge that knowledge acquisition and assimilation primarily occur through listening. This study explores the enhancement of students' listening competency through extensive listening practices, utilizing the participatory action research method, specifically the Collaborative Classroom Action Research approach. The research was conducted at Junior High School in Medan, Indonesia and involved 31 Grade VIII students. The study incorporated pre-test and post-test listening assessments, and observation across three cycles: pre-cycle, cycle I, and cycle II. The results clearly demonstrate the positive impact of extensive listening on students' listening skills. Overall, there was a substantial improvement, with scores increasing from 49.35% in the pre-test to an impressive 85.16% in cycle II. Notably, individual progress also showed substantial growth, rising from 6.45% in the pre-test to a remarkable 77.4% in cycle II. These findings underscore the undeniable effectiveness of extensive listening in language education. They offer valuable insights for English teachers and provide robust support for the adoption of extensive listening as a potent means to nurture and elevate students' listening skills, which are a fundamental aspect of language acquisition.