Reviewerly/exHarmony huggingface dataset:
Perancangan Desain User Interface Mobile Apps Pada Sistem Penanggulangan Gawat Darurat Terpadu D.I.Y

Background : Emergency incidents that occur in Indonesia are increasing day by day, both emergency incidents due to traffic accidents and incidents due to disease. The Indonesian government issued PERMENKES number 19 of 2016 concerning the Integrated Emergency Management System, in the creation of the SPGDT it is expected to be able to handle emergency cases in an integrated manner so as to minimize cases of disability and death. The Yogyakarta Special Region Health Service is currently running well in the implementation of SPGDT, but currently, the SPGDT application does not have the Mobile-Apps feature, especially on the Tracking Ambulance menu. With the ambulance tracking menu, people can easily make ambulance calls based on emergency cases that occur and also people don't need to worry if they find an emergency incident but the ambulance doesn't come, with ambulance tracking people can also see the movement of an ambulance that is on "standby" or in the process of “evacuating” an emergency event. Methods: the method in this research is the action research method. This action research method was chosen because the stages of action research start from diagnosis, planning, action and evaluation. Results: the results of this study, at the stage of identifying needs based on user actors. At the planning stage, what data flows are designed , created and the features needed . At the action stage, it produces a user interface design with Figma . At the evaluation stage, the final prototype score was assessed based on the System Usability Scale (SUS) questionnaire with the final score on the driver page prototype getting a final score of 62, while the prototype for paramedics got a final score of 71. And finally, the general public prototype got a final score of 69 Conclusions: The process of developing the design, planning and implementation of the mHealth application services requires the collaboration of various sectors, both from the user side from the health side. Feedback from various responses is the key to success to ensure the relevance and sustainability of the mHealth application services. Providing useful and easy-to-use and ensuring continuity of technical support can help smooth the process of using the mHealth application in day healthcare .
The Effectiveness of the Implementation of the Hospital Clinical Practice Based Simulation Model on the Practice Learning Outcomes of Nurse Profession Students During the Covid-19

Introduction: In connection with preventing the spread of Covid-19, all forms of education, including nursing education, are carried out by videoconference or e-learning (online). This also has an impact on nursing professional students where the application of skills for practice in hospitals is limited so that it greatly affects learning achievement. The application of the model is Hospital Clinical Practice Based Simulation an alternative for nurse students to practice during the Covid-19 pandemic so that learning outcomes can still be achieved. The purpose of this study is to analyze the effectiveness of the application of the HCPBS Model on the practical learning outcomes of Nursing Profession students at STIKES Suaka Insan Banjarmasin during the Covid-19 pandemic. Methods: This study uses a quasi-experimental design with posttest control group design approach. The research sample was students who underwent the nursing profession stage at STIKES Suaka Insan Banjarmasin Force X as many as 30 students. Sampling was carried out using the technique of Exhaustive Sampling. The statistical test used an independent sample t-test with a significance level of &lt;0.05. The research measuring tools are in the form of guidebooks and SOPs for the HCPBS model as well as learning outcomes by looking at assessments from cognitive, psychomotor, and affective aspects. Results: Based on the results of the study, it was found that the significance value of the p-value was 0.001 with a 95% confidence interval of 4.971-9.042. The difference in the mean value between the intervention group and the control group was 7.007. Where the average value for the intervention group is greater than the control group, namely 89.57 for the intervention group and 82.57 for the control group. Conclusion: So, it can be concluded that the Hospital Clinical Practice Based Simulation model is effective in increasing the practical learning achievement of the Nursing Professional Nurse STIKES Suaka Insan Banjarmasin during the Covid-19 pandemic, especially in the intervention group.
Android Snake Ladder on Triangle using TGT Learning Model to Increase Learning Motivation

The aims of this research were developing mathematics learning media based on android using Teams Games Tournament (TGT) learning type on triangle materials to improve learning motivation of class VII Junior High School students according to these validity, practical, and effective criterias through snake ladder game. The subject of this research were 28 students of class VII D SMP Negeri 1 Sedayu. This research based on ADDIE developing model contains 5 steps: (1) analysis, (2) design, (3) development, (4) implementation, and (5) evaluation. The results of this research showed that mathematics learning media based on android using Teams Games Tournament (TGT) learning type on triangle materials to improve learning motivation of class VII Junior High School students was completed on: (1) validity aspect through material expert validation with score 64 and categorized very good in criteria also media expert validation with score 64 and categorized very good in criteria. (2) practical aspect through mathematics learning media based on android tested to 28 students with student response questionnaire score was 1.053 and categorized good in criteria. (3) effectiveness aspect through increasing learning motivation students as much as 26% from 54% to 80%. So, it can be concluded that mathematics learning media based on android is appropriate for learning activity and beneficial to improve learning motivation students.
Code Switching and Code Mixing in English Language Learning during Online Learning in Covid-19 Outbreak

In learning English, language mixing is used more often than just monotonically using their mother tongue. A code is a kind of system used in communication between people. Both code mixing and code switching are oftentimes used by society while speaking in two or more languages, especially in the educational field. Therefore this study concern the use of code-switching in language learning. In determining the result of the study, the qualitative method is applied. The subject of the study is eleventh-grade students it is possible in finding code-switching in the form of daily dialogue and learning process. The techniques of data collection used observation. The result of the data analysis shows that code-switching is commonly done during the teaching and learning process, particularly for this online learning period which is impacted by the Covid-19 outbreak. This code-switching is necessary to conduct in avoiding misunderstandings in dialogue, increase the level of material comprehension, maximize classroom interaction, and create a good relationship between student and teacher.
On the Development of Customized Neural Machine Translation Models

Recent advances in neural modeling boosted performance of many machine learning applications. Training neural net-works requires large amounts of clean data, which are rarely available; many methods have been designed and inves-tigated by researchers to tackle this is-sue. As a partner of a project, we were asked to build translation engines for the weather forecast domain, relying on few, noisy data. Step by step, we developed neural translation models, which outper-form by far Google Translate. This paper details our approach, that - we think - is paradigmatic for a broader category of applications of machine learning, and as such could be of widespread utility.
Mobile Learning Trend in Vocational High School

This study synthesized the findings of studies on mobile learning trends in the vocational education learning process by scrutinizing journals from 2018 to 2022.This paper focused on the challenges and opportunities associated with the use of mobile in learning, as well as students' and teachers' readiness to use technology in the learning process.The trend of using mobile learning is growing, forcing distance learning to take place, and increasing the pressure on educational institutions to develop innovative learning and media that can still support the learning process.Given the trend of an increasingly dynamic and mobile society, as well as the demand for quality and diverse educational needs, the potential and prospects for developing mobile learning in the future are extremely promising.The learning concept is expected to encourage the creation of an effective and innovative learning environment to motivate students and teachers to learn.
MPSUBoost: A Modified Particle Stacking Undersampling Boosting Method

Class imbalance problems are prevalent in the real world. In such cases, traditional supervised algorithms tend to have difficulty in recognizing minority data because the models are likely to maximize prediction accuracy by simply ignoring the minority data. To address the class imbalance problem, various approaches have been tried, including data preprocessing techniques, cost-sensitive learning, and ensemble modeling. Recently, several hybrid models combining sampling methods with boosting have been proposed such as RUSBoost, LIUBoost, and CUSBoost. In this study, a novel under-sampling-based boosting method named MPSUBoost is proposed to handle the class imbalance problem. The proposed method is an integration of modified PSU and AdaBoost. The performance benchmark testing conducted on 35 highly imbalanced datasets indicated that the proposed method provided performance improvement over three existing methods (RUSBoost, LIUBoost, and CUSBoost). Moreover, we verified that the samples obtained by MPSUBoost effectively represented the given majority data, which led to a competitive advantage in the imbalanced data, particularly when true positives are imperative.
AUTOMATIC CHICKEN EGGS HATCHER USING DHT 22 SENSOR and DC MOTOR GEARBOX BASED ON ARDUINO

The hatching machine is one of the technological developments in the field of animal husbandry in increasing livestock productivity. Hatching eggs using an incubator is much more effective than natural/conventional breeding. The incubator is an incubator that has controlled temperature and humidity. Instruments used in the manufacture of hatching machines include a DHT 22 sensor which is used as a controller of temperature and humidity values, incandescent lamps are used as a heat source from the hatching machine, ultrasonic mist maker acts as a steam mist generator, DC motor is used as an egg turning rack driver, motor driver L298N acts as a DC motor movement controller, and Arduino Uno as a microcontroller that regulates all system work. This research was conducted with the aim of producing a hatching machine that is more complex and efficient. Based on data analysis carried out from the accuracy and thoroughness. The measurement accuracy ranges from 99.64% to 100%, while the measurement accuracy ranges from 99.64% to 100%, with an average measurement error of 0.178572%.
A Survey on Cervical Cancer Detection and Classification Using Deep Learning

Cervical cancer is one of the main cause of cancer death, impacting 570,000 people globally. Cervical cancer is caused by the Human Papillomavirus (HPV), which causes abnormal cell growth in the cervical region. Periodic HPV testing in woman has helped to minimize the death rate in developed countries. However, due to a shortage of affordable medical facilities, developing countries are still striving to deliver low-cost solutions. The most commonly used screening test for early detection of abnormal cells and cancer is the Pap smear test. This paper explores existing deep learning model and recent research works done using publicly accessible Intel and Mobile-ODT Kaggle dataset for cervix detection and classification and ensures that these automated technologies helps pathologist in providing fast and cost-effective results.
Semantic 3D Reconstruction of a Scene and Its Effective Visualisation

Single-image 3D scene reconstruction is required in multiple challenging tasks including mobile robotics, industrial monitoring and reconstruction of lost cultural heritage. While modern models demonstrate robust resolution of scene in real time with resolution up to 128 x 128 x 128 voxels, visualization of such detailed of a such detailed voxel model is challenging. A model with 128&lt;sup&gt;3&lt;/sup&gt; voxels contains 2097152 simple cubes 16M vertices. It is unfeasible for modern hardware to perform visualization of such voxel models in real-time. Hence a voxel model simplification technique is required to demonstrate reconstruction results in real-time. In this paper, we propose a new algorithm for voxel model simplification using predefined camera views. The algorithm reduces a rigid-body voxel model to a shell voxel model. It keeps only the voxels that are visible from the required view. We demonstrate the effectiveness of the proposed algorithm using a case study with a mobile robot and a state-of-the-art SSZ single-photo 3D reconstruction neural network. We generated a real and a virtual scene with various objects including a statue. We use a mobile robot equipped with a single camera to collect real and synthetic data. We train the SSZ model using the collected data. We developed a dedicated visualization software that implements our algorithm. The comparison of the visualization performance for the full model and its reduced version demonstrates that our algorithm allows to increase the performance by 420 times.
A Contrast-Pattern Characterization of Web Site Visitors in Terms of Conversions

The value of a company’s Web site depends on visitors performing actions that add value to the company. Those actions are called conversions. We present techniques for characterizing Web site visitors according to their conversions for more amenable interpretations by marketing experts. Existing Web analytics techniques are not designed to highlight the distinguishing characteristics of a class of visitors. Besides, there are no approaches for characterizing classes of visitors that take into account specific business goals. In this paper, we introduce a means of characterizing Web site visitors. To find what the different segments of visitors have or do not have in common, we first separate visitor sessions by conversions, and then for each class, we mine patterns to contrast with others. To mine patterns, we use PBC4cip, which is a contrast pattern-based classifier. Our pattern mining strategy is to use each conversion as a binary class at a time. We select the contrast patterns in a representative proportion of sessions (at least 10%). Our results show that a few patterns are enough to characterize a visitor class; since each class is associated with a conversion, an expert can easily draw conclusions as to what makes two classes different from each other. Further work will involve incorporating information from other sales channels and completing the analysis provided by existing techniques.
Transmission of Language Politeness to Students in Organizational Activities

This research is quantitative research using descriptive analysis which aims to analyse the process of transmitting language politeness values.Data collection is done by distributing questionnaires in the form of open questions to students who are actively participating in the organization.Based on the results of the study, it was found that 36.36% of students explained that politeness is an attitude, ethics, character, and action according to applicable norms; 40.90% explained that politeness in language is speech that is gentle, kind, polite, and does not use a high tone or yell.In addition, the results of this study also explained that 22.7% of students explained that their language politeness was inherited from their parents by giving examples to their children when talking, especially with older people.27,27% students explained how to learn politeness by watching and paying attention to people who spoke politely, imitated, and learned to use the Javanese language Krama Inggil.
“Hi, Google! Tell Me A Joke”: How Google Assistant Creates Its Jokes

Artificial intelligent-based application helps people in many ways, one of which telling them jokes. This study aims at (1) investigating the types of jokes on Google Assistant application, and (2) describing linguistic aspects used in the jokes. There were several steps in conducting this study. Firstly, the data of this study were the jokes taken from “tell me a joke” feature on Google Assistant. As many as 58 jokes were collected as the data. Then, the data were coded and analysed based on its linguistic aspects in terms of sounds, meanings, and word formations. After all data were analysed, conclusions were drawn. There are two forms of jokes in this application namely riddle and one liner. In riddle, the jokes are presented in question-answer form, whereas one liner joke only consists of one or two sentences. There are several linguistic aspects in creating the jokes, namely homonyms, minimal pair, substitution of sounds, onomatopoeia, phrase and words with similar pronunciation, idiomatic phrase, addition of sound and word combination. Among those aspects, homonyms are the most frequently utilized in the jokes. Jokes are beneficial for language learners to learn the real use of the language, thus further studies on jokes are suggested.&#x0D;
Analisis Tingkat Motivasi Belajar Siswa Dalam Pembelajaran Daring Pada Mata Pelajaran Matematika

The purpose of this study was to find out how the level of sudent motivation in online learning in mathematics in class XI MIPA SMA Negeri 1 Weru in the academic year 2019/2020 and to find out how students’ motivation to learn in each indicator. This research uses descriptive method with a qualitative approach. Data collection techniques used in this study in the form of a questionnaire. The result showed that the level of student motivation in online learning in mathematics in the class XI MIPA of SMA Negeri 1 Weru in academic year 2019/2020 was included in the medium category. With the percentage of students’ motivation in each indicator that is in indicator 1 (Perseverance in doing the assignment) of 66,53% so that it is included in the sufficient category, in indicator 2 (Resilient in facing difficulties) by 69,19% so that it is included in the sufficient category, at indicator 3 (Happy working independently) by 68,01% so that it is included in the sufficient category, in indicator 4 (There is encouragement and needs in learning) by 67,47% so it is included in the sufficient category, indicator 5 (Showing interest) 0f 55, 38% so it is included in the category of not good, in indicator 6 (Can maintain confidence) of 69,35% so that it is included in the sufficient category, in indicator 7 (Happy to find and solve answers to mathematical problems) of 64,11% so that it is included in enough categories.
Pelatihan Penggunaan Aplikasi Bandicam dan Quizziz dalam Pembelajaran bagi Guru-guru SDN Menteng Atas 14

School from home makes all learning activities carried out from home. However, the limited skills of teachers in using ICT-based learning media become an obstacle during online learning. Thus, training on the use of the Bandicam and Quizziz applications in learning for teachers of SDN Menteng Atas 14 is important to do during the Covid-19 pandemic. With this activity, it is hoped that teachers will be able to package interesting and fun learning. The method of implementing this community service activity is in the form of an online seminar. Seminar with the theme "Training on the Use of ICT-Based Learning Media (Bandicam and Quizziz)". held on Saturday, February 27, 2021 through the Zoom Cloud Meeting application with 25 participants. The first material discusses the development of learning media using the Bandicam application. The second material is about strategies for using interesting learning media. The third material is about the practice of using Quizziz in learning. This event runs smoothly and gives new enthusiasm for the participants in planning, designing, and implementing creative, inovative and fun learning so that students do not get bored easily in undergoing online learning so that learning objectives can be realized. The participants gave positive responses during the activity in the form of great enthusiasm in practicing the Bandicam and Quizziz learning media even though some participants were network constrained.
ANALISIS KESULITAN MENULIS RINGKASAN BACAAN PADA TEMA 8 SUBTEMA 2 SISWA KELAS IV MADRASAH IBTIDAIYAH

The problem that is often encountered in learning Indonesian at the basic level is the ability to write. One of the difficulties faced by class IVB MIN 1 Rembang students is the difficulty in writing summary readings. This study aims to determine the difficulty of writing a summary and to find out the factors causing the difficulty of writing a summary in class IVB MIN 1 Rembang. This research is a qualitative descriptive research with case study method. Data collection techniques by means of observation, interviews and document analysis. Data analysis techniques from data reduction, data presentation and verification. The results showed that there were difficulties experienced by students in writing summaries, namely, lack of understanding difficult vocabulary, difficulties in writing what they thought in written form and understanding long readings. The causative factor is the students' internal and external factors. Internal factors include difficulty concentrating during learning, boredom while studying and lack of understanding of the material. External factors, namely, teaching methods and learning media.
THE EFFECT OF PICTURE WORD INDUCTIVE MODEL (PWIM) STRATEGY TOWARD STUDENTS’ MOTIVATION IN LEARNING VOCABULARY

This study aimed to find out is there any signifiacnt effect or not Picture Word Inductive Model (PWIM) toward students’ motivation in studying vocabulary at second grade students of SMPN 2 Terara in academic year 2018/2019. This research was an experimental research (quasi-experimental with nonequivalent control group design). The population of this research was all of the second grade students of SMPN 2 Terara which consist of four classes. The samples were VIII B students’ as experimental group and VIII C students’ as control group. They were chosen by using purposive sampling technique. Experimental group was treated by using Picture Word Inductive Model (PWIM) and control group was treated by Contextual Teaching and Learning (CTL) that usually used by the teacher. The instruments that were used were vocabulary test and questionnaire. The researchers used SPSS 25 to compute the data. The results of the research were as follows: the data was analyzed using t-test. The result of the research showed that, there was positive effect of Picture Word Inductive Model (PWIM) strategy toward students’ motivation in vocabulary mastery. The result of t-test calculation showed that t-test was higher than t-table (t-test = 6,119 and t-table = 2,021) at confidence of interval 0.05 (95%), df = 23+23-2=44. Therefore, Null Hypothesis (Ho) was rejected and Alternative Hypothesis (Ha) was accepted. From the result of data analysis above, the researchers concluded that there was a significant effect of Picture Word Inductive Model (PWIM) toward students’ motivation in vocabulary mastery at second grade students of SMPN 2 Terara in academic year 2018/2019.