Reviewerly/exHarmony huggingface dataset:
Advancing Education Through Metaverse Virtual Reality Simulation

Metaverse refers to the next generation of the internet. Through the technology development, it allows users to interact with others by using 3D avatars. Education has been one of the highly compatible metaverse applications. Nowadays, the way of learning has also gradually changed and shifted to online with the collaboration of various tools. By using metaverse in the future, the learning process can be much more elevated with an immersive experience. Therefore, this study aimed to analyze user satisfaction using Mozilla Hub, an online tool that enables users to explore virtual worlds. We gathered the data by conducting a web-based simulation for 20 students to try the experiences and features. From the simulation, we asked some questions related to the experience of using it and analyzed the results by using a descriptive statistical method. The result showed that most participants gave a positive response toward the implementation of the metaverse. However, some improvement is still needed in developing the metaverse to be more optimally used.
Determining the Effectiveness of Cloud Computing on the Payroll Management System

The study explores the implications of cloud computing on managing the company's payroll system. This qualitative study aims to illuminate HR managers’ perceptions of the advantages of using cloud computing to manage payroll. The success of a firm depends on accurate and timely action. The primary source of information for this study is obtained through focused group discussion. Content and thematic analysis were done in 20 focused groups from the responses obtained from the HR managers working in the Payroll Department after switching from Traditional Computing to the Cloud. Each group had four to seven HR Managers. The data for this study was primarily collected from Indian Companies; however, it extensively emphasizes the widespread use of Cloud Computing in HR. After a thorough review of the literature and focus group discussion with HR managers in organisations using Cloud Computing in managing payroll for over a year, appropriate conclusions were drawn. The transition from traditional to Cloud Computing in Payroll has a favourable impact on the organisation's processes and structures. This study suggests a proposed model named 5A Model that will assist HR Managers to handle Payroll efficiently.
Forecasting the Global and Diffuse Solar Irradiance of Bangkok's Tropical Climate using Long-Short Term Memory (LSTM) Technique

This paper presents the model development to forecast the one-hour ahead global and diffuse solar irradiance of Bangkok, Thailand, located in a tropical climate zone. Based on the measurement records during 2019–2021, the forecasting models were developed by the long-short-term memory (LSTM) technique in which the ambient temperature, solar elevation, and an insolation parameter namely normalized global solar radiation were selected as the model inputs. To assess the forecasting performance, the LSTM models were compared to the artificial neural network (ANN) model and the simple persistence (SP) model. Two statistical parameters of normalized mean bias error (nMBE) and normalized root mean square error (nRMSE) were used for the performance assessment. The results showed that the LSTM model was superior to the other two models (ANN and SP) for all weather conditions (both wet and dry periods). The LSTM model also forecasted the global irradiance more accurately than the diffuse irradiance.
Applying Self-Assessment Manikin (SAM) to Evaluate the Emotional Responses to the Service Robot Feature

This study aims to examine the valence, arousal, and dominance associated with a participant's affective response to different waiter robots. We used a Self-Assessment Manikin (SAM) to assess emotional responses to these issues. SAM consists of a set of three pictorial scales, each representing a different affective dimension: valence, arousal, and dominance. In this study, SAM uses a pictorial representation of a human to evaluate the four types of waiter robots. The experiments were carried out through a questionnaire using Google Forms. Participants were shown video clips of four different types of waiter robots and then assessed to rate them using the SAM scale. The type 3 waiter robots were found that have the highest emotional responses across all three dimensions because they sounded interactive and user-friendly. Waiter robots can provide a sense of novelty and excitement for customers, which can create a positive emotional response. They can provide a unique and memorable customer experience, enhancing the overall dining experience. The results of this experiment will be helpful in the development of robots for service applications.
Celebrity: Creation of A Database Towards an Automatic Beauty Evaluation System

In recent days, facial beauty analysis has attracted various beauty-related fields like plastic surgery, the cosmetic industry, photo retouching applications, etc., The facial beauty analysis framework depends on an aesthetic scoring mechanism and needs high quality large-scale facial image database for facial beauty prediction. Beauty analysis can be extended to the ranking of beauty pageants in beauty pageant competitions. Most of the beauty scoring systems have focused on feature fusion and selection mechanisms through hand-crafted features with limited low-quality databases which are inadequate to analyze facial beauty and lead to infancy in the research of facial beauty. This work presents a machinebased automatic evaluation system for beauty by creating and compiling a database that includes beauty pageant images of winners and runners-up of beauty pageants competition using a deep learning algorithm. To evaluate the created database, pre-trained deep-learning models are used where deep-learned facial features are extracted for learning latent representations of beauty from facial images. From experiments performed on the created dataset, the classification accuracy achieved is 76.15%, using a pre-trained CNN model, ResNet 50.
The Delphi Approach for Benchmarking Student Learning Behaviour in Ubiquitous Learning Context

Within the realm of education, the idea of ubiquitous learning has emerged as a significant topic and a significant advancement in the discipline. In this respect, this study tries to investigate and benchmark the ubiquitous learning behavior of the students at University Teknologi MARA, Perlis Branch in the new context of the proposed ubiquitous learning model. The study adopts a qualitative research design as it aims to obtain multifaceted information through in-depth interview sessions with the participants selected for the study. The Delphi method was used in this study for data collection. Two rounds of data collection from a group of experts were employed in this approach. The input for the study was gathered from twelve participants who had experience with ubiquitous learning. The findings of this study highlighted some variations between the identified learning behaviour of the students and the suitable behaviour of the learners. The implications of the study were discussed.
Implementation and Familiarity Covid-19 Contact Tracing Application in Japan And Indonesia

In December 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan City, China. It was quickly determined to be caused by a novel coronavirus, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread worldwide, with over 582 million cases as of August 2022. To reduce this, in addition to establishing health protocols and getting vaccines, governments worldwide have developed digital contact tracing applications for smartphones. This study will focus on the differences in implementation and familiarity of the COVID-19 tracing application in Indonesia and Japan. This research aims to use tracing applications in Indonesia and Japan, namely PeduliLindungi and the COVID-19 Contact Tracing Application (COCOA). The objectives of this research are: 1) to study how the involvement of the PeduliLindungi and COCOA coronavirus tracking applications currently helps the community in the health sector, and 2) to find solutions to the problems they are experiencing and provide advice on PeduliLindungi and COCOA. The data collection method we used is questionnaires to students in universities in Japan dan Indonesia. We also did a literature review of some books and journals. The results of this study indicate that there are various advantages and disadvantages in tracing applications such as PeduliLindungi from Indonesia and COCOA from Japan among students. However, compared to the benefits, these two applications still have more disadvantages in using them. To help overcome these shortcomings, this study will provide some suggestions on how the application can help users during this pandemic.
Syllabus Management System and Coordinator Recommendation System on Universitas Multimedia Nusantara

This research project aims to improve the quality of created Syllabus by maintaining format consistency and addressing the need for competent course coordinators. To accomplish this, the study employs a range of methods, including quantitative research, prototyping, and the use of profile-matching algorithms to develop a website containing a comprehensive Syllabus management system and a course coordinator recommendation system. There are 8 phases: Initial Requirements, Design, Prototyping, Evaluation, Review & Update, Coding, Testing, and Maintenance. The unique aspect of this research is its focus on the Syllabus documents of the UMN information systems major, the integration of a document management system and a decision support system, as well as the implementation of ReactJS programming languages and YII2 frameworks. Data for the study was gathered through a combination of literature review, observation, and interviews and analyzed using content and descriptive analysis techniques. The Syllabus management system successfully standardized the format and arrangement of the Syllabus by providing a consistent template and streamlining the input process. The recommendation system offers valuable insights for determining subject coordinators by ranking candidates based on specified evaluation criteria. However, many areas can still be explored and developed to expand the knowledge base of information systems and enhance the quality of education.
The Students' Perspective on “Gather Town” Virtual Meeting in Online Language Learning

Since COVID-19 emerged and became a pandemic in Indonesia, the pattern of learning has also changed. Various efforts were made to make learning more effective. One of them is by using learning applications and learning websites. The applications used can be developed independently or using applications that have been developed and are free to use. This study discusses the use of the Gather Town Virtual Meeting (GTVM) Website in learning Mandarin speaking skills. GTVM is a virtual meeting platform that combines video calls with 2D maps. The appearance and content of Gather Town itself is similar to Video Game with 8 Bit video quality. The students of this study were 26 students. Two things that will become the research objectives in this research after learning by using the Gather Town Website are: 1. How to design online learning with GTVM as supporting tools in language learning; 2. How the students' perspectives about GTVM using in language online learning. The method in this research is the class action method. Students are asked to study Mandarin videos on GTVM. Then the students re-write the new vocabulary learned from each video and retell the contents of the story heard in Mandarin in their own language. The conclusion of this study is that students feel that learning through GTVM can encourage them to be more active in learning, increase new vocabulary knowledge and improve their speaking ability in Mandarin.
Forecasting of Outpatient Hospital Visits using A Bidirectional Long Short-Term Memory Model

Recently, accurate predicting outpatient visits is crucial in healthcare for optimizing service delivery and resource allocation. Time series models, particularly Deep Learning (DL) methods, have gained popularity in predicting demand and can potentially be used to predict demand for medical services, including outpatient hospital visits. This study aims to assess the potential of Bidirectional Long Short-Term Memory (Bi-LSTM) model in accurately predicting outpatient visits. The proposed model was tested with different set of parameters. Two important parameters adjusted in this study which are batch size and number of hidden nodes. The study also compares the performance of Bi-LSTM with other LSTM architectures, such as Vanilla LSTM and Stack LSTM. The results obtained show that Bi-LSTM performs best with batch size 64 and 10 hidden neurons. Besides, the results yielded indicate that the Bi-LSTM model performs exceptionally well with higher accuracy compared to other LSTM architectures. Overall, this study offers valuable insights into the use of Bi-LSTM models for predicting the number of outpatient visits.
Digital Token: Token-Based Degree Certificates with Credit Transfer System

The fake degree, diploma, or certificate is a global issue that affects many organizations, companies, and industries. With a rapid increase in the numbers of websites and social platforms, the fake degree certificate can be sold online by diploma mills or individuals. For falsifying academic transcripts and fake diploma are illegal in many countries. The using of the fake degree certificate can deceive educational universities, institutions or employers that they have obtained the legitimate degree. This issue may have the severe consequences for employers, universities, individuals, and public safety. There are companies have hired specialists to specifically review applicants' degrees. The traditional way of proving documents is difficult, time-consuming, and involves many intermediates that make the process more complicated. To counter this issue, this paper propose a solution by applying a blockchain technology. It can store degree certificates in a decentralized system that is immutable and traceable, reduce the need for intermediaries, and take a quick time for verification. This research develops the application using digital token to create genuine certificate. The results of this research provide a software prototype for issuing and verifying degree certificate.
The Implementation of Genetic Algorithm to Solve Final Project Defense Scheduling Problem

Scheduling of final project session is one of the problems that need to be handled in the Information Systems study program at Universitas Multimedia Nusantara (UMN). The problem arises because there are some differences in the available schedules of the prospective examiners. Besides that, another factor that is taken into consideration when the study program determines prospective examiners is the expertise of the examiners. Therefore, the topic of this research was raised to be able to solve the problem. The system development method used in this study is prototyping. The algorithm that will be used to create the scheduling system is a genetic algorithm to determine the final schedule for students' final project defense based on the availability and expertise of the examiners. The proposed system will handle two main processes, namely determining the appropriate examiner for each student based on the student's final project topic and determining a final defense schedule. The proposed system will be built on a web-based platform and have 3 access levels such as the head of the study program, lecturers, and students. The proposed system will provide the best recommendation scheduling results from all the possibilities. The recommended schedule will be used as the final schedule of the student's final project defense.
ICFY (I Care For You): An IOT Based Fall Detection and Monitoring Device using ESP32-CAM and MPU 6050 Sensors

Elderly people's safety and health are seriously threatened by falls. The elderly is vulnerable to fall injuries, which can occasionally result in death. Due to their physical makeup and advanced age, elderly people require greater care. The goal of this study is to develop a fall detection and monitoring system called ICFY (I Care For You) that can tell whether an elderly person has sustained an injury as well as to provide quick assistance to the elderly and reduce self-reported injuries. The rechargeable wrist wearable device has an ESP32-CAM module and MPU 6050 sensor that detect falls and take pictures, respectively. The project was created using the prototyping technique. The study involved on-site surveys and show the elderly demonstrations to provide them more information about the project. The criteria with the highest rank were determined using the ISO 25010 Quality Model survey. The top three (3) criteria following implementation were portability, functional stability, and usability. Overall, the project was rated “Very Good”. As a result, it is claimed that the wrist wearable device project is useful and effective for the elderly in preventing and monitoring falls.
PT Bottle Classification Function for Pfand Equipment

Approximately 8.3 billion tons of waste plastics are produced on Earth, and waste plastics that are not properly processed and recycled threaten our ecosystem on land and at sea. Since 2003, Germany has been using the Pfand system, which refunds deposits when containers are returned to reduce plastic waste. As a result, the plastic recycling rate is 97.4%, shows a high recycling rate. The system proposed in this paper simplifies the existing upcycling method and minimizes the cost incurred in the circulation structure by adding a function to separate renewable materials from materials requiring additional work to the existing Pfand system. It is a system that recognizes the QR or barcode of the product, classifies the product, and compresses and shreds the classified plastic. The proposed equipment classifies products by QR or barcode, but in the future, it plans to apply AI to classify products. In addition, handrails and stairs will be installed on the product so that elderly and disabled people in wheelchairs can use it comfortably.
Understanding of Compendium Student Guidance Using Text Mining

The Ministry of Education, Culture, Sports, Science and Technology (MEXT) published “Compendium Student Guidance - Seito Sidou Teiyou” in 2010. The compendium aims to activate student guidance and counseling in every primary and high school. However, reading and understanding this compendium is difficult for those unfamiliar with school teaching. Additionally, in December 2022, this text was substantially revised to reflect the increasingly complex and changing environment for students. This compendium is a frequent candidate for the teacher employment examination. Only seven months after the publication of the new edition, students will have to take a challenging exam. It takes time for university faculty to read complex documents and understand their moot points, and it is difficult to explain them in a way that is easy for students to understand. Therefore, this article analyzes the document using text-mining techniques with KH Coder software, SQL, and R language. In particular, it will discuss how to facilitate its understanding for university students taking the teacher employment selection examination.
The Deployment of Service Robots Powered by Artificial Intelligence in Five-Star Hotels: Does it Influence the Customer's Booking Intention?

Service robots are becoming increasingly common in the hospitality sector as an innovative technology that can improve customers' overall experiences. Despite its significance, the impact of service robot deployment on customers' booking intention has received scant consideration. Since booking intention may lead to real purchase behavior, the purpose of this study was to evaluate how the deployment of service robots in five-star hotels influences potential hotel guests' booking intention. This study used the Technology Acceptance Model (TAM) to predict the potential hotel guests' technology acceptance and booking intention. Using a quantitative approach, 198 research participants in the study are given questionnaires to fill out as part of the data collection procedure. A purposive sampling technique was used in this research. This study found that the perceived technological ease of use, customers' innovation self-efficacy, and perceived technological effectiveness have a positive influence on customers' intention to book a hotel room that employs service robots in their operation. This research result is consistent with the findings of previous studies on this topic. The outcome of the study is expected to give a better understanding of how implementing smart technology may influence customers' decisions to make hotel reservations, subsequently increasing the level of hotel occupancy rate.
User Experience Analysis of Customs for Land and Building Rights System

The Customs and Excise information system for Land and Building Rights (BPHTB) which is managed by the Regional Tax and Retribution Management Agency (BPPRD) of South Lampung Regency is considered to still have shortcomings in terms of user experience design. The purpose of this study was to explore the user experience of the BPHTB application in terms of usability, ease of use, ease of learning, and user satisfaction through three stages. The first stage is interviewing users of the BPHTB application. The second stage used the Usability, Satisfaction, and Ease of Use Questionnaire (USE Questionnaire) with BPPRD employees as respondents. The third stage of analysis was carried out using the usability testing method with respondents from BPPRD employees who had never used the BPHTB application. From the results of the three analyzes, it can be concluded that the system has shortcomings in the comfort aspect. After the results of the user experience analysis are obtained, recommendations for information system improvements are given in the form of interface design. Recommendations for improving the user interface design are expected to provide more benefits for users in conducting BPHTB transactions in South Lampung.
The Effect of the Gaze Visualization Interface on the Learning Performance of Virtual Reality Medical Education

Here we propose a virtual reality education system that applies an eye-tracking-based gaze visualization interface to prevent the user from experiencing cognitive overload, which may occur in existing virtual reality educational environments. Two gaze visualization interface types, Circle Marker and Highlight, are first used by the instructor to produce virtual reality medical educational content. An experiment is then conducted to analyze the difference in learning performance between these two interface types, with the degrees of concentration and learning flow selected as the learning performance indicators to be evaluated. The learning concentration is evaluated using the dwell time, and the learning flow is evaluated using a survey. A correlation analysis between the degrees of concentration and learning flow is performed, with a positive correlation determined for these two learning performance indicators. An independent samples t-test confirms that there is a statistically significant difference between the degrees of concentration and learning flow based on the type of gaze visualization interface, with the results obtained using the Circle Marker type having a more positive effect on both learning concentration and flow.