Reviewerly/exHarmony huggingface dataset:
Dynamic Attention for Isolated Sign Language Recognition with Reinforcement Learning

With computer vision developing rapidly, sign language recognition (SLR) can be realized to bridge the communication gap for deaf people. In this paper, we propose a novel deep reinforcement learning model imitating the dynamic attention of humans for isolated SLR that selectively pays attention to keyframes of video and exclude noise from the redundant frames. We construct a Partially Observable Markov Decision Process (POMDP) to learn dynamic attention for SLR from the non-differentiable sequence of interactions. The proposed model adopts Inflated 3D ConvNets as the feature learner. Following the policy learned by the deep reinforcement learning method, the proposed model “observes” a clip from the video to infer the position of keyframes and move the focus for the following observation. As a result, dynamic attention excludes interference from redundant frames and improves performance. We validate the effectiveness of the proposed method and compare it with benchmark methods on the Chinese Sign Language dataset.
Social media and pupils’ academic performance: A case of selected secondary schools in Lusaka District, Zambia

Social media is a collective term for websites and applications focusing on communication, community-based input, interaction, content-sharing, and collaboration. People use social media to stay in touch and interact with friends, family, and various communities. Today, social media has been commonly used by everyone, especially young people and schools are getting into this modern medium of communication rapidly. However, social media has dragged youngsters, especially pupils into it to the extent that it fritters away their valuable time meant for studies, energy, and money. From this background, the study was conducted to examine the effects of social media on pupils’ academic performance in secondary schools in the Lusaka district, Zambia. The study employed both qualitative and quantitative methods and a descriptive survey design that sampled head teachers, teachers, pupils, and parents. Data was obtained from the respondents by means of interviews and questionnaires. Frequency tables, graphs, figures, and pie charts were used to analyze the qualitative and quantitative data. Data was also analyzed by the use of software; Statistical Package for Social Sciences (version 26) and Microsoft Excel (version 16). The study discovered that social media has facilitated an easy and economical way of communication between friends and families worldwide. Additionally, the study showed that social media is a valuable source of information, providing pupils with access to educational content, news, and resources that can enhance their learning. However, social media on the other hand was seen to be a significant distraction for pupils, diverting their attention away from studying, assignments, and other academic responsibilities. Also, late-night social media browsing can lead to sleep deprivation, which, in turn, can impair cognitive functioning and academic performance. The study therefore recommended that there is a need to encourage pupils to use social media for educational purposes only, such as group projects or discussions related to course content. Furthermore, there is a need to guide and support pupils in managing their time effectively and avoiding social media-related distractions.
Application of Fuzzy Inference System Takagi-Sugeno Methods for Diagnosis of Diseases and Pests of Madura Paddy Rice Based on Symptoms

Diseases and pests of lowland rice are one of the factors that can cause a decrease in rice yields. Therefore, it is necessary to have a diagnostic system to identify diseases and pests of paddy rice from an early age based on damage symptoms. The process of diagnosis requires expertise, knowledge, and experience from experts. Therefore, this research tries to build an expert system that can diagnose diseases and pests of paddy rice early by applying the Fuzzy Inference System Takagi with the Sugeno method. Fuzzy Inference System Takagi forms fuzzy sets using implication functions (rules). Rule composition is obtained from a data set of relationships between regulations, where the affirmation (defuzzification) and input from defuzzification is a constant or linear equation. The Sugeno method is used to diagnose diseases and pests of rice plants based on the symptoms experienced. This research aims to help plant pest control officers diagnose diseases and pests of paddy rice plants from the symptoms that attack the rice. The testing technique used is system accuracy testing and Mean Opinion Score (MOS) testing. The MOS test was carried out by involving 30 respondents consisting of 10 farmers and 20 extension workers, where 4.27 was obtained on a scale of 5 which was categorized into a good system. while testing the accuracy obtained from testing the system on two experts on diseases and pests of Madura paddy rice plants in 30 different cases has resulted in an accuracy rate of 86.66%. The expert system built in this study was able to diagnose 13 diseases and pests of Madura paddy based on the knowledge of two experts on 38 symptoms, and the plan was feasible to use and categorized into a good system.
Sistem Pendukung Keputusan Untuk Menentuan Desa Paling Maju dengan Menggunakan Metode MOORA

Decision Support System (DSS) is an approach to support decision making using data, provides an easy interface, and can incorporate the thinking of decision makers. In this study, we take a case study that can be solved by using a decision support system, where the problem faced by the Government of the Sub-District of Sumbang is how to determine the most advanced village in the District of Sumbang, because to do a selection one must use the manual method and the assessment process takes a long time to get. results. Therefore, a decision support system is made that can assist the assessment process and where the decision support system is carried out using the moora method. Based on the results of calculations regarding research in determining the most advanced village in the Contributing Regency is the Contributing Village with a value of 0.3758. Where the village has very good road conditions and the facilities available in the village are also very good compared to other villages.
Implementation of A*(Star) Algorithm in Robots Object Movement

Today the development of robots has increased a lot. Over time the robot can used as a medium of learning and education. The maze mapping system can be used as educational media in robotics. In this study, the idea was obtained to design a robot moving objects that can move on a flat striped plane like a line tracer robot. Robot it adopts a maze mapping system to find the fastest path in moving objects. These objects are in the form of mini objects that have been given a color consisting of red, yellow, green, and blue. The four colors are used as a reference for the robot to detect objects based on the color that will be moved from the object detection start point to the available finish point. The method to be used on the robot is A*. The A* algorithm can find the fastest route on the path traversed by the robot, by adding up the actual distance with the estimated distance, thus making it optimal in the search for the route. The microcontroller used on This robot is an Arduino Due which functions to enter data from the results of sensor readings is on the robots. The sensors consist of an infrared module that functions as a detector line and a TCS34725 color sensor to detect the object to be moved. This wheeled robot uses a DC motor with a voltage of 12V to drive the two wheels. Then 10 times experiment to determine the fastest path with 1 type of color, obtained success with 70%. The results of this study can be used as a comparison material for the A* method with the A* method, another fastest path search.
Neural Network Classification in Javanese Handwriting Recognition using Projection Profile Histogram and Local Binary Pattern Histogram

Indonesia consists of various regional tribes, where each tribe has cultural diversity and some even have their own regional letters, like Javanese tribe has Javanese characters. Javanese letters consist of 20 basic letters called Nglegena script. Subject about Javanese language is delivered to elementary student until now aims to preserve Indonesian culture especially the Javanese. In this study, we present two feature extraction methods are Local Binary Pattern (LBP) and Profile Projection (PP). Neural Network (NN) chosen as classifiers for classifying 20 javanese letters Nglegena. Some digital image processing processes are carried out, are image inversion, dilation, denoising and skeletoning. The Javanese script dataset is taken from the Kaggle database with the name Aksara Jawa: Aksara Jawa Custom Dataset, consists of 2154 train images and 480 test images. The experiment were carried out in two models, Projection Profile Histogram - Neural Network (PPH-NN) and Local Binary Pattern Histogram - Neural Network (LBPH-NN). The experiment show that both feature extraction methods have very good performance, 99.98% PPH-NN and 89.6% LBPH-NN on average.
User Interface Design for Grab Merchant Application Version 4.18.0 with Usability Approach

The development of technology is increasingly rapid, providing convenience in various aspects of activities. This has also penetrated business actors so that they can easily access the products and services they offer to many customers. This can take advantage of current technology through smartphone applications. Grab Merchant is an application that offers food and beverage orders that are delivered according to customer needs. However, we found problems with the usability of application features, especially controlling stock from the user side. The purpose of this study is to measure usability of the Grab Merchant application, researchers use the Use Questionnaire method to propose design user interface. The user interface design that is built is an improvement on features in accordance with the results of the distributed questionnaire. The research focus consists of 3 basic aspects of usability measurement, namely effectiveness, efficiency and satisfaction. These three aspects are measured by indicators of Usefulness, Ease of Use, Ease of Learning and Satisfaction in the Use Questionnaire method. As a result, improvements were made to the user interface design of the interface on the features and there was an increase in these 3 indicators.
Sales Product Clustering Using RFM Calculation Model And K-Means Algorithm on Primskystore

The optimization of data processing procedures can yield high-quality information that is then utilized by business owners in the decision-making process. An effective company plan, particularly in the realm of promotion, holds significant importance for store proprietors in order to foster sustained business expansion. Primskystore is an e-commerce platform operating inside the retail industry, where the efficacy of product sales promotion is perceived to be suboptimal. Sales product advertising continues to revolve around a single sort of product. The objective of this work is to develop a data mining model through the implementation of a web-based application that utilizes the K-means clustering approach and the RFM model. The utilization of the K-Means clustering approach and the RFM model can facilitate the clustering of sales products at retailers. The data mining application employed on this website utilizes the Python programming language, MySQL as the database, and the Unified Modeling Language for system model creation. The findings of this research encompass the development of a web-based data mining tool designed to present the outcomes of product sales clustering within retail establishments. The system has the capability to present the outcomes of the RFM calculation model and KMeans clustering. Specifically, it reveals the presence of three distinct clusters, with cluster 0 accounting for 30% of the data, cluster 1 representing 7.5% of the data, and cluster 2 encompassing 62.5% of the data. This web-based data mining program has the potential to assist retailers in determining an optimal promotional business strategy.
Penerapan User-Centered Design Method Guna Pembaruan Substansi Terhadap Informasi dan Data-Data pada Website

The research carried out aims to carry out a substantive update of information and data on the website of the Mathematics Education Study Program, FKIP, UNPATTI. The research carried out applies the User-Centered Design (UCD) method, which is a method in a design that focuses on user needs. Broadly speaking, in using the UCD method, the research conducted was divided into three main stages, namely analysis, design, and evaluation with the process of implementing the UCD method using ISO 9241-210: 2019. Furthermore, the research conducted involved 44 respondents who were used as target users and categorized into two groups, namely the academic community (lecturers and students) and non-academic members (prospective students and alumni). Based on the results of the research conducted, 9 formulations of user requirements were obtained, followed by making a website interface design in the form of a prototype (wireframe). Furthermore, the resulting prototype is then evaluated by providing a series of task scenarios to guide users in using the website. The evaluation was carried out using a qualitative survey method, namely interview activities aimed at obtaining feedback regarding user experience on the appearance of the website design interface as well as obtaining recommendations and suggestions for further development. Based on the evaluation carried out, the result was that the resulting website design met user needs. This is because the design is produced as a solution to user needs, by a series of requirements submitted by users. In addition, the design of the website interface also provides a satisfying user experience. Therefore, the research carried out does not occur repetition (iteration), so it can proceed to the implementation stage. Furthermore, at the prototype implementation stage, the results of the website design are then converted into an interface display using the Content Management System (CMS) Framework and supporting programming languages ​​such as HTML, CSS, PHP, and Javascript. The website of the Mathematics Education Study Program which has been successfully updated for the substance of both the information and data contained therein can then be accessed via the official link of the Mathematics Education Study Program, FKIP, UNPATTI..
The Effect of E-CRM on Customer Delight “An Applied Study on Mobile Telecommunication Companies in Mansoura City”

This research aimed to examine the effect of Electronic Customer Relationship Management (E-CRM) on Customer Delight in the context of Mobile Telecommunication Companies. The research adopted the philosophy of positivism, the deductive approach, and the method of quantitative analysis as the research methodology. The instrument utilized for data collection was the questionnaire. Consequently, 424 usable questionnaires were collected electronically through social media channels from customers of Mobile Telecommunication Companies in Mansoura City. The data was then analyzed using SPSS and AMOS 23. The results revealed that Electronic Customer Relationship Management has a significant positive impact on Customer Delight. Furthermore, research results indicated that Demographic differences don‘t have significant differences in respondents’ opinions regarding research variables (Electronic Customer Relationship Management, Customer Delight) except Gender, Education Level and Age.يهدف هذا البحث إلى دراسة تأثير إدارة علاقات العملاء الإلكترونية (E-CRM) على إسعاد العميل فى مجال شركات إتصالات المحمول. اعتمدت الدراسه فلسفه الوضعيه ، والمنهج الاستنباطى ، وطريقه التحليل الكمى كمنهج للبحث. كانت الأداه المستخدمة لجمع البيانات هى قائمه الأستقصاء. تم جمع ٤٢٤ استقصاءً صالحاً للاستخدام إلكترونياً عبر قنوات التواصل الإجتماعى من عملاء شركات إتصالات المحمول بمدينة المنصورة. وتم تحليل البيانات إحصائيا بإستخدامSPSS وAMOS 23. وتوصلت نتائج الدراسه أن لإدارة علاقات العملاء الإلكترونيه تأثيرمعنوى إيجابى على إسعاد العميل، علاوه على ذلك، تشير نتائج الدراسه إلى أن الأختلافات الديموغرافيه ليس لها تأثير معنوى فى اختلاف اّراء المستجيبين فيما يتعلق بمتغيرات الدراسة (إدارة علاقات العملاء الإلكترونيه ، إسعاد العميل) بإستثناء (النوع ، مستوى التعليم ، العمر).
Use of Patterned Datasets (Minimum and Maximum) to predict Bitcoin and Ethereum price movements

Bitcoin is always interesting to keep predicting where the next price movement will go. Bitcoin is the first and most influential Cryptocurrency on cryptocurrency price movements. Bitcoin is traded in many markets, the largest in Indonesia is Indodax. Indodax provides a document sharing API so that third parties can build applications that are able to process data on bitcoin price movements in real-time and continuously. This research shows how patterned datasets can be applied to monitor bitcoin price movements from the indodax market and show their effects on other cryptocurrency assets besides bitcoin. This research shows how data that is patterned and then processed using the minimum and maximum functions can provide 2 important information, namely the potential position of bitcoin when it is at the maximum and minimum points. The results of the patterned dataset formula are then compared to the movements of the 2 cryptocurrencies with the largest capitalization, namely BTC (Bitcoin) and ETH (Ethereum). The results of the comparison show that the use of patterned dataset formulas successfully shows important points in cryptocurrency trading, with simpler instructions.
Multinomial Optimization of Naïve Bayes Through the Implementation of Particle Swarm Optimization

Sentiment analysis is widely used in cases of text processing and comments. One of the case studies is about the analysis of a hotel review by the public. The method used in analyzing a sentiment from comments or reviews of a hotel is the Naïve Bayes Classifier. One that can be used is the Multinomial Naïve Bayes method. In improving the results of the accuracy of the method required an optimization method. There are many optimization methods that can be applied to algorithms in sentiment analysis case studies. One well-known method is Particle Swarm Optimization (PSO). This study aims to determine the effect of PSO optimization on the Multinomial Naïve Bayes algorithm in the case of sentiment analysis. From the results of optimization and model testing, the highest accuracy was obtained in the Multinomial Naïve Bayes test with PSO optimization as hyperparameter tunning and feature selection of 97%.
Sistem Pakar Diagnosa Penyakit Influenza (Flu) Menggunakan Metode Forward Chaining

Expert system is a technology that is widely used in the health sector, one of which is for disease diagnosis. Influenza (Flu) is one of the respiratory diseases caused by a virus called the influenza virus. Diseases caused by climate change are usually Influenza (Flu) and cold diseases, which are often considered the same by society. The purpose of this study was to design an expert system application for the diagnosis of these two different diseases, namely flu and colds. The research data is sourced from data from the Ministry of Health of the Republic of Indonesia (KEMENKES). The design of this expert system application uses the forward chaining method with google appsheet and google sheet tools. The results showed that all the features of the application have worked properly after being tested using the black box testing method. This application also helps people be able to distinguish flu and cold diseases, it is shown through the results of an online survey that 91% of respondents need this expert system application.
Exploring the Effectiveness of Using Digital Tourism Platforms in Egyptian Tourist Destination

Digital platforms currently have a substantial impact on the growth of the tourist sector by providing cutting-edge marketing and quality control tools, worldwide market access, and an increase in the range of tourism services. This research aims to explore the effectiveness of using digital tourism platforms in Egyptian tourist destinations. To do this, this study used a descriptive analytical technique using a questionnaire instrument. The sample consisted of tourists visiting Egyptian tourist destinations. Only 576 returned surveys were valid for statistical processing of the data, with an 88.6% response rate from the total disseminated questionnaires. The research used a variety of statistical methods, such as descriptive statistics, factor analysis, reliability analysis, coefficient analysis, Pearson correlation analysis, and one-way ANOVA. The research's findings show that there are a number of differences based on visitors' nationality, suggesting that this demographic characteristic is important in greatly impacting tourists' opinions on the effectiveness of the digital tourism platform in Egyptian tourist destinations. The research recommended that the Ministry of Tourism and Antiquities should create a digital platform to help communities, tourism providers, and governments work together to offer new and exciting tourism experiences. These experiences will benefit the community in social, environmental, and economic ways.
Penerapan Metode ROC Dan Metode WASPAS Untuk Menentukan Penerima Beasiswa KIP Kuliah

KIP lectures are lecture education assistance which aims to free registration for college entrance selection and tuition or education fees. One of the tertiary institutions that has the opportunity to get KIP Lectures is Budi Darma University. Based on the results of observations and interviews with the assistant head of student affairs at Budi Darma University to determine the feasibility of the Indonesia Smart Card (KIP) College scholarship currently still using the conventional election system, by means of students submitting files to the selection team for the Indonesia Smart Card (KIP) College scholarship then taking part in tests and interviews To overcome the problems experienced by the selection team, a system is needed to help the selection team. One of them is using the Decision Making System (SPK). Where to do a combination of the Decision Support System method with the ROC method used for weighting and the WASPAS method used for alternative rankings. With the aim of providing recommendations for students who get KIP college scholarships. From the results of the calculation of the values ​​above, it can be determined who will receive the KIP College scholarship based on recommendations from the decision support system by applying the ROC method which is used as weighting and the WASPAS method which is used as a ranking determination to get the best ranking results on behalf of Iramaya Tampubolon with a Qi value of 0. 991921266, it can be concluded that if KIP quotas study at Budi Darma University 10, the ranking taken is according to the number of cities received.
Improved adaptive belief propagation algorithm with reduced complexity for concatenated SPC‐RS codes

Abstract In this letter, a novel single parity check‐aided minimum sum (SPC‐aided MS) algorithm is proposed. A cascaded compiled code scheme is used to approximate the adaptive belief propagation (ABP) algorithm for Reed–Solomon (RS) codes using the min sum (MS) algorithm. The computational complexity is greatly reduced compared with the previous algorithm. Simulation results show that the SPC‐aided MS algorithm can achieve coding gains of up to 1.1, 0.7, and 0.6 dB for RS (255,239) code compared with the conventional ABP, LRBP, and HD‐P‐ABP algorithms, respectively under the condition of .