Reviewerly/exHarmony huggingface dataset:
The Effect of Organizational Justice and Self-Efficacy on Career Satisfaction among the Employees of Banking Sector in Bangladesh

This present study aimed to determine the influence of organizational justice and self-efficacy on career satisfaction. Employing survey and cross-sectional method, data was collected from the permanent employees of thirteen selected commercial banks located in Dhaka and Chittagong cities, Bangladesh. This study adopted simple random sampling techniques to select the sample, total 1480 self-administered questionnaires were sent to the respondents via email, 440 useable questionnaires were returned. The data was analyzed by deploying the SPSS version 22.0 and Smart-PLS version 4.0. The results indicate that distributive justice and procedural justice has a significant positive influence on career satisfaction, where interactional justice is positively but insignificantly related with career satisfaction. The results also show that self-efficacy positively impact career satisfaction. Moreover, the results of this study offer significant implications for bank professionals, policymakers, and scholars in formulating a strategic approach and initiatives to augment the level of career satisfaction among employees in the banking sector. Lastly, this section will go into the consequences of the findings and provide recommendations for further research. This study makes a valuable contribution to the continuing scholarly discourse surrounding the significant impact of employee career satisfaction within the banking sector.
Adoption of Artificial Intelligence and Robotics in Organisations: A Systematic Literature Review

Organisations have increasingly used artificial intelligence (AI) to innovate and compete successfully. Therefore, knowing the factors that affect the adoption of AI is crucial. This study aims to investigate the theories and models utilised in studying the adoption of AI among organisations and identify the factors influencing AI adoption among organisations across countries. Hence, a systematic literature review (SLR) and the PRISMA framework were used. This SLR contains eleven earlier studies that uncovered a growth in research focusing on AI adoption among organisations. Furthermore, this SLR discovered that the TAM, TOE, and UTAUT models are the most common ones. Three factors influencing organisations’ adoption of AI across countries are perceived usefulness, perceived ease of use, and intention. In developed countries, 30 factors have been discovered as having a significant influence on AI adoption while in developing countries, 27 factors have been identified. There is a lack of prior literature using SLR to analyse the technological adoption frameworks and models for AI adoption among organisations. Studies on identifying the crucial factors influencing AI adoption among organisations are limited. Therefore, the findings of this study contribute to the current body of knowledge on AI adoption among organisations. The results of this SLR can also help managers make the right decisions and build effective strategies for adopting AI among organisations.
PERENCANAAN TEKNIS DRAINASE JALAN SAUDARA KOTA MEDAN

ABSTRACTJalan Saudara which is located in Medan Kota Subdistrict the city of Medan with the boundary between the Jalan SM Raja intersection and the Jalan Bahagia intersection with a length of 743 m is very prone to flooding, especially during the rainy season. The dimensions of the drainage channels are small and vary between open and closed channels. Drainage problems on your road a) The area of the inundation area is 1000 meters, b) The width of the inundation area is 6 m, c) The inundation height is 20 cm, d) Inundation duration is 15 minutes, e) Inundation frequency is every heavy rain and f) The causes of flooding are due to the dimensions of the canal small and there is a blockage of several damaged culverts. The aim of the research is to design the dimensions of the drainage channels along Jalan Saudara so that they can accommodate all water waste activities and are expected to overcome flooding in the area. The methodology is carried out by analyzing hydraulics and hydrological analysis to determine the calculation of maximum rainfall, rainfall intensity, time of concentration and discharge of runoff, flow velocity in drainage channels, design of channel discharge, and design of channels. The calculation results obtained a) The intensity of maximum rainfall with the analysis of various methods, it was found that the Log Pearson III method was the best used. This was done by statistical tests with chi-square and with Smirnov-Kolmogorov, b) The detailed design of the drainage using precast concrete in the form of a closed U-Ditch with dimensions of 120 cm x 100 cm with a height varying between 120 cm and 160 cm. c) At a certain point, drainage using Box culverts with dimensions of 150 cm x 100 cm with a height of 150 cm.Kewords: Saudara Street, Drainage, Technical Planning
UI/UX Design for Mobile-based Sports Instructor Search Application “Befind” using Design Thinking

BeFind is a website-based application that facilitates the public and sports instructors to be able to interact and transact with each other. However, the website has deficiencies such as incomplete features and inflexible use, so it is necessary to design a mobile-based application to optimize the features. The purpose of this research is to produce UI and UX model designs that apply the Design Thinking method and to find out the results of usability testing. Design Thinking is a product design process resulting from problem-solving efforts that arise from potential product users. Empathy stage, conduct interviews to get problems. The define stage is carried out by creating a user persona from the results of the interview. The ideate stage is carried out by brainstorming to compile user flow. The prototype stage is made in the form of a mockup design and a prototype design is prepared. The test phase was carried out to test the design with task scenarios on 4 usability aspects and 1 aspect using the System Usability Scale (SUS) questionnaire. In the final test for service seekers and service providers respondents obtained 97% and 96% learnability results, efficiency 0.033689182 goals/sec and 0.033689182 goals/sec, 96% and 95% memoryability, 0.0306 and 0.0800 errors, and satisfaction with SUS obtained 94 results with the best imaginable predicate. In efficiency there is a decrease in yield caused by a bad signal factor. The resulting UI and UX can become the foundation for development of the "BeFind" mobile application based on the prototype design that has been designed in this study.
Integration of Social Media in Website Based School Information System

Information systems and social media are a form of rapid development in the era of society 5.0. Both of these can be used in an agency in disseminating information and can be used as promotional media. One institution that is very closely related to this is an educational institution. An existing educational institution has used social media and a website-based information system. SMK PGRI 1 Bangkalan is one of the vocational schools in Bangkalan Regency which does not yet have a website and social media accounts to disseminate information. A website-based social media integrated information system is one of the recommendations in solving this problem. This study uses the waterfall research model in developing the system. The results of this research are a website-based school information system that is integrated with social media, namely WhatsApp and Instagram. In addition, the website that has been created also meets several quality aspects of ISO 25010, namely functional suitability which gets a percentage of 100% and is declared very good, portability which gets a percentage of 100% and is declared very good, performance efficiency which has an average speed of 1,193 which fall into the very good category, and the usability aspect which gets a percentage of 90% and is declared very feasible.
Antecedents and consequences of the “cancel culture” firestorm journey for brands: is there a possibility for forgiveness?

ABSTRACTThis paper aims to discuss the antecedents and consequences of cancel culture and assess if brands can gain the forgiveness of consumers and mitigate the damages of social media firestorms, that usually evolve from online abuse (e.g. cyberbullying, harassment, and offensive talk). A quasi-experiment study was conducted through an online survey simulating the cancellation journey. Results show that cancel culture is triggered by ideological incompatibilities such as religion, racism, animal rights, LGBTQIA+ and environmental issues. After the scenario that simulated an ideological incompatibility related to racism, 178 respondents rated high levels of brand hate, negative WOM, brand avoidance, brand boycott, brand retaliation, and intention to cancel the brand. However, an ‘apology’ by the brand leads to brand forgiveness, a decrease in the intention to cancel the brand and an increase in purchase intention.KEYWORDS: Brand forgivenessbrand hatecancel cultureideological incompatibilitiesapology Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1. https://www.theguardian.com/commentisfree/2020/feb/24/victorias-secret-woke-lingerie-diversity.2. https://www.forbes.com/sites/joanverdon/2021/03/18/time-for-mr-monopolys-get-woke-moment/.3. https://www.nytimes.com/2021/02/25/business/mr-potato-head-gender-neutral.html.4. https://fortune.com/2021/02/11/aunt-jemima-new-name-pearl-milling-company/.Additional informationNotes on contributorsCláudia CostaCláudia Costa finished the master’s degree in Marketing and Strategy at the University of Minho, where she also did her Bachelor’s degree in Management. Cláudia’s major interest lays in the consumer-brand relationship, with a special focus on the current social media context. She is also eager to redefine the role of social media marketing when it comes to a brand’s image and its values in the current society (e.g., feminism, minority empowerment, and overall representation).António AzevedoAntónio Azevedo is an Assistant Professor in the School of Economics and Management of University of Minho, Braga, Portugal. His primary research topics are tourism marketing, place marketing, destination branding, celebrity branding, advertising processing, and marketing strategy amongst others. He has published several articles in international academic journals and international conferences. He is also researcher of the Lab2PT Investigation Unit - Laboratory of Landscape, Heritage and Territory (University of Minho).
Transform hate speech in education from gender perspectives. Conceptions of Chilean teachers through a case study

The research presented is positioned under the issue of hate speech prevalent in society, particularly its emergence in schools. In recent years, we have witnessed the presence of a phenomenon that is not new; however, it poses challenges to the teaching and learning processes for educators. Specifically, feminist movements and those advocating for diversity and nonconformity have triggered a strong response filled with violent and discriminatory messages and actions. To obtain some answers to this challenge, a case study was conducted with 6 teachers from various schools in Chile. Semi-structured interviews were carried out to explore, from their perspectives, aspects such as the origins of hate speech, the possibilities and proposals that teachers have for creating counter-narratives against hate, the effects of hate messages from gender perspectives in their teaching practices, and finally, the processes carried out with students. Among the main conclusions, it can be mentioned that there is a violent disruption that deepens gender inequalities, a situation that is becoming normalized and is of great concern for educators. Teachers express that they lack the tools and competencies to address these problems, other than continuing with the treatment of official content.
Development of Multimodal Mathematics and Indonesian Language Books for Elementary School Learning in Bandung Barat

This study aims to (1) develop multimodal mathematics and Indonesian language books for learning in elementary schools, (2) determine the feasibility level of multimodal mathematics and Indonesian books for learning in elementary schools. This study used the Borg and Gall development model research method which consisted of (1) preliminary study, (2) initial product development, (3) expert validation and product revision, (4) limited field trials and product revision, (5) test try the field and the final product. The resulting product is an Android-based learning media in the form of multimodal books for learning mathematics and Indonesian in elementary schools with the subject, integer arithmetic operations, mixed integer arithmetic operations, determining mixed arithmetic operations with whole numbers, looking for main ideas and writing poetry in elementary schools. Based on the formulation of the problem, research results, and discussion, the results of this study can be concluded that (1) the development of Multimodal Book considered several product characteristics, namely, (a) students play an active role, (b) precise and consistent language, (c) music selection, background, buttons, types, colors, attractive letters, (d) animations and images support elementary school students' understanding, (2) multimodal Mathematics and Indonesian Language Books for Elementary School Learning are appropriate to use and can improve the learning of Mathematics and Indonesian Language for Elementary School students in West Bandung Regency.
Penerapan simple multi attribute rating technique exploiting ranks method dalam pemilihan jenis tanaman pangan di Desa Bandar Kwala

In the field of agriculture in Indonesia, there are forms or types of plants, one of which is food crops. Currently, the food crops that develop in Bandar Kwala village are rice, corn, peanuts, and cassava. So that there is competition for nutrient absorption between plants and many types of plant-disturbing organisms that appear and cause farmers to experience crop failure, the selling price in the market is not proportional to the price of the seeds they buy and the care they do. For each type of plant that is planted, it is necessary to pay attention to the factors that affect the growth of a plant, one of which is land management, seeding, fertilization and pest control. The purpose of this research is to apply the SMARTER method to get the ranking of plants suitable for planting on agricultural land in Bandar Kwala village based on food crop criteria. In the SMARTER method, the ranking results are obtained by looking at the final value obtained by each alternative, where the alternative rice plant gets a final value of 0.9581 as the first rank, the cassava plants alternative gets a final value of 0.2628 as the second rank, the alternative to peanut plant gets the final score was 0.2354 as the third rank, and the alternative maize crop obtained a final score of 0.0899 as the fourth rank.Keywords: Plant, decision, rank, SMARTER MSC2020: 90B50
Comparison of Triple Exponential Smoothing and Support Vector Regression Algorithms in Predicting Drug Usage at Puskesmas

Drug management is important in managing adequate drug supplies in Puskesmas, to avoid errors in controlling existing drug stock inventory, it is necessary to predict the amount of drug usage by comparing Data Mining methods and Machine Learning methods, using the Triple Exponential Smoothing (TES) and Support Vector Regression (SVR) algorithms. Implementation is done using the Python programming language. The data used is Amlodipine 10 mg and Amoxicillin 500 mg drug data with a period of 42 months, from January 2020 - June 2023. This study aims to determine the best algorithm by comparing prediction error rate using the Mean Absolute Percentage Error (MAPE) method. Based on research that has been conducted on Amlodipine 10 mg and Amoxicillin 500 mg drugs with a division of 80% training data and 20% testing data, the Triple Exponential Smoothing algorithm with an additive model produces MAPE values of 10.36% and 17.50% respectively with the "Good" category. While Support Vector Regression algorithm, with RBF kernel, complexity 1.0, and epsilon 0.1 produces MAPE values of 10.31% and 9.38% in the "Good" and "Very Good" categories, respectively. Based on this, it can be concluded that Support Vector Regression algorithm is better at predicting than the Triple Exponential Smoothing algorithm.
Information Technology Security Risk Management using the OCTAVE-S Method

The Salatiga City Population and Civil Registration Office is a regional device organization that already uses information technology in its business processes. Although they have taken advantage of the information system, they have not yet conducted an assessment of risk threats and have not run a risk management. The source of the problem is a problem in implementing risk measurement and management techniques using the Octave-S method that focuses on organizations with no more than 100 members. This technique is used to identify and analyze threats to critical assets in Salatiga City Population and Civil Registration Service. The results of analysis of such threats will be useful when performing mitigation plans in accordance with existing security practices. From the research that has been conducted, there are 2 areas of security practice that produce yellow stoplight status which is a sign that the organization has implemented security practices but is not yet perfect. Both areas of security practice will be selected as mitigation areas.In
Automatic graph construction and Exploring different types of LSTMs for Asian Hindi languages for Medical review Sentiment Analysis

Sentiment Analysis (SA) of medical reviews is crucial for improving healthcare outcomes. However, analyzing sentiment in low-resource languages such as Asian Hindi presents significant challenges. In this study, we propose an automatic graph construction approach to extract relevant features from medical reviews in Asian Hindi languages. We explore different types of Long Short-Term Memory (LSTMs), including traditional LSTMs, bidirectional LSTMs, and attention-based LSTMs, to classify the sentiment of medical reviews. Our proposed approach uses attention-based LSTM architecture and pre-trained Word2Vec embeddings to achieve high accuracy. We compare the proposed approach with existing models using various evaluation metrics, including accuracy, precision, recall, and F1-score. The results demonstrate that our proposed approach outperforms all existing models in terms of accuracy, achieving an accuracy score of 81%. These findings could have implications for improving healthcare outcomes by enabling better monitoring of patient feedback and identifying areas for improvement in medical services.
Few-shot object detection based on one-stage detector and meta-learning

There has been rapid progress in the development of object detection methods. A challenging problem of deep neural networks based object detection algorithms is they rely heavily on abundant training samples. When dealing with scenarios where samples are scarce, the accuracy of these models can degrade sharply, thus hampering their final efficacy. Recently, the emergence of few-shot detection methods has addressed this issue. The majority of existing research in the literature concentrates on constructing few-shot detection models based on two-stage object detectors due to their high capacity and compatibility with affiliated structures. As a result, these methods are capable of delivering high-performance object detection with a limited number of training samples. However, two-stage backbones often imply a lower inference efficiency as well as applicability with deployment on edge devices. To realize high-speed object detection specifically in computation resource-constrained scenarios, we propose a one-stage few-shot object detector by integrating a meta-learning structure with YOLOv3 model. Experimental results demonstrate that our proposed few-shot object detector achieves comparable detection accuracy to existing two-stage object detectors under the same training conditions. Meanwhile, it significantly prompts the inference speed, enabling real-time object detection in videos.
Yolov5-PB: a traffic sign detection algorithm based on deep learning

For the real road environment, the proportion of traffic sign targets is small and not easy to be detected, and the recognition background is complex and changeable, resulting in the problems of low detection precision and poor robustness. In this paper, a traffic sign detection algorithm based on improved Yolov5-PB is proposed. The algorithm uses the ParC-Net as the backbone feature extraction network to fully extract the target feature information. The BiFPN structure is adopted to enhance the feature fusion ability of the network for multi-scale traffic signs. Simulation is carried out on TT100K and GTSDB traffic sign datasets, and the results show that the mAP@0.5 of Yolov5-PB algorithm reaches 85.6% and 72.2%, respectively, which are 3.1% and 19.2% higher than Yolov5. The precision reaches 85.3% and 71.6%, respectively, which are 0.3% and 21.8% higher than Yolov5. Furthermore, compared with the current mainstream target detection algorithms, the proposed algorithm can achieve better detection precision and meet the requirements of real-time detection, and has better robustness.
Framing Culture in EFL Textbooks: A Critical Discourse Analysis at Islamic School

This present study aims to explore the cultural values represented in the local EFL textbook as a source of learning materials in Islamic Junior High Schools. This study implemented a qualitative approach as a research design. Three English teachers as participants were recruited purposively. The data collected from textbook analysis using the types of speech acts, and politeness strategies through the theory of Critical Discourse Analysis. Semi-structured interviews were conducted to strengthen the data. Then, the data were analyzed thematically. The study revealed that local English textbooks effectively represented cultural values and beliefs. The finding showed that the EFL local textbooks effectually encourage cultural awareness and English language proficiency among students. The cultural values performed in the textbook are greetings, politeness, self-introduction, hobbies, and family interactions, which exhibit the polite culture of how Indonesians communicate. The representation of family lunch highlighted the tradition that shapes Indonesian culture. Additionally, it implied that the teachers perceived the content in the textbook because it highlights moral values that are suitable in Indonesian culture. It has a significant implication for establishing English curricula to construct a proper local English textbook for Islamic junior high school students. This study demonstrated that local English textbooks included interesting and collaborative activities that highlighted Islamic traditions, fostering tolerance and respect. It also highlighted moral and cultural values that students could use to develop good manners.