Reviewerly/exHarmony huggingface dataset:
Development of web-based digital libraries as learning resource facilities in elementary schools

The development of Information and Communication Technology (ICT) has greatly influenced the world of education. One of the benefits of using ICT in education is that it makes it easier to find learning resources that it’s used in the learning process is the school library through digital libraries. The schools should develop digital libraries with facilities adequately. This study aimed to develop prototypes of web-based digital library products suitable as learning resources at public elementary school. The type of research used was research and development (R&amp;D) using the PPE (Planning, Production, and Evaluation) model, carried out at SDN Sindang III, Majalengka Regency. The subjects in this study were the school principal, ten teachers, and 43 students. The research instrument used observation, interview, and product validation sheets. Research data were analyzed qualitatively and quantitatively. The results of this research and development are web-based digital library products containing various textbooks adapted to the school curriculum, consist of 2013 curriculum books, Kurikulum Merdeka’s, numeracy literacy modules, children's story books, learning videos, and teacher-supporting books. The product validation by three experts and two practitioners using the DigiQUAL instrument, which consists of seven aspects, an average score of 4.4 is obtained, which is in the excellent category. Conclusion this study is innovation web-based digital library product can be a learning resource at SDN Sindang III, Majalengka Regency.
Understanding Stakeholders’ Perspective on An Innovative Business Model for Pediatric Immunization Records: A Single Case Study

The purpose of this qualitative case study is to explore the potential value of an innovative business model on pediatric immunization record management which will serve as the basis for the development of a digital platform for the use of pediatric consultants and medical secretaries at a private secondary hospital in Quezon City. The study utilized a qualitative case study involving the pediatric consultants and medical secretaries of a private secondary hospital in Quezon City. Qualitative data for this study were gathered through in-depth, semi-structured interviews, focus group discussions, documents, journaling, and observations. Results have shown that pediatric consultants and medical secretaries follow only one way of arranging patients' records which is through alphabetical order using the surname. Many clinics and hospitals still rely on paper-based medical records to document patients' information. All participants shared the same difficulties and sentiments when it comes to the problems they have in the current way they deal with immunization records. Based from the statements of the participants, results revealed that pediatric consultants and medical secretaries support and are in favor of the use of a web-based record management system. However, some participants stated their apprehensions for the security of patient information. Further study that focuses on formal training is recommended to increase the confidence of the healthcare workers in utilizing digital record management systems and intense exploration of the potential challenges in adapting a digitized records management system must be conducted.
An Impact of Distance Learning for Elementary School Students in SDN 11 Teluk Betung Pesisir Selatan

This study aims to determine how the impact of distance learning experienced by teachers and students during the COVID-19 pandemic. This study uses qualitative research methods, where in collecting information data with interview techniques, in order to find data on relevant matters. The subjects of this study were students of SDN 11 Teluk Betung Pesisir Selatan. The results showed that the distance learning process did not run optimally and there were several obstacles for teachers and students in distance learning.
Meningkatkan Kemampuan Membaca Permulaan dengan Media Kartu Huruf pada Siswa Kelas II Sekolah Dasar

The study was motivated by the low initial reading ability of students. The purpose of this research was to determine the improvement of students' initial reading skills using letter card media. The research employed a classroom action research method with grade II B students as the subjects. The object of the study was the students' initial reading ability through the implementation of letter card learning media. Data collection techniques included tests, observation, and documentation. The research instruments consisted of oral tests, checklist sheets, and observation sheets. The results of the study revealed that the use of letter card media significantly improved the initial reading skills of grade II B students at SD Negeri 19 Tanjung Tengang. The completion rate of students in cycle 1 was 54.16%, and in cycle II, it increased to 87.50%. The significant percentage increase from cycle I to cycle II led to the conclusion that students' initial reading skills can be effectively enhanced through the implementation of letter card media.
Pengembangan Media Komik dalam Pembelajaran Menulis Teks Anekdot untuk Meningkatkan Pemahaman Siswa Kelas X SMA Swasta Al-Hidayah Medan

The purpose of this research was to develop and assess the feasibility of comic media for teaching anecdote writing to Class X students at SMAS Al-Hidayah Medan. Following the Research and Development approach by Borg and Gall, this study involved seven steps: research and data collection, planning, product draft development, preliminary field testing, revising trial results, main field testing, and improving the operational product. The sample comprised 24 students from a population of 46. The assessment results indicated that the developed product was deemed feasible. Material experts I and II rated it as "Decent" (78%) and "Very Eligible" (95%) respectively. Media experts I and II assessed it as "Very Eligible" (90%) and "Decent" (80%) respectively. Indonesian language teachers' response was "Very Eligible" (94%), and students' response was also "Very Eligible" (90%).
Causal representation based on a GAE embedded autoencoder for domain adaptation

&lt;p&gt;Domain adaptation enables accurate predictions despite differing distributions between the source and target domains by learning domaininvariant representations. In some applications when there are confounding factors, some domain-invariant features correlated with the samples in the source domain may not be inherently relevant to the target domain. Causal inference uncovers causal relationships, allowing us to reveal the underlying patterns and mechanisms behind the data. However, most existing causal inference algorithms have limitations when applied to high-dimensional datasets with nonlinear causal relationships. In this work, a new causal representation method based on a Graph autoencoder embedded AutoEncoder, named GeAE, is introduced to learn invariant representations across domains. The proposed approach employs a causal structure learning module, similar to a graph autoencoder, to account for nonlinear causal relationships present in the data. Moreover, the cross-entropy loss as well as the causal structure learning loss and the reconstruction loss are incorporated in the objective function designed in a united autoencoder. In this way, it is capable of handling highdimensional data and enhancing the accuracy of crossdomain predictions through the use of causal representations. Experimental results on generated datasets and three real-world datasets demonstrate the effectiveness of GeAE in comparison with the state-of-theart methods. &lt;/p&gt;
Pengaruh Media Blog Terhadap Kemampuan Menulis Teks Cerpen pada Siswa Kelas Xl MAS Al-Washliyah Tebing Tinggi Tahun Pembelajaran 2022-2023

This study examines the impact of using blog media on students' short story writing skills in class XI at Mas Al-Washliyah Tebing Tinggi during the 2022-2023 academic year. The quantitative descriptive method was employed, with a total sample size of 32 students from both experimental and control classes. The data was collected through pretest and posttest essays. Posttest scores in the experimental class showed 12% in the very good category, 75% in the good category, 13% in the sufficient category, and 0% in the less and very less categories, with an average score of 75.25. On the other hand, the control class demonstrated 38% in the good category, 38% in the sufficient category, 19% in the less category, and 5% in the very less category, with an average score of 64.87. The results indicated that the experimental class, which utilized blog media, outperformed the control class that used conventional methods. Therefore, it can be concluded that blog media positively influences learning outcomes in writing short stories.
SCAECE:Self &amp; Co-Attention-based approach for Emotion Cause Extraction for moderate size dataset

&lt;p&gt;Emotion cause is an essential feature in generating empathetic responses. The process of finding the emotional causes for a particular is emotion cause extraction. This work proposes a multi-attention-based approach that utilizes textual and numerical features to enhance the cause extraction task. We target the usage of moderate-size datasets to show the efficiency of our model, as generally, the conversational datasets in English are of the mentioned size. In our work, we prove the efficiency of our model on the RECCON dataset against various state-of-the-art models and notice a significant amount of improvement. &lt;/p&gt;
Using the Modified Artificial Bee Colony Algorithm to Find the Non-Archimedean Epsilon for Evaluating the Efficiency in DEA

The artificial bee colony algorithm is one of the population-based optimization methods inspired by the evolutionary principles of the social behavior of bees. On the other hand, one of the sub-fields of operations research science is data envelopment analysis. There are some difficulties in DEA models for selecting the appropriate numerical value for an infinitesimal non-Archimedean epsilon. So far, various methods have been proposed to solve this problem and choose the suitable non-Archimedean epsilon. In order to solve the problem, the artificial bee colony algorithm (ABC), and modification of the original ABC algorithm (MABC) are adopted and proposed in this paper. The impacts of our proposed algorithms on the suitable non-Archimedean epsilon by solving only one linear programming (LP), instead of n LP are investigated. Finally, the performance of the proposed algorithms is evaluated by comparing the solutions obtained from GAMS software based on the presented examples.
A Study on the Effects of University PBL (Problem-Based Learning) Classes on Learning Motivation and Learning Strategies

The purpose of this study was to explore the effects of university PBL classes on learners' learning motivation and learning strategies.The study was conducted during the second semester of 2022, targeting 56 students from the College of Education at A University in Chungbuk.To evaluate the students' learning motivation learning strategies before and after PBL classes, the MSLQ(Motivated Strategies for Learning Questionnaire) was used.Corresponding paired t-tests were conducted to analyze the effects of PBL classes on 6 sub-factors of learning motivation and 9 sub-factors of learning strategies.The main results of the study were as follows.First, after participating in PBL classes, learners' self-efficacy, a sub-factor of learning motivation, improved, while test anxiety decreased.Second, after PBL classes, critical thinking, and metacognition, sub-factors of learning strategies, showed improvement.Based on these findings, PBL classes have been found to improve higher-order thinking skills, which are critical skills for future talents.Therefore, universities that aim to cultivate future talent should actively incorporate PBL into their educational practices.This study is significant in that it compared and analyzed PBL classes before and after in terms of specific sub-factors of learning motivation and learning strategies among university students.It specifically revealed the direct effects of PBL classes on different factors of learning motivation and learning strategies.
Discrete sequence rearrangement based self-supervised chinese named entity recognition for robot instruction parsing

Named entity recognition (NER) plays an important role in information extraction tasks, but most models rely on large-scale labeled data. Getting the model to move away from large-scale labeled datasets is challenging. In this paper, a SCNER (Self-Supervised NER) model is proposed. The BiLSTM (Bidirectional LSTM) is adopted as the named entity extractor, and an Instruction Generation Subsystem (IGS) is proposed to generate "Retelling Instructions", which analyzes the similarities between the input instructions and "Retelling Instructions" as the losses for model training. A series of rules based on traditional learning rules have been proposed for discrete forward computation and error backpropagation. It mimics language learning in human infants and constructs a SCNER model. This model is used for robot instruction understanding and can be trained on unlabeled datasets to extract named entities from instructions. Experimental results show that the proposed model is competitive with the supervised BiLSTM-CRF and BERT-NER models. In addition, the model is applied to a real robot, which verifies the practicality of SCNER.
LiDAR-based drone navigation with reinforcement learning

&lt;p&gt;Reinforcement learning is of increasing importance in the field of robot control and simulation plays a~key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number of published scientific papers involving this approach. In this work, an autonomous drone control system was prepared to fly forward (according to its coordinates system) and pass the trees encountered in the forest based on the data from a rotating LiDAR sensor. The Proximal Policy Optimization (PPO) algorithm, an example of reinforcement learning (RL), was used to prepare it. A custom simulator in the Python language was developed for this purpose. The Gazebo environment, integrated with the Robot Operating System (ROS), was also used to test the resulting control algorithm. Finally, the prepared solution was implemented in the Nvidia Jetson Nano eGPU and verified in the real tests scenarios. During them, the drone successfully completed the set task and was able to repeatably avoid trees and fly through the forest.&lt;/p&gt;
Vocabulary Enrichment and Student’ Communicative Competence: The Case in Task-Based Language Teaching

In order to realize and support Indonesian national educational program of MBKM, every higher educational institution is recommended and stimulated to implement learning model of task-based language teaching (TBLT). This study investigated how enriching vocabularies and giving other prompt such as driving question words effective for students’ speaking performance, such as fluency. This was a qualitatively designed study. One class semester two students majoring in civil engineering department were involved as research participants. Learning material in the form of snapshot consisting of pictures was design to bridge the students thought to the whole learning materials. Snapshot without vocabulary enrichment and driving questions was tried in the first two sessions. Discussion upon the lesson was intensively undertaken to know why students hesitated and were doubtful to speak. Observation results combined with students’ perception concluded that enrichment of vocabularies and stimulating questions were found effective to increase students’ speaking performance, learning motivation and enthusiasm. Moreover, by practicing in front of their group and by succeeding in perform such task made them more stimulated to do better. Therefor made their learning meaningful.
The use of the C4.5 Algorithm for Applications Initial Assessment of Disabilities People the Case Study of the Ministry Social Center Wyata Guna Bandung

The development of information technology is snowballing, data is processed quickly and practically. Several problems often arise. Social instructors often find it difficult to process the data to determine which social service decisions should be provided. Persons with Disabilities are any person who experiences physical, intellectual, mental, and sensory limitations in the long term in interacting with the environment and may experience obstacles and difficulties in participating fully and effectively with other citizens based on equal rights. The Initial Assessment Form is a decision-making instrument through a process called the Initial Assessment. Later, the need for Social Welfare Services (PPKS) can be known as whether the quality is ready to be educated and included in the residential, community, or family categories. The method in this research is to use the Engineering Research Method. The decision tree model produces an accuracy level of 86.6%, the test data is suitable, and 13.3% is not suitable. In determining the service category and calculating the C4.5 Algorithm, it is better to add the number of datasets so that the accuracy of the value is higher.
A Comprehensive Comparison of Pre-training Language Models

&lt;p&gt;Recently, the development of pre-trained language models has brought natural language processing (NLP) tasks to the new state-of-the-art. In this paper we explore the efficiency of various pre-trained language models. We pre-train a list of transformer-based models with the same amount of text and the same training steps. The experimental results shows that the most improvement upon the origin BERT is adding the RNN-layer to capture more contextual information for short text understanding. But the conclusion is: There are no remarkable improvement for short text understanding for similar BERT structures. Data-centric method[12] can achieve better performance.&lt;/p&gt;
Type Analysis of Speaking Performance Assessment Task in English for Nusantara Textbook

One of the key factors in the success of learning English is the use of textbooks. The English textbook entitled "English for Nusantara SMP/MTs Class VIII" is one of the textbooks used in many schools as a guide for teachers and students in teaching and learning English. Although English for Nusantara textbooks have been widely used, there is no research has focused on the analysis of speaking assessment tasks in this textbook. Therefore this study aims to analyze the task of assessing speaking skills in Nusantara English textbooks. This study use a qualitative approach. The subject of this research is Nusantara English textbooks used in the context of learning English in Indonesia. Data collected through document analysis will include task descriptions, types of assessment, and instructions given for each task. The collected data will be analyzed descriptively to identify the types of assessment included in the speaking tasks. The results of this study show that intensive assessment tasks are the most common in this book. However, this study also found a limited variety of activities in speaking assessment task. The implications of the results of this research are important in the development of textbooks and the improvement of learning speaking skills in the context of English in Indonesia.
Improving Students’ Motivation in Learning English through Gamification

In the event of world pandemic of COVID-19, emergency remote learning settings have become normalized in Indonesia and it has affected students’ motivation in learning. Educators around the world have found a way to enhance students’ motivation through gamification. Therefore this study aims to improve students’ motivation in learning English through gamification in online learning settings. This study was conducted at a Private Junior High School with 36 eighth graders. The method used in this study is Classroom Action Research (CAR). After conducting two cycles in the implementation phase, the result, supported by the questionnaire, interview, and observation data, shows how gamification is able to improve students’ motivation. In collecting the data, qualitative and quantitative method were used. The questionnaire as the quantitative data, consist of subdimensions of intrinsic and extrinsic motivation. As for the qualitative method, to identify the students’ problem, observation and an end-of-cycle interview were conducted. Through two cycles, the implemented action was able to improve students’ motivation in English class and enlighten the ambience of the class. Although students’ response to gamification was highly favorable, the findings also suggest a new issue. Some students have developed a speech anxiety by learning online due to fear of making mistakes and a feeling of embarrassment. The current study has been able to shed lights on the benefits of gamification in a teaching and learning process of English Language Teaching (ELT).
Multimodal Analysis of Mie Sedaap Advertising

One of the texts has a complex meaning is advertisement, both print media advertisements and electronic media advertisements. The complexity of meaning is due to conveying messages in advertisements not only using language elements but also nonverbal language elements and other visual means. Therefore to understand the complexity of meaning, it is necessary to carry out a multimodal analysis in the advertisement. This study aims to analysis of Mie Sedaap advertisements. Advertisements, both print media advertisements and electronic media advertisements, are texts that have a complex meaning. Therefore, to understand the complexity of meaning, it is necessary to do a multimodal analysis of the advertisement. The multimodal analysis discussed in this paper uses the theory of Systemic Functional Linguistics (SFL). This study used a descriptive qualitative method and observation through video advertisements for Mie Sedaap. The data were collected from observations through video advertisements for Mie Sedaap. The findings of the study were analyzed using qualitative data analysis, including data reduction, data display, and conclusion. The research results show that Mie Sedaap advertisements have a multimodal semiotic system that includes linguistic, visual, audio, gestural, and spatial elements.
Implementasi Sensor PIR Dan Kamera Untuk Keamanan Ruangan Berbasis Internet of Things

Room security is a very important thing to prioritize. One of the solutions to prevent crime levels needs to be equipped with a security device or a device capable of monitoring a room with the ability to detect the presence of an unwanted person. Therefore, this study designed a tool to monitor rooms based on the Internet of Thing (IoT) with surveillance cameras, which is one way to monitor the situation in a room. This system combines the use of the pir sensor, the raspberry pi camera module, and the raspberry pi, in order to be able to find out the condition of the room in the form of photos sent and also use bot features on internet applications, namely telegram messenger. This system is more efficient because it uses storage from telegram, and also the system will send notifications via telegram bots. So that the user can take action as soon as possible if things happen that are not desired. When the pir sensor detects movement in the room, the camera takes a photo and then sends it to the user's telegram bot account and the buzzer sounds as an early prevention of crime.