The Impact of Kahoot! And Quizizz to Teach English Tenses for Flyers

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Mastering English tenses is crucial for A2 Flyers students, enabling them to expand their language proficiency and excel in English examinations such as the Cambridge test. However, many schools and centers solely rely on traditional grammar-based teaching methods and paper exercises, resulting in student disinterest. To address this issue, educators must incorporate modern technological tools to cultivate students’ enthusiasm for learning tenses. Kahoot! and Quizizz present promising opportunities for both teachers and students. This research aims to investigate the effectiveness of using Kahoot! and Quizizz in teaching English tenses to Flyers. Participants in the study are A2 level students at Phuong Nam Language Center. Quantitative data was gathered through pre-test and post-test assessments, while qualitative data was obtained through questionnaires and semi-structured interviews. The test scores indicated a significant improvement in students’ academic performance, with the mean score increasing from 4.50 in the pre-test to 7.55 in the post-test, indicating notable progress. Moreover, the results highlighted the students’ heightened engagement during the teaching and learning process, particularly with the use of Kahoot! and Quizizz. Consequently, these quiz applications proved to be beneficial tools for teaching English tenses to Flyers.

Circular Economy Transformation in Chemical Industry: Integrating CRM and AI for Sustainable Growth

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This white paper explores the pivotal role of Customer Relationship Management (CRM) in the digital transformation journey of the chemical industry. As customer expectations continue to evolve and competition intensifies, chemical companies are turning to CRM solutions to enhance customer interactions, streamline operations, and drive business growth. The abstract provides an overview of CRM’s significance in the chemical sector, highlighting its role in customer segmentation, sales automation, marketing optimization, and customer service enhancement. By centralizing and optimizing customer-related processes, CRM enables chemical companies to deliver personalized experiences, improve sales productivity, and foster stronger customer relationships. Through a comprehensive examination of CRM implementations and potential applications in the chemical industry, this white paper aims to provide valuable insights for industry professionals seeking to leverage CRM to navigate the challenges and opportunities of the digital age.

A Comparison of Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM) in River Water Quality Prediction

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River water is a crucial natural resource utilized for various purposes, including agriculture and drinking. Human activities such as mining, industrial discharge, and improper waste management contribute to river water pollution, affecting its quality and posing risks to human health. Monitoring and predicting river water quality are essential for effective management and pollution control. The research focuses on Dissolved Oxygen (DO), and comparing of Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM) to developed prediction models. Evaluation of the models’ performance shows that the ANN model outperforms LSTM in predicting Dissolved Oxygen (DO) concentrations, achieving lower Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). Although LSTM exhibits lower Mean Squared Error (MSE), the ANN model demonstrates better accuracy in minimizing the average distance between predicted and actual values. The findings suggest that ANN-based models offer good performance in river water quality prediction, with potential for further enhancement through additional variables or model architecture adjustments.

Quality Laying Hen Eggs through Soaking Guava (Psidium guajava) Leaves Extract

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This study aims to determine the extent to which the concentration of guava leaves extract (Psidium guajava) and storage time affect the quality of laying hen eggs. Food materials such as laying hen eggs are easily perishable, meaning that they will deteriorate in quality within 14 days of being stored at room temperature, and will even rot soon after. This study aims to determine the effect of giving guava leaf extract (Psidium guajava) and soaking time on the quality and shelf life of eggs. The method used was a Completely Randomized Design (CRD) with a factorial pattern consisting of 2 factors. Factor A is the concentration of guava leaves extract (Psidium guajava) solution and factor B is the storage time with 3 replications. The treatments used were: Factor A concentration of guava leaf extract solution A1 = 0%, A2 = 15%, A3 = 30%, and A4 = 45%. Factor B storage time B1 = 0 days, B2 = 7 days B3 = 14 days. The variables analyzed in this study were egg weight loss, egg white index, and yolk index. The data obtained were analyzed using the ANOVA test. If there is a significant difference between treatments, it will be continued with the Duncan Test. The results of the ANOVA analysis showed that the interaction had no significant effect (P>0.05) on the egg white index and egg yolk index. Giving each concentration gave good results in egg weight loss. Meanwhile, the egg white index and egg yolk index showed good results with a concentration of 15%. It is concluded that giving guava leaves extract (Psidium guajava) and storage time can maintain the quality and extend the shelf life of laying hen eggs.

Biomorphological Features and Anatomical Structure of the Leaf of the Akmella Plant

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 In this article, there are determined the anatomical structure of the leaves of the vegetative organs of the Acmella plant has been studied, and diagnostic and adaptive structural features. Also, the localization of biologically active substances in assimilative organs is explained on the basis of anatomical studies.

The Effect of Intellectual Capital, Leverage and Company Size on Profitability and its Impact on Company Value of Sub-Sector Food and Beverage Registered on the Indonesian Stock Exchange Period 2012 – 2022

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This study aims to determine the effect of intellectual capital, leverage, and company size on profitability and their impact on company value in the food and beverage sub-sector.

This research is quantitative empirical research using hypothesis research that examines the significant influence and direction of the direct and indirect relationship between the independent variables and the dependent variable through the intervening variable. This study used a sample of food and beverage sub-sector companies listed on the IDX for 2012–2022 using a purposive sampling method where 45 companies were obtained from the population and 14 companies were selected according to predetermined criteria.

Based on statistical test results, it was found that intellectual capital partially had a negative and insignificant effect on profitability, while leverage and company size had a positive and significant effect on profitability. Partially, intellectual capital, leverage and profitability have a positive and significant effect on company value, while company size has a negative and insignificant effect on company value. Partially, the results of the Sobel Test Path Analysis indirectly mean that profitability as an intervening variable is not able to mediate the influence of intellectual capital and leverage on company value, while directly profitability as an intervening variable is able to mediate the influence of company size on company value.

Synthesis of PVA/TiO2 Composite Layer over Conductive Textile Sheet Using Electrospinning Method for Enhancing Self-Cleaning Properties

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The present research used the electrospinning method to apply a polyvinyl alcohol/titanium dioxide (PVA/TiO2) layer over a conductive textile (70 % polyester and 30 % cotton) sheet. PVA with 10, 12.5, and 15 g concentrations was mixed into 100 ml distilled water. Then, each PVA solution was mixed with 1.5 wt.% of TiO2. Afterward, the electrospinning method applied a PVA/TiO2 composite onto a conductive textile sheet. Various characterizations were conducted, such as resistivity, scanning electron microscopy (SEM), Fourier transforming infrared (FTIR), and photocatalytic activity. The resistivity result is 9.5, 10, and 10  for A, B, and C samples. According to SEM investigation, higher PVA concentration leads to higher fiber sizes around 0.65 µm. An increase in PVA content does not affect the bands that were formed. The size of the fiber diameter contributed to the photocatalytic activity of MB. A smaller fiber diameter could enhance photocatalytic activity.

Analysis of Purchasing Intention in the Fashion Industry: Enhancing Product Sales through Live Commerce Streaming

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This study investigates the impact of live-streaming commerce on the Indonesian fashion industry, with a specific focus on small and medium-sized enterprises (SMEs). It explores how factors like perceived media richness, price fairness, electronic word-of-mouth (eWOM), social media marketing, and brand image influence consumer purchase intentions. The research methodology includes a survey of Indonesian consumers who have engaged in shopping for fashion products via live streaming at least once in the past three months. The findings analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), reveal the pivotal role of media richness, price fairness, and social media marketing in shaping purchase intentions, with brand image emerging as a key mediator. However, electronic word-of-mouth (eWOM) shows less impact. indicating a complex market dynamic. The findings highlight the effectiveness of live streaming as a marketing and sales tool in the digital era. The study contributes valuable insights for SMEs looking to optimize their digital strategies and enhance sales effectiveness in the rapidly evolving e-commerce landscape.

Adoption and Adaptation of Generative Artificial Intelligence in Organizations: Actions for Efficient and Responsible Use in Interaction with Collaborators

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The aim of this work was to determine the actions needed to adopt and adapt Generative Artificial Intelligence (GenAI) for efficient and responsible use in the organization, without affecting the contribution of the collaborator to his/her work activities. A bibliographic review of the scientific literature and information published by consulting companies on the current development of research related to GenAI and its impact on organizations was carried out. Artificial intelligence search tools, academic search engines were used, and criteria for the inclusion and exclusion of publications were established. As a result, necessary actions were identified for the adoption, adaptation, efficient and responsible use, and interaction of GenAI with employees in their work environment. These actions include the adjustment of processes, infrastructure, and resources; capacity-building for integration and a culture of innovation, protocol development, staff training, creation of flexible and supportive working environments, collaboration with regulators, transformation of work; and alignment of staff management practices. It was concluded that GenAI is having a major impact on organizations by automating processes and increasing productivity and efficiency. It is essential to address actions in three categories: staff training, fostering a culture of innovation, ethics, and accountability in the use of this technology, and its efficient adoption and adaptation without affecting the contribution of employees. This research helps to identify the elements needed to deepen research development and define, in real contexts, the effectiveness of the adoption and efficient adaptation of GenAI in internal processes and interaction with collaborators, with the aim of promoting best practices that generate value through its use.

Knowing How, Knowing Why, Knowing Whom: Examining the Alignment of the MBA Programs with the Intelligent Career Theory Framework (ICTF)

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This study explored the relationship between the Intelligent Career Theory framework (ICTF) and the MBA’s Program Educational Objectives (PEO). Employing a self-reported questionnaire survey with 11 MBA graduates from the past five years, the research examined graduates’ perceptions of the program’s effectiveness in fostering skills and knowledge aligned with the core ICTF components: Knowing Why (Intrinsic motivation and career goals), Knowing How (Knowledge & skills), and Knowing Whom (professional networks & mentors). Pearson’s correlation coefficients were utilized to analyze the relationship between these ICTF components and the program’s PEOs. The Permutations were employed to deal with the limitations of a small sample. The significant correlation between the ICTF components and PEOs with the relative strength of know-why and weakness of know-whom provide insight into the program’s alignment with career intelligence development. Recommendations for curriculum improvement and ongoing program evaluation based on the ICTF framework are presented. This study highlights the value of ICTF as a tool for enhancing MBA programs and empowering graduates for successful careers.