Reviewerly/exHarmony huggingface dataset:
PENERAPAN MODEL PEMBELAJARAN DISCOVERY LEARNING BERBASIS SMARTPHONE UNTUK MENGUPAYAKAN MINAT BELAJAR PADA PEMBELAJARAN MATEMATIKA [APPLICATION OF SMARTPHONE-BASED DISCOVERY LEARNING MODELS TO CREATE INTEREST IN LEARNING MATHEMATICS]

&lt;p&gt;The results of the PISA study in 2018 showed that the mathematics ability of Indonesian students was still in the low performance category. One of the factors that causes this is the lack of student interest in learning mathematics. Interest is very important because it is interest that encourages students to be active and act in learning. This study aims to see whether the application of a smartphone-based &lt;em&gt;discovery learning&lt;/em&gt; model can help increase interest in learning mathematics. The research method used is a descriptive qualitative research method using several research instruments. This research was conducted in one of the schools in South Tangerang at the junior high school level. The instruments used by the authors are observation sheets and reflection sheets and mentor feedback sheets. The results of this study concluded that the application of a smartphone-based &lt;em&gt;discovery learning&lt;/em&gt; model is able to effect student interest in learning, which is shown by an increased willingness to learn, pleasure in learning, and student participation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;BAHASA INDONESIA ABSTRACT: &lt;/strong&gt;Hasil studi PISA pada 2018 menunjukkan kemampuan matematika siswa Indonesia masih berada dalam kategori &lt;em&gt;low performance&lt;/em&gt;. Salah satu faktor yang menyebabkan hal ini adalah kurangnya minat siswa terhadap pembelajaran matematika. Minat menjadi hal yang sangat penting karena minatlah yang mendorong siswa untuk aktif dan bertindak dalam pembelajaran. Penelitian ini bertujuan untuk melihat penerapan model pembelajaran &lt;em&gt;discovery learning&lt;/em&gt; berbasis &lt;em&gt;smartphone &lt;/em&gt;dapat membantu mengupayakan minat belajar pada pembelajaran matematika. Metode penelitian yang digunakan adalah metode penelitian kualitatif deskriptif dengan menggunakan beberapa instrumen penelitian. Penelitian ini dilakukan di salah satu sekolah swasta di Tangerang Selatan pada jenjang SMP. Instrumen yang digunakan oleh penulis adalah lembar observasi, lembar refleksi, dan lembar umpan balik mentor. Penelitian ini memberikan hasil bahwa penerapan model pembelajaran &lt;em&gt;discovery learning&lt;/em&gt; berbasis &lt;em&gt;smartphone&lt;/em&gt; mampu mengupayakan minat belajar siswa yang ditunjukkan dengan meningkatnya kemauan untuk belajar, rasa senang siswa dan partisipasi siswa.&lt;/p&gt;
SISTEM PAKAR IDENTIFIKASI PENYAKIT KUCING MENGGUNAKAN METODE FORWARD CHAINING BERBASIS ANDROID

Many cats are kept by Indonesians. However, they are unable to adequately care for them, hence a tool that can identify and explain cat ailments is required. Making applications that make use of expert systems based on Android can do this. Forward chaining will be the research technique employed in this application to build the system. This Android software aids in the diagnosis of illnesses in cats. Additionally, expert system applications can make use of the forward chaining strategy.
Spatial Modeling of Flood Affected Areas of Krukut River in Pela-Mampang Segment, South Jakarta, Indonesia

Flooding is one of the most common natural disasters in Indonesia, and the capital city of DKI Jakarta is no exception. Every year, there are always areas that experience flooding, mainly triggered by the overflow of flowing rivers. Jakarta itself is located in a downstream area consisting of swampy areas that are floodplains. One of the river basins that most often experiences flooding is the Krukut River. This is mainly triggered by the high value of rainfall which can reach more than 200 mm in a day. Massive development along the riverbanks has exacerbated the flooding, especially in the Pela Mampang segment which includes Pela Mampang Village, Mampang Prapatan Subdistrict and Petogogan Village, Kebayoran Baru Subdistrict. This research models two-dimensional flood inundation using the HEC-RAS program to describe the distribution of potential floods for return periods of 2, 5, 10, 25, 50 and 100 years. In addition, a spatial analysis of the affected infrastructure up to the RT level was also conducted to provide an overview of the extent of inundation using 4 types of classifications (low, medium, high and extreme). The results showed that 19 out of 150 RTs in Pela Mampang urban village and 33 out of 79 RTs in Petogogan urban village were flooded with a total inundation area of 100-year flood reaching 39.58 ha. The affected infrastructure reached 1,903 units with the area of inundated roads reaching 3.27 ha. It is hoped that this research can provide input for future infrastructure planning and river management in order to anticipate and mitigate disasters better.
PENGARUH PEMBELAJARAN BERBASIS WEBSITE TERHADAP HASIL BELAJAR SISWA

This study aims to determine the effect of web-based learning on student learning outcomes. Learning outcomes are the achievement of student development standards to participate in learning activities over a certain period of time. Learning outcomes can measure students' ability to set learning objectives. This research was conducted at SMKN 2 Rambah using a website-based learning model. The purpose of this research is to reveal and analyze the learning process using the website. The method used in this study is the method by collecting data to answer questions using a qualitative research approach. The targets in this study were 20 TKJ students. The results of the study show that website-based learning has less effect on student learning outcomes. During learning students are effective in learning and students understand the material displayed. The results of the study show that the website-based learning process is effective in improving student learning outcomes
PERENCANAAN SISTEM PEMESANAN MAKANAN DI RUMAH MAKAN BERBASIS ONLINE MENGGUNAKAN MOBILE ANDROID DENGAN METODE BARCODE

The current development of information technology has affected various sectors of life, including the culinary sector. Modern restaurants and restaurants have switched to online-based food ordering systems. The purpose of this research is to design and develop a food ordering system at an online-based restaurant using an Android mobile with the barcode method. The barcode method is used to facilitate the food ordering process and assist users in making transactions quickly and efficiently. The results of system testing and validation show that an online-based food ordering system using an Android mobile with the barcode method can increase efficiency and effectiveness in the food ordering process. This research is expected to provide contributions and solutions for the culinary industry in utilizing information technology to improve service quality.
EFEKTIVITAS MEDIA PEMBELAJARAN ARTICULATE STORYLINE UNTUK MENINGKATKAN PRESTASI BELAJAR SISWA

Learning network system administration, most students are less enthusiastic and focused on learning and their learning achievements are also still many below the Minimum Completeness Criteria (KKM), this is evidenced from 18 class X TKJ students only 10%, who passed this subject, factor what affects this is that they are lacking in terms of understanding the material if it is only conveyed through explanations using modules or e-modules that are less interesting. This research aims to improve student learning on class X TKJ network operating system material at Muhammadiyah Aimas Vocational School. The type of research used is MDLC (Multimedia Development Life Cycle). The results of the trial assessment of several aspects of the media program 96.6% received a very good category, the instrument rating aspect with a percentage of 100% was in a very good category, and for material aspects it received a percentage of 94.6% which also received a very good category, the last one was a response assessment students to the media and get a percentage of 79% with a very good category. the results of the media effectiveness test from the pretest test with an average of 32.00 and the posttest test with an average of 80.28, indicate an increase in student achievement performance in the class X TKJ Network Operation System material at SMK Muhammadiyah Aimas.
Focus Group Discussion on Students’ Perception of Gamification in Learning Cohesion in Arabic

Learning languages had been taught as a passive process. But in this era of Information and Communication Technology, a lot of educators use the technology provided on the Internet to attract students to focus on learning. Nowadays, gamification is widely used by educators while teaching online including Arabic language. Thus, this study aims to identify the students’ perception on gamification in learning Arabic cohesive devices. This study employed qualitative approach which the researchers used focus group discussion as a mode of data collection. The sampling method used is convenience sampling which all of them are students at Universiti Sains Islam Malaysia (USIM), 2nd year students, semester 2, 2018/2019 taking Arabic subject. In this study, researchers managed to recruit 14 participants for 3 focus group discussion whereby 5 participants respectively in the first group and 4 participants in another group. From the result of the research, the process of learning Arabic cohesive devices in the Arabic language takes place with all enjoyment which increases the students’ interest for learning.
An Error Analysis In Writing Short Essay Made By The First Semester Students English Department Nommensen University

Writing is one of the learning topics taught at the Department of English Education at HKBP Nommensen University Medan. Meanwhile, based on the writer‟s experience the writer still made an error when writing an essay. The aims of this study are to find out the dominant types of error and the causes of the error. This study used qualitative descriptive as a case study. the population of this study was the 1sT semester students English Department of Nommensen University from groups A and B consist of 15 students. The data was collected from the students‟ tests and interviews. According to the result, there were four types of errors by using the appropriate tenses in writing a short essay made by the first semester students, those were (1). Omission (17.2%), (2). In Addition (10%), (3). Misformation (69.1%), and (4) Misordering (3.7%), the dominant types of error by using the appropriate tenses in writing a short essay made by the first semester students English Department Nommensen University on their short essay was Misformation (69.1%). The cause of the error by using the appropriate tenses in writing short essays was an Interlingual and Intralingual Transfer. this study indicates that there are still errors in writing short essays, which dominate by misformation errors or errors in word structure, which occurs because of interlingual and intralingual transfers or errors in the intended target language.&#x0D;
Assessing the Efficacy of Synthetic Data for Enhancing Machine Translation Models in Low Resource Domains

An artificially generated dataset mimics real-world data in terms of its statistical properties, but it contains no real information. Data around rare occurrences like Covid-19 pandemic is difficult to capture in real-world data due to their infrequent nature. Additionally, cost involved and time-consumption to gather real world data is a big challenge. In such cases, synthetic data can help create more balanced datasets for model training. This project investigates the effectiveness of using synthetic data for tuning machine translation models when training data is limited. The Covid-19 domain is chosen considering the urgency and importance of the global accessibility of information related to the pandemic. TICO-19, a publically available dataset was effectively formulated to cater to this need. The medical terminologies were extracted and passed to OpenAI API to generate training language pair data. The fine-tuned davinci model is then verified with blind test data provided under TICO-19 for translation from English to French. SacreBLEU score is used to compute the translation quality, the fine-tuned model has a significantly higher BLEU score of 19.54 in comparison to the base model with a BLEU score of 0.44. The adapted model also has a comparable score to the next-generation version of davinci with a BLEU score of 22.29.
A Deep Learning Emotion Classification Framework for Low Resource Languages

Emotion classification from text is the process of identifying and classifying emotions expressed in textual data. Emotions can be feelings such as anger, joy, suspense, sadness and neutral. Developing a machine learning model to identify emotions in a low-resourced language with a limited set of linguistic resources and annotated corpora is a challenge. This research proposes a Deep Learning Emotion Classification Framework to identify and classify emotions in low-resourced languages such as Hindi. The proposed framework combines a classification model and a low resource optimization technique in a novel way. An annotated corpus of Hindi short stories consisting of 20,304 sentences is used to train the models for predicting five categories of emotions: anger, joy, suspense, sadness, and neutral talk. To resolve the class imbalance in the dataset SMOTE technique is applied. The optimal classification model is selected through experimentation that compares machine learning models and pre-trained models. Machine learning and deep learning models are SVM, Logistic Regression, Random Forest, CNN, BiLSTM, and CNN+BiLSTM. The pre-trained models, mBERT, IndicBERT, and a hybrid model, mBERT+BiLSTM. The models are evaluated based on macro average recall, macro average precision, and macro average F1 score. Results demonstrate that the hybrid model mBERT+BiLSTM out perform other models with a test accuracy of 57%.
"USING A MOBILE APP TO CREATE RELEVANT AND PARTICIPATORY MUSIC LEARNING SPACES"

This case study features pedagogical strategies that were used in the context of a mobile app for learning to encouragerelevant engagement and participation. For 20 weeks, a group of 18 piano students, ages 10 through 15, used a mobileapp known as
AR-BASED LEARNING RESOURCE: A DIFFERENT WAY TO LEARN DATA-STRUCTURES

Considering the difficulties in the teaching/learning process of computer programming, the development of skills related to Computational Thinking (CT) to prepare people to better solve problems stands out. Augmented Reality (AR) allows for the
WEB VIEWERS FOR EDUCATIONAL VR CONTENTS

This paper introduces web viewers for educational VR contents. Recently, many types of VR goggles have been releasedas commercial products and many entertainment applications for them have been created. However, educational VRcontents have been
Tracking and Grasping of Moving Objects Using Aerial Robotic Manipulators: A Brief Survey

Unmanned Aerial Vehicles (UAV) has evolved in recent years, their features have changed to be more useful to the society, although some years ago the drones had been thought to be teleoperated by humans and to take some pictures from above, which is useful; nevertheless, nowadays the drones are capable of developing autonomous tasks like tracking a dynamic target or even grasping different kind of objects. Some task like transporting heavy loads or manipulating complex shapes are more challenging for a single UAV, but for a fleet of them might be easier. This brief survey presents a compilation of relevant works related to tracking and grasping with aerial robotic manipulators, as well as cooperation among them. Moreover, challenges and limitations are presented in order to contribute with new areas of research. Finally, some trends in aerial manipulation are foreseeing for different sectors and relevant features for these kind of systems are standing out.
A Risk Prediction Model for Network Security Using Knowledge Graph

To reduce the probability of network risk, a knowledge graph-driven risk prediction model for network security was developed by exploring the information on network detection data. Indicators of the model were determined for security protection capability, attack threat risk, network performance anomaly index, and disaster tolerance, which were included in the index system of the developed model. The primary and secondary indicators were categorized to construct the knowledge graph. The graph attention mechanism was also integrated into the model. The entity-level attention network layer learned the attention coefficients among neighboring entities in the relationship path. The relationship of level attention network layers was obtained using new entity feature vectors and the attention coefficients. Entity feature vectors were aggregated to output risk prediction results. The experimental results showed that the model accurately predicted the level of risk in network security, reducing the number of risk events to more than 38%.
Research on the Memory Processing Rules of Children in Tang Poetry Reading Using Internal Feature Extraction and Deep Neural Network Method

There are differences in children's cognitive abilities towards Chinese Tang poetry. Several Tang poems are easier for children to learn, while others are difficult. Thus, it is necessary to understand what characteristics of Tang poetry make children find difficult to learn. This problem was modeled as a binary classification problem in machine learning. Firstly, a Tang poetry recitation test was conducted on children, and the average score of all children on each poem was calculated. After data processing, a measure of the difficulty of Tang poetry was determined as the dependent variable for the study. Tang poetry has many characteristics, such as theme type, publication period, and style depending on whether it rhymes, the number of words, number of sentences, sentence length, and whether there are rare characters. These features were selected as independent variables. We constructed two classification models based on the classification and regression tree (CART) and deep neural network methods. The F1 scores of the methods were 80.3 and 84.8%. Although the accuracy of the CART model was slightly lower, it still showed strong interpretability for the characteristics of Tang poetry that were difficult for children to learn. The results can assist in practical teaching.
Design of Blended Teaching Platform for Aerobics Courses Based on Wearable Virtual VR

To teach intricate skills that are not learned and mastered in traditional aerobic courses, we used augmented reality (AR) technology. Features such as virtual-real fusion, information interaction, and tracking registration were used in the AR system. The AR system enhanced real-time interaction and enabled 3D panoramic exploration using wearable virtual reality (VR) devices. Visualization and interactive technology were developed with tools such as 3D MAX and Blender in the system. Vuforia SDK was chosen as the suitable AR framework. The hybrid online-offline information teaching system based on AR technology was also created using Photon distributed computing solution and Unity 3D graphics program. The system facilitated online communication and education and provided offline self-learning and training for students. The teacher used a mobile terminal to zoom in or flip the overlapped 3D model against a real background. This method effectively presented complex skills for students to understand and learn.
Comparing Visualizations to Help a Teacher Effectively Monitor Students in a VR Classroom

Educational virtual reality (VR) applications are the most recent addition to the learning management tools in this modern age. Due to health concerns, financial concerns, and convenience, people are looking for alternate ways to teach and learn. An efficient VR-based teaching interface could enhance student engagement, learning outcomes, and overall educational experience. Typically, teachers in a VR classroom do not have a way to know what students are doing since students are not visible. An efficient teaching interface should include some mechanism for a teacher to monitor students and alert the teacher if a student is trying to catch the attention of the teacher. An ideal interface would be one, which helps a teacher effectively monitor students while teaching without increasing the cognitive load of the teacher. In this paper, we present a comparative study of two such student monitoring interfaces. In the first interface, the student activity related information is shown using icons near the student avatar (representing a student in the VR environment). While in the second interface, a set of centrally-arranged emoticon-like visual indicators are present in addition to the student avatar, and the student activity related information is shown near the student emoticon. We present a detailed user experiment comparing the two interfaces in terms of teaching management, student monitoring capability, cognitive load, and user preference. Participants preferred and performed better with Indicator-located interface over avatar-located interface.
A Comparative Study on Optimizing Virtual Reality Experience through User Representations in Industry

Virtual Reality (VR) has emerged as a powerful tool in the industry, offering benefits such as enhanced learning outcomes, improved skill acquisition, and deeper engagement across various fields [1]. However, the absence of a standardized approach and guidelines for VR system operation poses a challenge when implementing interaction types and user representations in VR environments. This paper focuses on investigating the impact of controller visualization on precision, accuracy, and immersion within VR environments. By identifying the optimal and most comfortable user representation, which involves a combination of input devices and visual displays, we aim to address this challenge. Previous research has not sufficiently explored the interplay between these interaction methods and user ownership, task performance and usability in immersive virtual environments for different tasks. To bridge this gap, we conducted a comprehensive user study, comparing three VR user representations: visualized controllers with physical controllers, visualized animated hands with physical controllers, and visualized animated hands with hand tracking. Participants evaluated each setup, and we employed qualitative feedback and quantitative metrics, including task completion times and error rates, to evaluate their experiences. Our findings highlight that hand tracking may have limitations in terms of usability but excels in generating a strong sense of body ownership compared to the alternative options. Notably, our analysis revealed minimal or no significant difference between the use of visualized hands or controllers when controllers were employed as the input device. Thus, the choice of the best user representation largely depends on personal preference, while the most effective operation mode varies based on the specific task executed in the VR environment. By leveraging these insights, the industry can harness the full potential of VR technology, driving greater productivity, efficiency, and overall success.