Reviewerly/exHarmony huggingface dataset:
Bahasa Inggris

Literacy is the ability of Indonesian language competence on the basis of reading and writing. Literacy skills in Indonesia are quite lagging behind other nations in the world. To improve literacy skills, we use the SAC (All Smart Children) approach with TaRL (Teaching at Right Level) learning. This approach can be realized by using one of the clustering methods, namely the K-Means Algorithm. The grouping will use data from the implementation of the literacy program at SMP Santi Yasa Petak in the span of 3 months and the modeling using the Rapid Miner application. The results obtained divided students into 2 clusters, namely a cluster of students who were able to carry out a literacy program of 8 people and a cluster of students who had not been able to carry out a literacy program of 5 people.
Penerapan Standar Nasional Indonesia (SNI) dalam Tata Kelola Arsip di Perguruan Tinggi

Currently in Indonesia, most agencies/institutions have not carried out the archive management process using SNI/ISO standards. It is time for effective and efficient archive management to be implemented. This study aims to describe archive management by applying SNI/ISO 30301, 23081, and 15489 standards at the University of Indonesia Archives Office, the benefits obtained, the obstacles faced and the supporting factors in the implementation process. The research method used is descriptive, namely describing the process of applying SNI/ISO standards 30301, 23081, and 15489 at the University of Indonesia Archives Office which includes policies, responsibilities, monitoring and evaluation, risk assessment/management, training and competence, recording control, making processes , capture and manage records. In addition, the study also describes the benefits obtained and the obstacles faced as well as the supporting factors. The application of SNI/ISO 30301, 23081, and 15489 in managing archives is an indicator/requirement as a benchmark in managing archives effectively and efficiently.
Need Analysis for Teaching English in Early Childhood Education Students

Analysis of needs for English language teaching in PG-Paud. English for Specific Purposes (ESP) in the learning process in higher education is often less effective. One contributing factor is the lack of a learning plan so that learning is not relevant to the field of science they are capable of. Therefore, it is necessary to start planning learning by conducting a needs analysis based on students' needs in learning English. This research aims to determine and describe the needs of English language students in PG PAUD Universitas Prima Nusantara Bukittinggi. This research was conducted using a qualitative descriptive approach. The objects of this research were students in the third year. Data was collected through questionnaires and direct interviews. The collected data is classified so that students' needs in learning English can be identified, then each one is explained. The research results show that (1) students' mastery of English is still relatively low, (2) 50% of students improve their oral communication or speaking skills and 30% write as the main priority in learning English in preparation for applying for work, (3) during learning English, students expect an increase in their skills related to both oral and written. Based on these results, it is recommended to prepare syllabus planning and develop English teaching materials in PG-Paud programs.
House Price Prediction Using Linear Regression Model

Machine learning is a subset of Artificial Intelligence. Artificial intelligence (AI) and machine learning (ML) are key technologies in solving problems and addressing a wide range of issues in many different fields. Due to its capacity to automate processes, analyze massive volumes of data, and make precise judgments. Generally, it is used in voice assistants, recommendation systems, autonomous vehicles as well as in fraud detection. It also plays a vital role in the real estate sector, accurate house price prediction helps buyers, sellers, and investors make accurate decisions. There is a need for technology to predict housing values because they rise annually. Predicting house prices can assist developers in setting a property's selling price as well as buyers in scheduling the ideal time to buy a home. Four factors influence the price of a house which are area, bedrooms, bathrooms, and location. This study uses a methodology to forecast the price of houses based on relevant features, specifically by applying a linear regression model. Through the use of machine learning methods such as Random Forest, K-Means, Decision Tree, and Linear regression. This strategy will make it easier for people to invest money in a legacy without going via a broker. The study's findings indicate that the Linear regression yields the best accuracy.
FAKTOR PENYEBAB KETIDAKTEPATAN KODE DIAGNOSA SEBAGAI SYARAT PENGAJUAN KLAIM PASIEN RAWAT INAP PESERTA BADAN PENYELENGGARA JAMINAN SOSIAL KESEHATAN DI RUMAH SAKIT UMUM SURYA HUSADHA DENPASAR

Background: Writing a complete diagnosis can produce the right coding because the diagnosis is written in a complete, clear, specific, and consistent manner. Writing clear, complete, and consistent diagnoses can produce quality data (Hatta, 2008). Based on observations made for 1 month from 23 January to 23 February 2023, 39 claim files were returned by the Health Social Security Administering Body due to inaccuracies in the diagnosis code.. This was caused by the doctor's notes that were not clearly legible in 24 (61.5%) claim files and the use of abbreviations in patient diagnoses in 15 (38.5%) claim files, while the purpose of this study was to find out the relationship between doctor's notes that were not clearly legible and the use of abbreviations for patient diagnoses for inaccuracies in the diagnosis code as a condition for filing claims for inpatient patients participating in the Health Social Security Administration at Surya Husadha General Hospital. Methods: The design in this study used a quantitative analytic descriptive research design and porpusive sampling research type, and the sample in this study were all inpatient claim files returned by Health Social Security Administering Body claims for inaccuracies in the diagnosis code totaling 39 claim files. Doctor's notes were illegible in 24 (61.5%) claim files and the use of abbreviations in patient diagnoses in 15 (38.5%) claim files. Result: From the results of this study it was found that there was a relationship between illegible doctor's notes and inaccuracy of the diagnostic code with a p value of 0.001 &lt;0.05 and the use of abbreviations in patient diagnoses for inaccuracy of patient diagnosis codes with a p value of 0.003 &lt;0.05.
Parents' Social Support And Adjustment To Students' Learning Motivation In Junior High School Country 18 Central Maluku

The decrease in learning motivation was caused by students not being consistent in studying at home, besides that students paid less attention to the teacher's explanations because students did not understand the material presented by the teacher which was caused by inadequate internet network access, lazy doing assignments and delaying in submitting assignments.The purpose of this study was to test empirically the relationship between parental social support and adjustment to student learning motivation at SMP Negeri 18 Central Maluku, with a total of 170 students. This study uses population research. Data collection used a learning motivation scale, parental social support scale, and self-adjustment scale. The data analysis used in this study used multiple linear regression analysis with an assumption test. The results showed that there was a very significant relationship between parental social support and adjustment to student learning motivation with a significance value of 0.000 (p &lt;0.05), the higher parental social support and self-adjustment was able to increase student learning motivation.
Sistem Informasi Penerimaan Karyawan (E-Recruitment) Menggunakan Pendekatan Human Centered Design (HCD)

A Web-Based Employee Recruitment Information System or e-Recruitment can be used as a solution in handling the employee recruitment process in a company. With a web-based employee recruitment information system or e-recruitment, companies can choose the right employees for their company themselves. Apart from that, companies can also process applicant data in a database so that applicant data does not accumulate in the filing cabinet. In this research, the author discusses how to design a web-based employee recruitment information system. The system development methodology used is Human Centered Design. The system was built using the PHP programming language, database server with MySQL. The result to be achieved from this research is that the web-based employee recruitment information system is expected to be able to assist the company's HRD department in the employee recruitment process and make it easier for managers to view employee recruitment reports.
Analisis Penggunaan Energi Surya Fotovoltaik Sebagai Sumber Energi Alternatif

Solar photovoltaic energy is a renewable energy source that converts sunlight into electricity through the use of solar photovoltaic cells. The potential of solar energy is enormous, because the sun is an energy source that is abundantly available throughout the world. The method in this article is a qualitative method with literature study or Library Research. The purpose of this article is to analyze existing theories by looking at their comparison to previous theories in the research literature. The literature used is literature from research results or reviews that are recorded in national and international scientific articles that are relevant to the topic of this article. All articles used are sourced from the electronic literacy data search engine Mendeley and Google scholar. Based on the results of the literature review article on the results and discussion, it can be concluded that solar photovoltaic energy has high potential to be used as an alternative energy source in the long term in the future.
Language Learning Media Through Mobile APP: The Effects of Busuu on Vocabulary Learning and Listening Skills

This study investigates the effects of the Busuu Mobile app on vocabulary learning and listening skills. In order to achieve the objective of this study, the researchers used a quantitative approach with a pre-experimental design. The participants of this study were 38 students of class 7.1 in SMP Negeri 4 Tangerang Selatan, with a total of 469 populations. The data were collected through pre-tests and post-tests to determine students’ vocabulary learning and listening skills scores. The scores were then analyzed using Paired Sample Effect Size to determine the effects’ significance. The effect size of students’ vocabulary learning and listening skills was high, with 4.404 for vocabulary learning and 4.670 for listening skills (&gt;1). This study concludes that using Busuu on students’ vocabulary learning and listening skills had a high effect. Therefore, the Busuu mobile app is advised to be utilized in vocabulary learning and listening skills. The future study of finding out the students’ perception of using Busuu will be necessary for the effectiveness of using this mobile application.
An Error Analysis of EFL Undergraduate Students’ Writing Composition in Universitas Tanjungpura

An e rror a nalysis of EFL u ndergraduate s tudent’ w riting c omposition. This study has thoroughly investigated morpho-syntactic errors in the compositions of English Language Education undergraduates at Universitas Tanjungpura. Employing a descriptive methodology and drawing from Ellis (1994), the research analyzed 97 self-descriptive compositions. The findings reveal a significant prevalence of morpho-syntactic errors, totaling 793 syntactical and 333 morphological errors across an average of 18 sentences per composition. Syntax errors involve sentence patterns and subject-verb agreement, while morphological errors revolve around inflection and conversion challenges. Categorized into omissions, additions, misinformations, and misorderings using a surface strategy taxonomy, the errors provide insights into students' linguistic competence. The study advocates for targeted instructional interventions, integrated curriculum development, cross-linguistic awareness programs, and learner-centered approaches. Longitudinal studies and teacher training programs are recommended for a deeper understanding of error evolution and effective pedagogical implementation, contributing to the discourse on morpho-syntactic errors in EFL writing with practical implications for language instruction. Keywords: Error analysis, morpho-syntactic error, self-descriptive composition Abstrak: Analisis Kesalahan pada Komposisi Menulis Mahasiswa S1 Bahasa Inggris. Penelitian ini telah menyelidiki secara menyeluruh kesalahan morfo-sintaksis dalam komposisi mahasiswa pendidikan bahasa Inggris di Universitas Tanjungpura. Dengan menggunakan metodologi deskriptif dan mengacu pada Ellis (1994), penelitian ini menganalisis 97 komposisi yang bersifat self-descriptive. Temuan penelitian mengungkap prevalensi yang signifikan dari kesalahan morfo-sintaksis, dengan total 793 kesalahan sintaksis dan 333 kesalahan morfologis rata-rata dalam 18 kalimat per komposisi. Kesalahan sintaksis melibatkan pola kalimat dan kesepakatan subjek-predikat, sedangkan kesalahan morfologis berpusat pada tantangan infleksi dan konversi. Dikategorikan ke dalam penghapusan, penambahan, miskomunikasi, dan penyusunan yang salah menggunakan taksonomi strategi permukaan, kesalahan-kesalahan ini memberikan wawasan tentang kompetensi linguistik mahasiswa. Studi ini menganjurkan intervensi pembelajaran yang ditargetkan, pengembangan kurikulum terintegrasi, program kesadaran lintas bahasa, dan pendekatan berpusat pada pembelajar. Studi jangka panjang dan program pelatihan guru disarankan untuk pemahaman yang lebih mendalam tentang evolusi kesalahan dan implementasi pedagogis yang efektif, berkontribusi pada wacana tentang kesalahan morfo-sintaksis dalam penulisan EFL dengan implikasi praktis untuk pengajaran bahasa. Kata kunci: analisis eror, karangan deskripsi diri, morfo-sintaksis eror, DOI: http://dx.doi.org/10.23960/jpp.v13.i3.202331
Analyses of Question Types and Evidence Evaluation Types in Big Data Analysis for 7th Grade Students

The purpose of this study was to analyze the types of questions generated through big data analysis, establish hypotheses based on the generated questions, and determine authenticity by analyzing the types of evidence evaluation. To this end, ‘COVID-19’ and ‘yellow dust’, which are relatively familiar subjects and various types of big data have been accumulated in large quantities, were selected as research themes. The subjects of the study were 137 7th grade students, 72 male students, and 65 female students. The results of the study are as follows. First, in big data analysis, questions were created centered on conjectural questions. Second, among the types of evidence evaluation, the rejection type did not appear. Therefore, it is necessary to establish a teaching strategy so that various types of questions can be presented. In addition, it is necessary to teach how to critically judge collected big data and how to use various big data.
Digital Transformation and Cloud Computing: System Dynamics Modeling Approach

Digital transformation allows organizations to use new technologies to rebuild and redefine relationships with customers, employees and partners. Organization are creating high-performance virtual machines on the cloud platform to accelerate the digital transformation of organizations. Organizations are solving data analytics problems by moving to modern data storage on Google Cloud. This study aims to explore the determinants of cloud-based digital transformation in organizations using a System Dynamics Model. Positive factors for cloud-based digital transformation are unparalleled accessibility, cost efficiency, high scalability, automation possibilities, enhanced security and flexibility. Cloud-based digital transformation is also affected by negative factors such as data security and service quality, performance and cost, and integration of existing systems with the cloud and requires strict control. This study develops a framework for successful cloud-based digital transformation in organizations. This research contributes to the understanding of the decision-making process of cloud-based digital transformation in organizations.
Perancangan Sistem Informasi Absensi Akuntansi STAIN Bengkalis Berbasis Android

Student attendance aims to monitor the level of student attendance and discipline students. Recording student attendance which is currently done manually on paper can be improved, so as to improve the quality of attendance data processing, service quality and systems in the STAIN Bengkalis Accounting study program. This research aims to develop an Android-based STAIN Bengkalis accounting attendance information design that can be used on lecturers' and students' mobile devices. SDLC is the method used to develop the design of Android-based STAIN Bengkalis accounting attendance information in this research. The Android-based STAIN Bengkalis accounting attendance information design can facilitate lecturers and students in carrying out the daily attendance process.
Analisis Penyebab Over Heating Untuk Tindakan Perawatan Pada Screw Compressor Di PT. Semen Padang Unit Indarung IV

&#x0D; Semen Padang Indarung IV unit has a screw compressor type compressor unit to produce high pressure air. In its operations, one of the Atlas Copco type compressor units often experiences over heating problems, namely the working temperature exceeds 1000 C. The method used is trouble shooting the compressor system, such as checking the lubricating oil, pressure, valves, working temperature and cooling system. , as well as overhaul maintenance actions if necessary. Based on the research results, it was found that the factors that cause overheating of the compressor are: Dirty air quality affects the condition of the air filter for air supply, limited space for placing the compressor causes the air supply to decrease, the oil filter has passed its useful life and is not suitable for use, and the oil cooler is clogged with scale, which hinders the oil cooling process. Based on this damage, recommendations for maintenance activities on the Atlas Copco Compressor are: maintaining air quality, periodically cleaning the tubes in the oil cooler, replacing the new oil filter according to compressor specifications, as well as comprehensive maintenance measures&#x0D;
Unveilling the Application, Advantage and Limitation of AR, VR &amp; MR in Immersive Learning Technologies in AEC

Immersive technologies are now implemented in construction in India. Immersive technology is an integration of virtual content with the physical environment in a way that allows the user to engage naturally with the blended reality. In an immersive experience, the user accepts virtual elements of their environment as part of the whole, potentially becoming less conscious that those elements are not part of physical reality. In this paper, some key terms /features such as applications, uses, benefits, challenges, limitations, education, and future aspects of AR/VR/MR/and XR have been highlighted vis-a-vis with the implication of each case in the construction industry, construction management, and construction project. The advantages and disadvantages, impact, and purpose of each technology are extended in this article for each technology. Emphasis is given to introducing and including each technology in tertiary education and curricula of undergraduate and postgraduate architectural engineering and construction management. Adoption of these technologies in construction leads to improvement in construction productivity, efficiency, low cost, and time, which is, in turn, beneficial to the owner, contractor, builders, and stakeholders on the implication of these immersive technologies.
Exploring the Performance of Container Runtimes within Kubernetes Clusters

The advent of cloud computing, with its Pay-As-You-Go model, has significantly simplified IT maintenance and revolutionized the industry. In the era of Microservices, containerized deployment and Kubernetes orchestration have permeated almost every working domain, drastically reducing the time to market for software releases. Kubernetes utilizes container runtimes to manage Containers, with the Container Runtime Interface (CRI) serving as a communication medium with low-level container runtimes such as runc and kata container. With the deprecation of Dockershim, developers are left to choose between CRI-O and Containerd, two CRI implementations. This study configures a Kubernetes cluster with both Containerd and CRI-O separately and analyzes performance parameters such as throughput, response time, CPU, memory, and network utilization. Additionally, we examine the impact of using runc and kata container runtimes together within the cluster. The study, conducted using a performance script created by JMeter, reveals that different container runtimes cater to distinct business use-cases and can complement each other when used together in a cluster environment. High compute applications are best run using runc, while high-security requirements are fulfilled by kata. The study provides a comprehensive performance comparison between Containerd and CRI-O, shedding light on the depth and versatility of container runtimes.
A Comparative Analysis of Data Stream Clustering Algorithms

This study compares the performance of stream clustering algorithms (DenStream, CluStream, ClusTree) on Massive Online Analysis (MOA) using synthetic and real-world datasets. The algorithms are compared in the presence on noise level [0%, 10%, 30%] on the synthetic data. DenStream epsilon parameter was tune to 0.01 and 0.03 to improve its performance. We use the performance evaluation metrics CMM, F1-P, F1-R, Purity, Silhouette Coefficient, and Rand statistic. On synthetic data, our results show that ClusTree outperformed CluStream and DenStream on the almost all the metrics except in Purity and Silhouette were DenStream performs better at noise levels (10% and 30%). ClusTree outperform CluStream and DenStream on Forest Cover type dataset on metrics CMM, F1-P, F1-R, Silhouette Coefficient, and Rand statistic with 90%, 74%, 77% and 89% respectively. However, the tune DenStream epsilon parameter shows some improvements. On electricity data, DenStream outperform CluStream and ClusTree at epsilon parameter (0.03 and 0.05) on metrics F1-P, F1-R, and Purity. The investigation of DenStream epsilon parameter (0.03 and 0.05) on RandomBRF Generator with noise level [0%, 10%, 30%] shows that DenStream with epsilon 0.03 outperform other parameter adjustment.
Decentralized App for music Streaming

Abstract: Music has always been a way for artists to express themselves. The music industry has grown exponentially in the last few years with the emergence of digital music streaming platforms. However, streaming platforms for streaming music are centralized, so artists only receive a small part of the revenue and still have no control. Respect their content. Cases of plagiarism are on the rise in the music industry, so there is a need to use technology that can help artists. Currently, there is a need for technological change that will give artists control and transparency over their content. According to the current system, artists are registered with record labels, streaming platforms, etc. must rely on many intermediaries such as to eliminate this problem, our article focuses on blockchain decision-making approach where artists and users can interact directly to upload, buy songs, and pay Royalties. Artists can submit their music to the DApp to ensure ownership and avoid the impact of piracy. Users can buy and stream music from independent artists or support artists with purchases and donations using Ethereum.