Reviewerly/exHarmony huggingface dataset:
Development of a natural language chatbot interface for website users

Today, there are a variety of technology solutions for creating chatbots, including universal platforms such as Google's Dialogflow, Microsoft's Azure Bot Service, and IBM's Watson Assistant, as well as chatbot builders such as ActiveChat, SendPulse, and BotPress. The disadvantage of the considered platforms and designers is the limitation of the free plan. This study considered the development and integration of an informative chatbot into the department's website in order to create a virtual assistant for potential applicants and applicants. The relevance of the study is due to the modern conditions of admission, limited opportunities to conduct career guidance events in connection with the consequences of the COVID 19 pandemic and the war on the territory of Ukraine. The object of research is a system of informing website users using natural language. A software product has been developed, which is an information system for applicants. The dynamic JavaScript programming language combined with the Node.js code execution environment and the Telegraf library was chosen to create the chatbot. The Heroku cloud platform with an integrated Heroku PostgreSQL database became the server for the operation of the chatbot. The system is implemented using the @BotFather Telegram service, which makes it possible to integrate it into any web resource. The stages of chatbot development are highlighted with examples of information, linguistic, and technical support. An analysis of the compliance of the developed chatbot with regard to the criteria of informativeness, multimodality, emotionality, productivity, and interactivity was carried out. The structure of the information content of the chatbot, which includes a set of modules, has been developed. A test version of the chatbot has been designed, tested, and integrated into the website of the Department of Applied Linguistics, which will continue to be tested and improved in 2023–2024. Practical significance: the structure of information content and the method of developing a chatbot could be used to develop authentic systems for informing applicants in institutions of higher education
Electronic anonymous voting system based on blind digital signature

Представлена схема создания системы анонимного дистанционного голосования, в основе которой лежит алгоритм слепой электронной подписи — один из эффективных способов сформировать и подписать бюллетень для голосования. Описан метод построения канала связи для анонимной передачи бюллетеней на сервер и доказана надежность такого метода, а также указан рекомендуемый способ безопасного хранения бюллетеней голосования в виде блокчейн-транзакций. В ходе исследования были изучены возможные угрозы безопасности системы и представлены способы их предотвращения. Таким образом проанализирована надежность представленной системы и продемонстрировано, что система анонимного удаленного голосования не подвержена этим уязвимостям. Nowadays, remote voting systems and applications become very popular, but they have some drawbacks, especially in terms of anonymity. The aim of the paper is to create a scheme for developing a reliable anonymous remote voting system. The methodology for designing such a scheme is based on the algorithm of blind ballots digital signature. This algorithm is one of the effective ways to generate and sign a voting ballot, where its encrypted voting results are transmitted to the ballot server without any information about user. A secret channel protocol was created to anonymously transfer ballots from voters to a server. This article proves the reliability of this method and also presents a recommended method for securely storing ballots as block chain transactions. In addition, possible threats to the security of the system were investigated and analyzed and there were presented possible ways to prevent them. As the result of this work, an effective scheme for creating an anonymous remote voting system with relatively small number of participants was described. Moreover, the reliability of the presented system was analyzed and it was demonstrated that the system of anonymous remote voting is not affected by possible vulnerabilities discovered during the investigation. As a result of the performed research, it was shown that the presented anonymous remote voting scheme is a good alternative to traditional voting and other similar systems.
Conceptual Framework of Inclusive Human Resource Management to Support Neurodiversity Employment

This study aims to proposed a conceptual framework for inclusive human resource management in supporting neurodiversity employment. As organizations increasingly commit to fostering diversity and inclusion, the integration of neurodiversity into the workforce has emerged as a contemporary trend. This concept seeks to harness the unique talents of neurodivergent individuals, thereby enhancing organizational performance. However, the adoption of neurodiversity also introduces distinctive challenges within organizations’ human resource management practices, an aspect that has received limited attention in the human resource management literature. To address this gap, the study explores institutional forces, human resource management approaches, and perceived inclusion that influence the support for neurodiversity within organizations based on relevant literature. Through this exploration, the authors aim to provide a comprehensive understanding and a practical framework for guiding future research on neurodiversity in the workplace, enriching the discourse on inclusive human resource management and facilitating more informed organizational practices.
Influence of Financial Performance and Environmental Performance on Company Reputation

The purpose of this research is to analyze the reciprocal influence between financial performance and environmental performance on corporate reputation. The population used consists of non-financial companies listed on the Indonesia Stock Exchange (BEI) from 2019 to 2022. The sample size is 28 companies each year, selected using purposive sampling. This study utilizes documentary data, including annual reports, the Corporate Image Index (CII) published by Frontier Consulting Group, and the PROPER index published by the Ministry of Environment and Forestry.The results of this research, using simple linear regression analysis, indicate that financial performance has a positive and significant effect on corporate reputation. Corporate reputation has a positive and significant effect on financial performance. Environmental performance has a negative and non-significant effect on corporate reputation, while corporate reputation has a negative and significant effect on environmental performance. Environmental performance has a negative and significant effect on financial performance, and financial performance has a negative and significant effect on environmental performance.The implications of this research, especially for companies, are that it can serve as a basis for strategic decisionmaking. On the other hand, performance is a key aspect in developing reputation for the future.
Video Annomaly Classification Using Convolutional Neural Network

The use of surveillance videos is increasingly popular in city monitoring systems. Generally, the analysis process in surveillance videos still relies on conventional methods. This method requires professional personnel to constantly monitor and analyze videos to identify abnormal events. Consequently, the conventional approach is time-consuming, resource-intensive, and costly. Therefore, a system is needed to automatically detect video anomalies, reducing the massive human resource utilization for video monitoring. This research employs deep learning methods to classify anomalies in videos. The video anomaly detection process involves transforming the video into image format by extracting each frame present in the video. Subsequently, a Convolutional Neural Network (CNN) model is utilized to classify anomalous events within the video. Testing results using the CNN architectures DenseNet121 and EfficientNet V2 yielded performance accuracies of 87% and 75%, respectively. The testing results indicate that the DenseNet121 architecture outperforms the EfficientNetV2 architecture in terms of performance.
Animals as Criminal Evidence in the Perspective of Criminal Procedure Law

This study aims to determine the conception of living things as evidence in a criminal offense based on existing legal regulations in Indonesia; the method used in this research is a normative method with a statutory approach, and the data used is secondary data, in the form of primary legal materials consisting of Law Number 8 of 1981 concerning Criminal Procedure (KUHAP) and the Draft Criminal Procedure Code (RKUHAP). The results of this study found that living things can be used as evidence if they meet several leading indicators, one of which is that these living things must be directly related to a criminal case; the novelty of this research regards the wetting and comparison of animals as evidence from the perspective of the Criminal Procedure Code and Draft Criminal Procedure Code.Keywords: Animals; Crime; Evidence
The Effect of Emotional Display Rules on Service Employee Burnout: A Focus on the Mediation of Challenge Appraisal and Hindrance Appraisal

Emotional display rules are official and unofficial requirements on how people&#x0D; should express their emotions to others in organizations, playing crucial roles&#x0D; in emotional management. According to the job demand-resources model,&#x0D; emotional display rules can cause job stress and burnout because they are&#x0D; job demands. However, in light of the challenge-hindrance job stress model,&#x0D; the effect of job demands on burnout may differ according to whether people&#x0D; perceive them as challenges or hindrances. The purpose of this study is to&#x0D; determine the causal relationship among emotional display rules, challenge&#x0D; appraisal, hindrance appraisal, and service worker burnout. In this study, we&#x0D; postulate that emotional display rules increase burnout, while challenge and&#x0D; hindrance appraisals mediate the display rules-burnout relationship. A total&#x0D; of 213 survey responses were collected from frontline workers in the service&#x0D; industry, and an analysis of results revealed that emotional display rules are&#x0D; positively associated with burnout, while challenge appraisal negatively mediates&#x0D; the display rules-burnout relationship. We also found that hindrance appraisal&#x0D; did not mediate between emotional display rules and burnout, while perceived&#x0D; organizational support and self efficacy did not moderate the relationship&#x0D; between emotional display rules and burnout. These results may demonstrate&#x0D; the possibility that service worker burnout can be buffered with the perception&#x0D; of emotional display rules as challenging rather than hindering job demands.&#x0D; In addition, they imply that service workers’ perceptions and mind controls&#x0D; are more important than external factors like organizational support in managing&#x0D; job demands, such as emotional display rules. This study shows the importance&#x0D; of job appraisal in understanding service workers’ stresses and burnout.
Korean EFL Learner Preference for Voice-Based Audio Asynchronous Online Discussion

This study explores Korean EFL learner preferences and perceptions of digital composing (DC) with innovative online technology tools during the implementation of emergency remote learning measures. The research compares learner use of text-based DC and voice-based audio asynchronous online discussion (AOD). This paper investigates the following research problem: What digital modes of interactive, online instructional design can serve as appropriate, learner-accepted replacements for offline instruction? One prior finding indicated that Korean undergraduate EFL learners preferred text and audio DC to video modes. To follow up, this paper investigates 57 learners’ preferences and perceptions toward text-based and voice-based DC, and compares the results. The data analysis methods employ paired-samples Tests, and a thematic analysis to identify issues raised in student comments. The results reveal that learners’ levels of user satisfaction with voice-based audio AOD and their ratings of its perceived usefulness confirm that it can be a satisfactory, effective, and preferable task for engaging learners in digitally-mediated four-skills practice. Another finding is that utilizing a voice-based audio module did not significantly alter learners’ course satisfaction when superseding a text-based module. These findings inform pedagogical practice with empirical insights regarding learners’ use of digital technologies, levels of acceptance, and DC preferences.
The Performance Comparison of DBSCAN and K-Means Clustering for MSMEs Grouping based on Asset Value and Turnover

Background: This study focuses on the latest knowledge regarding Micro, Small and Medium Enterprises (MSMEs) as a current central issue. These enterprises have shown their significance in providing employment opportunities and contributing to the country’s economy. However, MSMEs face various challenges that must be addressed to optimize their outcomes. Understanding the characteristics of this group was crucial in formulating effective strategies. Objective: This study proposed to cluster or combine micro, small, and medium enterprises (MSMEs) data in a particular area based on asset value and turnover. As a result, this study aimed to gain insights into the MSME landscape in the area and provided valuable information for decision-makers and stakeholders. Methods: This study utilized two methods, namely the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) method and the K-Means method. These methods were chosen for their distinct capabilities. DBSCAN was selected for its ability to handle noisy data and identify clusters with diverse forms, while K-Means was chosen for its popularity and ability to group data based on proximity. The study used a dataset containing MSME information, including asset values and turnover, collected from various sources. Results: The outcomes encompassed identifying clusters of MSMEs based on their closeness in the feature space within a specific region. Optimizing the clustering outcomes involved modifying algorithm parameters like epsilon and minimum points for DBSCAN and the number of clusters for K-Means. Furthermore, this study attained a deeper understanding of the arrangement and characteristics of MSME clusters in the region through a comparative analysis of the two methodologies. Conclusion: This study offered perspectives on clustering MSMEs based on asset value and turnover in a specific region. Employing DBSCAN and K-Means methodologies allowed researchers to depict the MSME landscape and grasp the business attributes of these enterprises. These results could aid in decision-making and strategic planning concerning the advancement of the MSME sector in the mentioned area. Future study may investigate supplementary factors and variables to deepen comprehension of MSME clusters and promote regional growth and sustainability. Keywords: Asset Value, Clustering, DBSCAN, K-Means, Turnover
Impact of Audit Committee Effectiveness on Accrual and Real Earnings Management among Jordanian Listed Firms: Conceptual Paper

The aim of this study is to conduct a comprehensive literature review on the impact of audit committees' independence, meeting frequency, and financial expertise on earnings management (both accrual and real). This review will act as a guide for upcoming empirical research. Many countries, when drafting corporate governance legislation, have focused on improving the characteristics of audit committees to deter unethical behaviour by management. Jordan is among the countries that have included provisions in the Corporate Governance Code for listed service and industrial sector companies that emphasise the characteristics of audit committees and their directors. The provisions were implemented in 2009 and revised in 2017. The current study suggests that researchers should choose a study sample from the years 2014 to 2019 to achieve different goals. First, leaving out years after corporate governance started in 2009 lets us check claims that the quality of corporate governance mechanisms improves over time. This is because the years proposed to be left out (2009–2013) are long enough for listed companies to get used to corporate governance. Second, a comparison can be conducted on the quality of corporate governance mechanisms before and after recent reforms. Empirical studies are likely to provide feedback to both legislators and regulators as to whether governance mechanisms are working as intended.
Multiuser-Based Fertilizer Supply Information System In East Plongkowati Kud, Grobgan District

KUD Plongkowati Timur is located at Jalan Godong-Karangrayung, Grobogan Regency, which apart from operating in the savings and loan business unit, is also a distributor of fertilizer products produced by PT. Petrokima Gresik and PT. Pupuk Sriwidjaja Palembang. In running the fertilizer distributor business unit at KUD Plongkowati Timur, the process of recording purchase and sales transactions is not carried out using an integrated system in the database, all data is still recorded conventionally by the administration section, while the administration section's computer functions to create reports which are copied from notes provided by cashier so that data security is not guaranteed because the database is not yet integrated. Based on the problems that exist in the East Plongkowati KUD, the author would like to propose a design for a Fertilizer Inventory application system to be taken into consideration in helping speed up the process of recording purchase and sales transactions and can provide the information needed by the East Plongkowati KUD, Grobogan Regency in the form of purchase reports, sales reports, reports. suppliers, customer reports. So the design of the fertilizer inventory information system uses the Microsoft Visual Basic 6.0 programming language with a database from Microsoft Access 2007 and the design of reports from Crystal Report 7. It is hoped that making this application can be one of the efforts that can be made to overcome problems that often occur so that it can increase work effectiveness which of course will have an impact on improving the quality of service to customers.&#x0D;
Sentiment Analysis on a Large Indonesian Product Review Dataset

Background: The publicly available large dataset plays an important role in the development of the natural language processing/computational linguistic research field. However, up to now, there are only a few large Indonesian language datasets accessible for research purposes, including sentiment analysis datasets, where sentiment analysis is considered the most popular task. Objective: The objective of this work is to present sentiment analysis on a large Indonesian product review dataset, employing various features and methods. Two tasks have been implemented: classifying reviews into three classes (positive, negative, neutral), and predicting ratings. Methods: Sentiment analysis was conducted on the FDReview dataset, comprising over 700,000 reviews. The analysis treated sentiment as a classification problem, employing the following methods: Multinomial Naïve Bayes (MNB), Support Vector Machine (SVM), LSTM, and BiLSTM. Result: The experimental results indicate that in the comparison of performance using conventional methods, MNB outperformed SVM in rating prediction, whereas SVM exhibited better performance in the review classification task. Additionally, the results demonstrate that the BiLSTM method outperformed all other methods in both tasks. Furthermore, this study includes experiments conducted on balanced and unbalanced small-sized sample datasets. Conclusion: Analysis of the experimental results revealed that the deep learning-based method performed better only in the large dataset setting. Results from the small balanced dataset indicate that conventional machine learning methods exhibit competitive performance compared to deep learning approaches. Keywords: Indonesian review dataset, Large dataset, Rating prediction, Sentiment analysis
Cash Sales Information System Multiuser Based On Human Computer Facilities Semarang

Sarana Insan Computer (SIK), a sales company operating in the computer sector in Central Java, has utilized Information Systems even though they are not yet well integrated between one system and another. Therefore, in this thesis the author will develop a cash sales system model by choosing SIK as the research object. The cash sales information system created includes a system for ordering goods, sending goods, sales returns and cash sales reports. This research aims to make it easier to present reports directly, accurately, quickly and to enable systems that do not yet exist to be integrated into an integrated system. So that the cash sales information system can be implemented well, a software development process is carried out which is based on correct software engineering. The software development model used in this research is a multiuser development model. Information technology which is developing rapidly today really provides support for the development of a cash sales information system for a computer sales company such as SIK, especially with the use of computer-based information technology or better known as a Computer Based Information System, because of the use of computer technology in a system. information will be able to process data more quickly with minimal error rates, save labor and save costs. The Cash Sales Information System is designed using direct data processing methods. The use of the direct data processing method is intended so that every incident of cash sales information can be processed directly. The procedures that will be processed consist of the administration section which handles administration, the purchasing section which handles incoming goods, the sales section which handles customer service and the computer goods sales section, the personnel section and the leadership itself.&#x0D;
Catch Production Data Information System and Fish Auction at UPT PPP Pondokdadap

Sendang Biru beach is facing directly to the Indian Ocean, an area with abundant fishing potential. People working as fisherman make Sendang Biru is a fishing ground. Fishing ports play an important role in the development of every activity related to fisheries, especially capture fisheries. The fishing port is a place for government activities in the field of fisheries, such as loading and unloading of fish. Unit Pelaksana Teknis Pelabuhan Perikanan Pantai (UPT PPP) Pondokdadap is one of the coastal fishing ports with the largest landing of fish, especially tuna, tuna, and skipjack in Malang. Fishery production results are obtained from fishing by fishermen in the sea. The types of fish mostly found in Sendang Biru are dominated by large pelagic fish, namely tuna. Fishing production is obtained from fishermen's catches with fishing gear in the form of purse seines and handlines. A lifeboat with handline fishing gear is the fleet used to catch large pelagic fish. Total fishery production from production volume and production value on January 1 to June 30, 2022 obtained results on fishery production volume reaching 5,596,271 kg with fishery production value reaching Rp. 137,691,524,000. There are several obstacles during the fishing process regarding bad weather or rainfall with high waves, which can affect fishermen's income in fishing activities classified as low.