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International Journal of Applied and Advanced Multidisciplinary Research (IJAAMR)
Published by MULTITECH PUBLISHER
ISSN : -     EISSN : 30262437     DOI : https://doi.org/10.59890/ijaamr.v1i2
Core Subject : Economy, Humanities, Education, Social, Engineering,
Humanities Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Education Social Sciences
International Journal of Applied and Advanced Multidisciplinary Research (IJAAMR) is a multidisciplinary journal that publishes high quality research papers in the areas of Business Management, Agriculture, Information Technology, Engineering, Health & Life Science, Zoology, Humanities, Applied Sciences, Biology, Criminal Justice, History, Public Administration, Political Science, Sociology, Social, English, Science, Mathematics, Human Resource Management, Accounting, Business Administration and Management, Computer Science, Communication, etc. International Journal of Applied and Advanced Multidisciplinary Research (IJAAMR) publishes articles monthly.
Arjuna Subject : Teknik (semua kategori) - Teknik Sipil dan Struktur
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 3 (2023): November 2023" : 5 Documents clear
Customized Education Artificial Intelligence's Role In Tailored E-Learning. Kanbur, Gaurang; Meenakshi Thalor
International Journal of Applied and Advanced Multidisciplinary Research Vol. 1 No. 3 (2023): November 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijaamr.v1i3.469

Abstract

This research is driven by the immense potential of personalized e-learning systems to address the challenges of effective online education delivery. It focuses on proposing an efficient architectural framework for personalized e-learning systems, exploring various techniques and challenges and offering innovative solutions. The paper conducts a thorough review of current state-of-the-art methodologies in implementing personalized e-learning systems, along with discussions on the crucial requirements and challenges for successful deployment. Furthermore, it presents an efficient framework for building effective e-learning systems, while also discussing mechanisms, challenges and future research directions that the research community can consider. The subsequent sections of this paper provide a detailed exploration of the research, followed by a proposal for a personalized learning system, and insights into important issues for the community to address. The paper concludes by summarizing its findings and contributions.  
Psychological Emotion Recognition of Students Based Chatbot Senapati, Atharva; Anuja Phapale
International Journal of Applied and Advanced Multidisciplinary Research Vol. 1 No. 3 (2023): November 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijaamr.v1i3.565

Abstract

In the context of modern education, where students' emotional well-being plays a crucial role in academic success, the integration of technology, particularly machine learning-based chatbots, presents a promising avenue to support and recognize the psychological states of students. This paper delves into the development and evaluation of a chatbot system designed to recognize and respond to the emotions expressed by students. Leveraging natural language processing and sentiment analysis, the chatbot engages in conversations with students, allowing for the real-time recognition of emotional states. Our study does not only focus on the technical aspects of emotion recognition but also exploration the implications and ethical considerations of deploying such technology in educational settings. By shedding light on the potential of machine learning-based chatbots to enhance emotional support and understanding within educational environments, this research contributes to the ongoing dialogue on students well-being and the role of technology in education.
Fortifying Data Security: Node.js Authentication, Authorization, and the Dark Web Influence in Modern Web Apps Shah, Sarthak; Anuja Phapale
International Journal of Applied and Advanced Multidisciplinary Research Vol. 1 No. 3 (2023): November 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijaamr.v1i3.679

Abstract

This paper delves into the crucial aspects of authentication and authorization in modern web applications with a focus on enhancing data security. It explores the use of Node.js, a versatile server-side language, for building web applications and discusses the significance of a secure website for establishing trust between clients and servers. The research covers the implementation of authentication using packages and hashing algorithms, emphasizing the importance of "salt" and "pepper" for password security. Authorization methods, including cookies, sessions, and middleware, are also explored. The paper highlights the necessity of robust security measures to safeguard user data from the dark web and points to future directions in web security, including the role of blockchain and artificial intelligence in the WEB3 landscape.
Targeted Display Advertising using Machine Learning Chaitali Khachane
International Journal of Applied and Advanced Multidisciplinary Research Vol. 1 No. 3 (2023): November 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijaamr.v1i3.715

Abstract

This paper delves into the intricate challenges of problem formulation and data representation in the context of a large-scale machine learning system for targeted display advertising. Unlike traditional models, this system is not just conceptual but has been operational for years across thousands of advertising campaigns. Since obtaining ideal training data is cost-prohibitive, data is sourced from related domains and tasks and then adapted for the target task. The paper outlines the architecture of this multi-stage transfer learning system, emphasizing the problem formulation aspects. Extensive experiments demonstrate the value of each transfer stage. Real-world results with diverse advertising clients from various industries showcase the system's performance. The paper concludes with valuable insights gained from over half a decade of work on this complex, widely deployed machine learning system.
The Influence Of Providing Rewards And Reinforcement On Stuedent Learning Outcomes In Class IV Mathematics At State Primary School 106143 Sukamaju School Year 2022/2023 Abi, Antonius Remigius; Sitanggang, Paskah Afriani; Lumbanraja, Bogol; Regina Sipayung; Rumiris Lumban Gaol
International Journal of Applied and Advanced Multidisciplinary Research Vol. 1 No. 3 (2023): November 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijaamr.v1i3.802

Abstract

  This study aims to determine the effect of giving rewards and reinforcement on student learning outcomes in mathematics in class IV at SD Negeri 106143 Sukamaju for the 2022/2023 academic year. In this study, researchers used quantitative methods. The population used was all students at SD Negeri 106143 Sukamaju with a sample of 31 students. Sampling using nonprobability sampling. The results of this study indicate that the results obtained from correlation test can be seen in the correlation coefficient of r (count) 0.689 ≥ r (table) 0.355, it can be concluded that the alternative hypothesis (Ha) is accepted, that is, there is a significant effect between reward and reinforcement on student learning outcomes at SD Negeri 106143 Sukamaju. It can also be seen from the results of the t-test where t (count)> t (table) is t (count) of 5.113 and t (table) of 2.042, then the hypothesis (Ha) is accepted. This shows that there is a significant positive effect between the provision of rewards and reinforcement and mathematics learning outcomes in class IV of SD Negeri 106143 Sukamaju for the 2022/2023 academic year.

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