Reviewerly/exHarmony huggingface dataset:
Faktor–Faktor yang Memengaruhi Niat Pembelian Mi Shirataki Instan: Aplikasi Extended Theory Of Planned Behavior

Instant shirataki noodles are included in functional foods made from iles-iles tubers (Amorphophallus onchopyllus). Instant shirataki noodles have several benefits because of the glucomannan content in iles-iles tubers. This product experienced a positive increase in demand despite limitations in terms of consumer segment and product availability. This shows that there is a possible purchase motivation by the belief that the product is safe and healthy compared to ordinary instant noodles. The purpose of this study was to analyze the factors that influence the purchase intention of consumers of instant shirataki noodles by expanding the Theory of Planned Behavior. This study used primary data obtained through an online questionnaire. The samples in this study were 450 people. Sample determination using the Purposive sampling method. Data analysis in this study used descriptive analysis and Partial Least Square (PLS-SEM). The results showed that E-TPB model proved to be better in explaining the effect of purchase intention on instant shirataki noodles with variables that had a positive and significant direct effect on intentions, namely attitudes towards behavior, subjective norms, perceived behavioral control, health awareness and perceived availability. In addition, the findings suggest that health awareness and perceived availability can have a significant indirect effect on intentions. The strategy is to create marketing events by inviting consumer reference groups, collaborating with social media influencers, providing customer testimonials, and increasing promotions and product availability.
Pelatihan English for tourism guna peningkatan interaksi sosial dan self-confidence bagi komunitas pariwisata

As a tourism place, Jodipan Colorful Village is not only visited by domestic tourists, but also foreign tourists. On the one hand, the English language skills of teenagers around Kampung Warna-wani Jodipan are still very limited. Most teenagers there also tend to feel insecure when it comes to interacting with foreign tourists. In response to this, the service staff conducted an English for Tourism Training for six days to ten youths in Colorful Village. Service activities consist of psychoeducation to increase self-confidence and English for tourism training to improve English language skills in tourist areas. The results of the evaluation showed an increase in both self-confidence and English language skills in service participants.
In the Face of Uncertainty, Peer-Training: Lessons from a Group Strategy Undertaken by Sociology Faculty During the Pandemic

The training offered to university teaching staff tends to be scant, voluntary and heavily oriented toward novice teachers. With the arrival of Covid-19 and the sudden switch to online teaching, training became an urgent need for teachers. In this context, some faculty members of the University of *anonimizado* created a multi-cohort faculty peer-training group for collaborative learning in multimodal teaching methods. This paper describes the initiative and analyses the impact of the training on participating faculty members. The authors used a mixed methods research strategy with a sequential approach. Results indicate that training action’s collaborative dynamics contributed to the general well-being of the participants, bringing about a reduction in their feelings of isolation, insecurity and lessening their perception that they lacked the skills required for the new situation. Also, intergenerational differences were detected in the effects the training had on more novice and more experienced teachers.
PREDISPOSITION OF SCHOOLCHILDREN TO COMPUTATIONAL THINKING WHEN STUDYING DIGITAL TECHNOLOGIES

The article discusses the problem of measuring of the schoolchildren predisposition to computational thinking in the process of studying digital technologies in the framework of project activities for the robots creation. The structure of the model for measuring propensity, ability and susceptibility to computational thinking is described. A high degree of gender dependence of respondents for the “propensity” scale was found. It is established that teaching digital technologies most of all contributes to the formation of schoolchildren’ propensity for computational thinking.
Design and Execution of Cyberattacks Simulation for Practice-Oriented Experiential Learning

Convergence of ICT networks, if not properly secured, could lead to catastrophe, especially in critical infrastructure. A malicious cyberattack such as data breach can cause substantial damages to the critical assets and services of an organization. Rapid identification, technical analysis, strategic, and tactical response can minimize the impact of cyber incident and crisis. Various initiatives around the globe are taken to ensure the cyber resiliency of the digital space. Cybersecurity capacity building and exercises are widely adopted initiatives. The attack-simulated cybersecurity exercises can be conducted on vulnerable testbed supported by technologies like virtualizations. However, very limited resources, artifacts, and research are available in academic domain related to such testbed and exercises. In order to conduct research on how effective are practice-oriented experiential learning in building higher-order skillset in cybersecurity domain, a practice-oriented lab which replicate a real-cyberattack scenario was developed. The developed exercise contains a malware-based scenario which leads to data breach and includes vulnerability assessment, lateral movement, scanning, and log analysis of victim machine and network traffic analysis. In this paper, we presented the design of simulated attacks-based practice-oriented testbed for building deep cybersecurity skill sets. With the objective to provide platform to apply and analyze skills and assess abilities to counter cyberattacks, vulnerable machines and exploits were developed for the experiment. Exercise type design, selection of vulnerabilities, and exploits are derived from the real-life cyber incidents.
Expert System Detection of Disease Due to Bacteria Salmonella using Android-Based Forward Chaining Method

Many diseases are caused by unhealthy food, one of which is Salmonella bacteria. Diseases from the Samonella bacteria can attack the digestive tract which includes the stomach, small intestine, and large intestine or colon. Some species of salmonella can cause infection through food. This includes Salmonella Typhi and Salmonella Shigella. Based on the problems above, there are still many people who do not know the symptoms of this bacterial disease and how to diagnose it with a high certainty value. With the aim of making an expert system application through each android phone by means of a diagnosis through the signs and symptoms. The researcher chose to use the forward chaining method. This method was chosen because this method is considered capable of providing a high level of certainty. The forward chaining method is one of the decision-making strategies starting from facts to conclusions or final conclusions. The result of this research is to create an android-based expert system application that can diagnose diseases caused by salmonella bacteria based on existing symptoms using the forward chaining method. This expert system has the benefit of providing good education to the public regarding diseases caused by salmonella bacteria.
Required Quality of Service attributes in the context of various types of Web Services

Abstract4Nowadays, many business units are based on network solutions on the Internet.Various industry branches are entering the Web and offering their services.Customers differ a lot in terms of what services quality requirements they want to be ensured.Functional conditions are defined at the level of business process implementation, but quality issues are also very important there.This study concerns the analysis of non-functional requirements for different groups of users of Web Services.The main objective is to identify differences in user expectations in the context of distinct services offering various functionalities on the Internet.The research was carried out via a systematic literature review within the Web of Science database using keyword chains.As a result of this work, 21 publications describing case studies of the implementation of Web Services and their qualitative attributes were identified.In the context of 20 different types of Web Services, a total of 23 quality attributes were listed.
Face and silhouette based age estimation for child detection system

The problem of age estimation based on facial images is a well-known computer vision task that is widely applied in identification systems.With help of the special Dyzurnet.plunit detecting Internet content, related to sexual abuse of children we slightly redefined a problem.Our Convolutional Neural Network (CNN) solution is focused on infants and prepubescents recognition and in the particular age ranges can be considered as the-state-of-the-art in children detection.Silhouette-based age estimation is often concentrated on the human gait or body proportions analysis.Single image age estimations on the dressed (fully or partly) body are not typically researched because of a lack of properly labeled data.In our work, we present the method used to train image preparation and the final effectiveness of age estimation of that kind.The proposed solution is a part of the system for responding to threats to children's safety in cyberspace with particular emphasis on child pornography
A Comparative Study of User Identification for COVID-19 Vaccination Online Registration

Due to the COVID-19 pandemic, individuals have been encouraged to obtain COVID-19 vaccinations.As part of the vaccination process, it is necessary to verify the identity before obtaining the vaccines.Incorrectly identifying the individuals could lead to serious consequences.For example, an incorrect vaccination schedule ( e.g., incorrect timing between doses and incompatible brands) may cause undesired side effects to an individual, so it should be more accurate and convenient to identify themselves whenever and wherever people are required.One of the most effective and commonly used identification methods is face-to-face (or offline) identification.However, the method is typically time-consuming and is not suitable for the current situation where individuals should avoid direct contact.Hence, there is a growing trend for an online identification method where individuals use digital credentials to identify themselves.This paper suggests an online authentication system for improvements by investigating how different people authenticate themselves online in each country for COVID-19 vaccination.Comparing the online authentication systems between a country that have their national identification cards or not makes the Pros and Cons of both systems clear, particularly, in Japan and Thailand.
Temporal Language Modeling for Short Text Document Classification with Transformers

Language models are typically trained on solely text data, not utilizing document timestamps, which are available in most internet corpora.In this paper, we examine the impact of incorporating timestamp into transformer language model in terms of downstream classification task and masked language modeling on 2 short texts corpora.We examine different timestamp components: day of the month, month, year, weekday.We test different methods of incorporating date into the model: prefixing date components into text input and adding trained date embeddings.Our study shows, that such a temporal language model performs better than a regular language model for both documents from training data time span and unseen time span.That holds true for classification and language modeling.Prefixing date components into text performs no worse than training special date components embeddings.
Reinforcement Learning for on-line Sequence Transformation

In simultaneous machine translation (SMT), an output sequence should be produced as soon as possible, without reading the whole input sequence.This requirement creates a trade-off between translation delay and quality because less context may be known during translation.In most SMT methods, this trade-off is controlled with parameters whose values need to be tuned.In this paper, we introduce an SMT system that learns with reinforcement and is able to find the optimal delay in training.We conduct experiments on Tatoeba and IWSLT2014 datasets against state-of-the-art translation architectures.Our method achieves comparable results on the former dataset, with better results on long sentences and worse but comparable results on the latter dataset.
Software Sentiment Analysis using Deep-learning Approach with Word-Embedding Techniques

Sentiment Analysis in the Software Engineering community aims to make the development and maintenance of software a better experience by helping provide code and library suggestions, defect-related comments for source code, etc.The manual finding of sentiment-based comments may be an inaccurate prediction and a time-consuming process.Automating the sentiment analysis process by leveraging Machine Learning models can benefit software professionals by giving them insights into other developers and feelings about software products, libraries, development, and maintenance tasks at a glance.This study aims to develop software sentiment prediction models based on comments by (1) identifying the best embedding techniques to represent the word of the comments, not just as a number but as a vector in n-dimensional space (2) finding the best sets of vectors using different features selection techniques (3) finding the best methods to handle the class imbalance nature of the data, and (4) finding the best architecture of deep-learning for the training of models.The developed models are validated using 5fold cross-validation with four different performance parameters: accuracy, AUC, recall, and precision on three different datasets.The experimental finding shows that the models developed using the word embeddings with feature selection using Deep Learning classifiers on balanced data can significantly predict the underlying sentiments of textual comments.
Extending Word2Vec with Domain-Specific Labels

Choosing a proper representation of textual data is an important part of natural language processing.One option is using Word2Vec embeddings, i.e., dense vectors whose properties can to a degree capture the "meaning" of each word.One of the main disadvantages of Word2Vec is its inability to distinguish between antonyms.Motivated by this deficiency, this paper presents a Word2Vec extension for incorporating domain-specific labels.The goal is to improve the ability to differentiate between embeddings of words associated with different document labels or classes.This improvement is demonstrated on word embeddings derived from tweets related to a publicly traded company.Each tweet is given a label depending on whether its publication coincides with a stock price increase or decrease.The extended Word2Vec model then takes this label into account.The user can also set the weight of this label in the embedding creation process.Experiment results show that increasing this weight leads to a gradual decrease in cosine similarity between embeddings of words associated with different labels.This decrease in similarity can be interpreted as an improvement of the ability to distinguish between these words.
Representing and Managing Experiential Knowledge with Decisional DNA and its Drimos® Extension

The Semantic Web concept is proposing a future concept of the WorldWideWeb (WWW) where both humans and man-made systems are able to interconnect and exchange knowledge.One of the challenges of Semantic Web is smart and trusted accommodation of knowledge in artificial systems so it can be unified, enhanced, reused, shared, communicated and distributed with added aptitude.Our research represents an important component of addressing the above challenge and exciting, cutting-edge exploration trend in the general area of developing tool for intelligence augmentation.
An Experimentation Framework for Specification and Verification of Web Services

Abstract4Designing and implementing Web Services constitutes a large and constantly growing part of the information technology market.Web Services have specific scenarios in which distributed processes and network resources are used.This aspect of services requires integration with the model checkers.This article presents the experimentation framework in which services can be specified and then formally analyzed for deadlock-freedom, achievement of process goals, and similar features.Rybu4WS language enriches the basic Rybu language with the ability to use variables in processes, service calls between servers, new structural instructions, and other constructions known to programmers while remaining in line with declarative, mathematical IMDS formalism.Additionally, the development environment allows simulation of a counterexample or a witness -obtained as a result of the model checking -in a similar way to traditional debuggers.
Application Design “Xanthe Original Distro” Web Based to Increase Sales Value

Xanthe Original distributions have quite a number of buyers or members, in this case, the main focus that will be evaluated is how to process online and offline sales of original Xanthe products. Online sales of original Xanthe products are still required to contact the original Xanthe distribution via WhatsApp to ask for stock, product details, product prices, and product delivery costs, so members or buyers must wait first until the distribution party replies to the WhatsApp chat, while in offline sales Xanthe products originals are required to come to the original Xanthe distro, and the problem that often occurs when buyers come directly to the distribution is that the product they want to buy is out of stock. The purpose of designing this application is to produce an effective and efficient sales application on the Xanthe Original distribution. The research used in completing this sales application is observation, interviews, and documentation carried out at the Xanthe Original Distro Sidoarjo. This sales application is made using the PHP Native programming language and MySQL as the database. The results of the research on this sales application are that the distribution party can manage goods data, category data, expedition data, member data, and computerized sales data. This application is expected to make it easier for members to buy original Xanthe products because product orders and product payments are made online, and there is no need to come to the store.
Permodelan Sistem Pembayaran SPP Berbasis Sms Gateway Pada SMK Negeri 1 Bandar Lampung

SMK Negeri 1 Bandar Lampung is an educational institution located on Jl. Morotai Island Jl. Morotai Island No. 33, Jagabaya III, Sukarame, Bandar Lampung City, Lampung 35122, Indonesia. SMK Negeri 1 Bandar Lampung has expertise programs, namely Dressing, Catering, Information and Communication Technology, Animation and Business and Management. As for the SPP payment system at SMK Negeri 1 Bandar Lampung it is still done manually, where the Administrative Officer still uses a book to record SPP payment data. This causes SPP data storage is still in the form of archives, where data storage media like this are easy to damage or lose, and archives that accumulate make the performance of school staff not good. From this problem, the idea emerged to create a desktop-based application and an sms gateway, in which it can manage payment transaction data and provide information to parents related to tuition transactions. The methodology used in making this application is the Waterfall method. The programming language used is Java Neatbeans, the database uses MySQL and Gammu as a tool to connect the SMS Gateway. Supported by the existence of a computer at the institution. With the application of the desktop-based tuition payment information system and SMS Gateway, it is hoped that it will make it easier to manage transactions and provide information to parents
Perancangan Sistem Informasi Akuntansi Persediaan Barang Pada Toko Jabat

The process of registering goods is very important because we need to know when goods enter and leave, and when checking, we need to know the existing stock. The current system running at Jabat stores has many shortcomings and weaknesses, including the recording of receipts and problems at Jabat stores is not yet fully electronic, so inventory management is slow and often incomplete. Common errors such as number typos or missing data. Reports that are still manual greatly affect the company's performance and have not been able to meet all company needs. The application is expected to help and facilitate the work of the Administration in managing the list of goods reports, incoming goods reports, outgoing goods reports, and inventory reports as well as minimizing errors in processing these reports
Aplikasi Perhitungan Pajak Karyawan Pada PTPN VII Unit Tulung Buyut

PTPN VII Unit Tulung Buyut is one of the businesses engaged in rubber plantations. Income tax data processing is currently using Microsoft Excel and making reports is still simple by utilizing the forms that have been made previously. so that existing problems will result in inaccurate income tax data reports so that it can result in disputes for each income tax data report. The purpose of making this application is to obtain a more advanced application program by utilizing programming languages in its development. Data collection methods used are interviews, observations, documentation and literature review. The approach used is object-oriented and uses the Extreme Programming method as a system development process. System development tools are in the form of Document Flowcharts (BAD), and Unified Modeling Language (UML), namely use case diagrams, class diagrams, activity diagrams and sequence diagrams that can help to design a pPph 21 taxation system. The software on this system uses the Java programming language to speed up the process of paying employee income taxes and the MySQL database is used to store employee report data and income tax payments
Employee Payment Information System Design at PT Tamanaco

This research is motivated by the existence of problems in the scope of the payroll information system. Problems in the form of inaccuracies in the calculation of employee salaries, and invalidity in salary. The purpose of this study is to build a system that aims to provide convenience and accuracy in managing the amount of employee salaries, as well as providing convenience in generating reports related to payroll at PT. Tamanaco. The method used in this research is data collection using literature study, interviews and system development with the waterfall method. The results of this study indicate that all menus and features in the system are running well and the system can process salary data and print salary slips correctly. This research can contribute to the company in the hope of providing convenience in producing reports related to payroll, and is expected to provide additional knowledge and can be a reference material in the field of technology, especially the field of Information Technology studies.