Reviewerly/exHarmony huggingface dataset:
PELATIHAN KETERAMPILAN SENI MENGHIAS MEDIA DENGAN TEKNIK DECOUPAGE ART PADA KELOMPOK WANITA PURNAKRAMA MARANATHA MALANG

This community service aims to enrich and encourage the entrepreneurial creativity of the target audience in order to empower their skills. Participants in this community service activities are the members of the group of “Purnakrama GSJA - Maranatha Malang”, in which consist of women who are struggling to live alone as widows or unmarried. They live independently and are responsible for their own well-being without the support of a husband or partner. Empowering the participants' skills is delivered by introducing and teaching them the decoupage art technique, that is the art of decorating plain objects/used items with deco-napkins so that the value of the object will increase greatly. After attending this training, participants are expected to stimulate their creativity, as well increase their knowledge and skills, with the result it can be used to help their welfare even though they have to live independently. Decoupage art is chosen a main training topic as it provide a lot of beneficial advantages. Besides it can be easily taught in an efficient time, it also being able to transform used/plain items into more valuable ones because decoupage art have a variety of interesting motifs. Apart from that, the tools and materials used for decoupage art really easy to look for, and the costs are affordable. The competencies have been achieved, as in the end each of the participants has been successfully applied decoupage art technique using two kinds of deco-napkins patterns towards two different medias surfaces, in which each media need special and different treatment to apply decoupage technique. The first media is strap-plastic bag with its rough surface, then another media is flower pot which has smooth surface. In the end, the final evaluation results declared that community service using Decoupage art has been success to empower the members of the group of “Purnakrama GSJA - Maranatha Malang”
RANCANG BANGUN SISTEM INFORMASI E-LEARNING BERBASIS WEB (STUDI KASUS MI AL-INAYAH DARMINIYAH)

Learning is a process of interaction between educators and students where educators provide knowledge to grow at once develop insight, creativity and mindset of students. website-based e-learning to support the learning process teaching at MI Al-Inayah Darminiyah which can make it easier for students to learn&#x0D; and provide flexibility to be able to receive learning materials where and anytime without face-to-face contact with the teacher. The method used is the method and UML (Unified Modeling Language) and built using the PHP programming language (Hypertext Preprocessor) and using MySQL as database server as well XAMPP as a web server. Data collection through interviews with teachers and school staff as well as make observations which are then carried out by research literature. The result is that the e-learning website can be used by the admin, teachers and students at MI Al-Inayah Darminiyah in supporting the learning process teaching at the moment. Admins can manage teacher and student accounts, teachers can&#x0D; easily manage the material and assignments submitted. Student with easily get school notifications as well as materials and assignments delivered by the teacher. This e-learning website helps schools to improve processes learning optimally so that it can further affect improvement academic student achievement because of the convenience for students in accessing the media learning anytime and anywhere in accordance with the school's vision of " Menjadi Sekolah yang Berprestasi dan Berakhlakul Karimah”.
Comparative Analysis of Music Education Programs at the University Continuing Education Center in Gwangju Metropolitan City and Measures to Revitalize Local Culture

The purpose of this study is to analyze music education programs of university lifelong education centers in the Gwangju area, how they affect the vitalization of local culture, and to seek ways to develop music education at the level of lifelong education for vitalizing local culture. In order to expand opportunities for lifelong education to revitalize the local culture, it is necessary to open various educational programs as well as provide financial support for education expenses, and to provide opportunities for trainees to take courses regardless of time and place by utilizing an online platform. do. By enabling more trainees to take lifelong music education, it is possible to develop individual abilities and expand job opportunities, and promote cultural development and vitalization of cultural activities in the community.
An Iterative Neighborhood Blending Method For Multimodal Product Retrieval

Recently, the product matching and retrieval methods based on users’ real needs are becoming a hot spot in academic research, especially in the era of big data, more efficient and accurate matching methods become more necessary. Therefore, this paper aims to design an iterative neighborhood blending method for multimodal product retrieval, this method fuses image and text features of products that can efficiently retrieve items of interest to users from massive product data. First, the feature extraction model is trained by the classification head in the training stage. secondly, post-processing methods such as pooling, batch normalization and feature normalization method are designed to obtain feature vectors of different dimensions. Thirdly, product matching and retrieval are realized by an improved iterative neighborhood mixing method. Finally, experiments on the Shopee-Price dataset demonstrate that the iterative neighborhood blending algorithm brings significant improvements to the multimodal product retrieval task compared to the state-of-art.
The effects of sleep quality, sleepiness, fatigue, and psychological resilience on attention performance

AMA Demirci H, Bilge Y, Söğütlü L, Çatan H, Yıldırım Ü. The effects of sleep quality, sleepiness, fatigue, and psychological resilience on attention performance. Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology. 2023;18(3):127-136. doi:10.5114/nan.2023.134064. APA Demirci, H., Bilge, Y., Söğütlü, L., Çatan, H., & Yıldırım, Ü. (2023). The effects of sleep quality, sleepiness, fatigue, and psychological resilience on attention performance. Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology, 18(3), 127-136. https://doi.org/10.5114/nan.2023.134064 Chicago Demirci, Hasan, Yıldız Bilge, Lütfiye Söğütlü, Hanife Merve Çatan, and Ülkü Tankut Yıldırım. 2023. "The effects of sleep quality, sleepiness, fatigue, and psychological resilience on attention performance". Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology 18 (3): 127-136. doi:10.5114/nan.2023.134064. Harvard Demirci, H., Bilge, Y., Söğütlü, L., Çatan, H., and Yıldırım, Ü. (2023). The effects of sleep quality, sleepiness, fatigue, and psychological resilience on attention performance. Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology, 18(3), pp.127-136. https://doi.org/10.5114/nan.2023.134064 MLA Demirci, Hasan et al. "The effects of sleep quality, sleepiness, fatigue, and psychological resilience on attention performance." Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology, vol. 18, no. 3, 2023, pp. 127-136. doi:10.5114/nan.2023.134064. Vancouver Demirci H, Bilge Y, Söğütlü L, Çatan H, Yıldırım Ü. The effects of sleep quality, sleepiness, fatigue, and psychological resilience on attention performance. Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology. 2023;18(3):127-136. doi:10.5114/nan.2023.134064.
Spelling Correction in Rule Based Virtual Assistant for a MSME Business

Virtual assistant is a system that can communicate like a conversation that functions as an assistant to answer user questions. Users can type the questions at the virtual assistant menu. The research conducted resulted in a system that can make corrections to user typing on a virtual assistant that manages remove, duplicate, add, and substitute spelling errors. The role of artificial intelligence is more prominent to enhance the experience of customers and ease the burden of customer service and reduce cost. Often times, users mistype or misspell a sentence to deliver messages in a quick manner. But as computers could only understand correctly typed words, Automatic Spelling Correction (ASC) methods were born. This research implements Levenshtein Distance to correct incorrect words that combines it with a rule-based virtual assistant to serve information to the users using the web. In this experiment we implemented spelling correction in a real-time virtual assistant on a MSME website, it requires a small corpus to not burden the server and the users. We try to build this spelling correction using the Symspell library on the corpus from online news article (Tempo) with alterations catered to the needs of the business. The best results were achieved through the utilization of the ”Add” error type, achieving an impressive accuracy rate of 91.67%. On average, the system successfully corrected 81.25% of one-character errors from the original input.
Interactive Instructional Material to Aid TVET Module

The utilization of Augmented Reality (AR) technology is a significant aspect of the ongoing Digital Revolution 4.0. In the realm of contemporary education, the integration of innovative technologies has become pivotal in enhancing instructional methodologies. The aim of this study is to create Mobile Augmented Reality (AR) content and a storyboard for instructing the Basic Microcontroller module within the Telecommunication Program for Technical Vocational Education and Training (TVET). This involves referencing the Written Instructional Manual (WIM), survey and interview sessions to ensure the integration of AR into the instructional materials. An engaging and effective AR content that aligns with the course objectives and enhances the learning experience for trainees undertaking the Basic Microcontroller module in the Telecommunication Program that features two operational modes were developed. In the learn mode, trainees explore seven augmented Basic Microcontroller components through a user-friendly interface, guided by instructional materials. There is an evaluation mode, wherein trainees are assessed on their circuit assembly and programming skills, receiving star ratings and feedback for performance improvement. The research outlines the development of a user-friendly educational application, incorporating interactive guidance and trainer input in the selection of topics, microcontroller components, and circuit assembly training modes, emphasizing a preference for Android platform development. The application is designed to enhance the learning process by providing an engaging and interactive educational experience.
Quantile Normalized Neighbor Combinatorial Machine Learning Based Recommendation in Digital Marketing

The scientific advancement of the contemporary years has set industries on the move. The advancement in marketing has led to the point where reshaping to digital movements is essential. Even though it appears to be a plunge for marketers, as a matter of fact, all mechanized applications and systems that are designed on the basis of artificial intelligence only reduces the complication of conventional targeting and customization procedure. In several applications, the platforms utilized for online promotion carry algorithms for recognizing the best combinations whereas in other cases, the business establishments or institutions involving digital marketing take advantage to design and execute in-house personalized arrangements. As a case study, a method called, Quantile Normalized Neighbor Combinatorial Learning-based Recommendation (QNNCL-R) is applied for generating new leads that will ultimately become customers (i.e., promoting student higher education to admission branding in our scenario) via twitter dataset. The data obtained from the twitter dataset (i.e., higher education) is fed to the recommendationsystem. Then, the relevant set of features and event labels (i.e., tweets) is selected by Quantile Normalized Chi-square Feature selectionand a Neighbor Combinatorial Learning-based Recommendation algorithm with the best performance is selected for the recommendation process for higher education. QNNCL-R method is compared with other algorithms and indicating that QNNCL-R method performs better than other methods.
Exploring the Impact of Informal Language on Sentiment Analysis Models for Social Media Text Using Convolutional Neural Networks

The present study sought to investigate the influence of informal language on the effectiveness of sentiment analysis models when applied to social media text. A Convolutional Neural Network (CNN) approach was employed, and the model was developed and trained on three distinct datasets: a sarcasm corpus, a sentiment corpus, and an emoticon corpus. The experimental design involved keeping the model architecture constant and training it on 80% of the data, followed by evaluating its performance on the remaining 20%. The results revealed that the model achieved a high accuracy of 96.47% on the sarcasm corpus, with class 1 exhibiting the lowest accuracy. The sentiment corpus yielded an accuracy of 95.28% for the model. The integration of the sarcasm and sentiment datasets resulted in a slight improvement in accuracy to 95.1%. The inclusion of the emoticon corpus had a marginal positive effect, resulting in an accuracy of 95.37%. These findings suggest that the use of informal language has minimal impact on the performance of sentiment analysis models applied to social media text. Furthermore, the incorporation of emoticon data may lead to a modest improvement in accuracy.
Perancangan Sistem Keamanan Tambahan Pada Kendaraan Menggunakan Tracker SMS

Motor vehicle theft continues to pose a significant issue, primarily due to the vulnerability of security systems relying on manual keys. Thieves are well-versed in exploiting this weakness, necessitating innovative solutions. This study's objective is to design a tool that employs a GPS tracker and SMS to provide precise location coordinates. Additionally, it aims to deter motor vehicle theft by interrupting the electric current flow in the vehicle. Using the Research and Development (R&amp;D) method based on prior research, the outcome is a system capable of providing location points at extensive distances beyond conventional vehicle boundaries. In summary, this device interacts by sending pre-programmed commands to Arduino Uno, with ON functioning to activate electrical systems, OFF for deactivation, and LOCATION for requesting navigational position messages.
NAVIGATING THE NTF LANDSCAPE: INTELLECTUAL PROPERTY CHALLENGES AND OPPORTUNITIES

This article delves into the dynamic realm of Non-Fungible Tokens (NFTs) and the significant ramifications they have on the protection of intellectual property. By analyzing the convergence of non-fungible tokens (NFTs), smart contracts, and blockchain technology, this this article aims to explores the legal ramifications and potential advantages that emerge from the utilization of NFTs for the commercialization and exploitation of intellectual property. The article provides an examination of the legal aspects of NFT transactions, encompassing details such as ownership transfer, copyright, trademark, and patent considerations, in addition to the complexities of minting and ownership transfer. The necessity for precise agreements to delineate the scope of intellectual property rights conveyed is emphasized in the article, which also stresses the significance of transparency, due diligence, and clarity. Moreover, it underscores the convergence of common law principles and NFT transactions, prompting inquiries regarding the conveyance of intellectual property rights and emphasizing the need for exhaustive investigation. In light of the ongoing transformation of digital ownership on the NFT market, the article emphasizes the need for a cautious and well-informed strategy to tackle legal intricacies, promote openness, and cultivate trust within the NFT ecosystem.
Tackling an Unbalanced Dataset for Classifying Indonesian E-Commerce Reviews Using Multi Word Embedding Model

Product reviews are an integral part of ecommerce. By Q2 2020 alone, the average of e-commerce visitors in Indonesia almost reached 400 million. This vast amount of traffic resulting a massive amount of product review information. Product reviews in Indonesia are usually paired with a rating system from one to five based on user satisfaction with the product. Mostly, the number of reviews in each rating is unbalanced. Ratings 5, 4, and 1 are usually more frequent than ratings 2 and 3. This imbalanced data makes classification challenging to categorize the review rating, leading to inaccurate predictions for the rating with fewer data than the others. Previous research used various approaches for classifying review ratings, such as machine learning and fine-tuning a state-of-the-art deep learning model. In this research, we propose a new approach that leverages multiple-word embedding combined with CNN to deal with the highly unbalanced dataset problem. By leveraging multiple-word embedding techniques, the model can extract more features from the review text. We also proposed an extended pipeline to enhance the model performance. The proposed model and pipeline perform better than the fine-tuned Indonesian BERT-based and RoBERTa-based pre-trained models baseline with 0.93 accuracy and 0.82 F1-Macro scores.
A Functional Data Classification Model Utilizing Functional Mahalanobis Distance and Regenerative Kernel Methods

The classification of functional data is an important research direction in modern data mining. In this paper, we propose a similarity measurement method for functional data based on functional Mahalanobis distance and regenerative kernel theory, considering the scenario where the predictor variable is a random function and the response variable is a categorical scalar. This method is then applied to functional kernel principal component analysis. During the classification phase, classic algorithms such as support vector machines and random forests can be combined to accomplish the task of classifying functional data. In empirical analysis, compared to the regenerative kernel based on Euclidean distance and the Euclidean distance regenerative kernel based on B-spline basis functions, the proposed method achieves better classification results. Furthermore, this similarity measurement can also be utilized in other machine learning algorithms based on regenerative kernel theory, thereby developing corresponding analysis methods for functional data.
PROFESSIONAL ETHICS IN THE NEW MEDIA ENVIRONMENT: IMPORTANCE AND CHALLENGES

There is no doubt that the developments in the field of technology and the information revolution that the contemporary world is witnessing are one of the most important major historical developments in human history. These current developments have led to major changes in the field of the media industry and the patterns of information consumption, production, dissemination, and sharing of its contents, which in turn has made the media sector divided into two areas: Traditional media: which includes newspapers, magazines, radio and television. New media: which is mainly based on new technology and the flow of information via the internet, mobile phones, applications, programs and social networking sites such as Facebook, Twitter, Instagram and others...... Considering that technological, scientific and technical development of any kind can be a double-edged sword, which has prompted legislators to regulate these areas in a way that serves media ethics and human rights of various kinds and avoid attacking them, we will try in this research paper to reveal the most important mechanisms developed by the Algerian legislator in the service of media ethics and to preserve the rights of citizens or what is known as the right to privacy
Aplikasi Media Pembelajaran Aksara Jawa untuk Siswa Sekolah Dasar menggunakan Augmented Reality berbasis Android

Javanese script is one of the local learning materials for Javanese that has been taught since elementary school. The characters are difficult for students because they are rarely used in everyday activities. The growing development of learning media technology can be utilized to attract students' attention and make learning activities easier. One example is the use of augmented reality technology. The purpose of this study is to develop a learning medium that can make it easier for students to learn Javanese characters. Methods used in research to develop these applications are waterfall models, which include need analysis, data collection, system design, implementation, and testing. Literature studies and interviews are used for data collection. In this study, it can be seen that the application has been successfully created and developed. Based on system testing using black-box testing, the features of the application ran according to plan and obtained 91.85% of the feasibility test results using the Likert-scale test criteria, which meant that the application was worthy of use.
Media Aplikasi Quizizz dalam Pembelajaran Ilmu Pengetahuan Sosial dan Pengaruhnya terhadap Hasil Belajar Peserta Didik

This study aims to find out how the use of quizizz application media affects the learning outcomes of class VIII students at SMPN 189 Jakarta. The method in this research is quantitative experiment with the One Shot Case Study experimental design, in this study there is no control class and only one class sample will be given treatment. Data collection techniques in this study using test techniques, observation, questionnaire/ questionnaires and documentation. The results of the study are as follows: The results of the study show that the Quizizz Application variable and the Class VIII Student Learning Outcomes variable at SMPN 189 Jakarta have some of the results of the calculation analysis. The calculation of t count is reinforced by the results of the t count &gt; t table or (9.506 &gt; 1.697) and a significance value of 0.000 is less than 0.05, which means that Ha is accepted, and Ho is rejected with a significance value smaller than 0.05, namely (0.000 &lt; 0, 05). So, it can be concluded that the Variable Use of the Quizizz Application partially has a significant influence on Learning Outcomes.
Convergence

Convergence is an important aspect of the computation of probabilities. It can be defined in many ways, each type of convergence having its own interest and its specific field of application. Note that the notions of convergence and approximation are very close.
Security And Privacy Using Two Fold Encryption Protocol Techniques In Edge Computing

With deployments of IoT devices and the arrival of 5G fast wireless, placing compute and analytics close to where data is created is making the case for edge computing. Edge computing is transforming the way data is being handled, processed, and delivered from millions of devices around the world. The explosive growth of internet-connected devices – the IoT – along with new applications that require real-time computing power, continues to drive edge-computing systems. Due to several advantages like low latency, Real-Time Availability. Real-time Data Transmission, brings Company and customer together, Edge Computing is used. To overcome several problems regarding security and privacy concerns, this paper provides solution by introducing Secured Two Fold Encryption Protocol in Edge Computing (STFC) based on two encryption schemes namely proxy re-encryption and searchable encryption. This paper particularly focus on securing the data from attackers by providing double encryption scheme. In this paper, Resource Manager is introduced in order to reduce the computational overhead in the encryption process.