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All Journal Journal International Journal of Teaching and Learning (INJOTEL) Management Studies and Business Journal
Erlangga, Irwan Syah
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Other

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DIGITAL TRANSFORMATION IN EDUCATION: CHALLENGES AND OPPORTUNITIES IN THE MODERN ERA Erlangga, Irwan Syah; Frandy Putra Perdamen Tarigan; Lantri Ternasih; Dede Umar
International Journal of Teaching and Learning Vol. 2 No. 12 (2024): DECEMBER
Publisher : Adisam Publisher

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Abstract

Digital transformation in education has become a phenomenon that has significantly changed the way of teaching and learning in the modern era. On the one hand, this transformation offers various opportunities, including increased accessibility of education through online platforms, the development of more interactive teaching methods, and increased personalization in learning. Students can now access learning materials from leading institutions globally, while also gaining a more engaging learning experience through the use of technology such as augmented reality and gamification. However, the challenges that arise cannot be ignored. The digital divide remains a problem, with not all students having equal access to the necessary technology, as well as a lack of training for educators in using digital tools effectively. In addition, the issue of data security and protecting student privacy is increasingly important amidst the increasing use of digital platforms. Developing a curriculum that is relevant to industry needs and digital skills is also a challenge in itself, considering the rapid changes in the world of work. To overcome this challenge, collaboration between educational institutions, industry and government is needed to create an inclusive and adaptive educational ecosystem. With the right approach, digital transformation can bring great benefits to education, producing graduates who are ready to face global challenges and contribute positively to society. Thus, this research aims to analyze in depth the challenges and opportunities faced in the current digital transformation process in education.
Enhancing Quality Management through Advanced Statistical Techniques Nugroho, Cahyo Adi; Perdana, Janatika Putra; Tirtoadisuryo, Dendy; Rachmat, Asep Ferry; Erlangga, Irwan Syah
Management Studies and Business Journal (PRODUCTIVITY) Vol. 1 No. 9 (2024): Management Studies and Business Journal (PRODUCTIVITY)
Publisher : Penelitian dan Pengembangan Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62207/vbrcgz16

Abstract

Production environments with high variability present challenges in maintaining quality consistency, which are difficult to address using traditional approaches. This research aims to evaluate the impact of machine learning (ML)-based optimization on long-term quality management in industrial sectors that experience high production fluctuations. Using a systematic literature review approach with the PRISMA method, this research analyzes 18 studies related to the implementation of ML in quality process optimization. Results show that ML significantly supports product stability, defect reduction, and sustainable operational efficiency. The implications of this research strengthen the application of ML as a relevant and effective method for improving long-term quality in dynamic production environments.
The Role of AI in Enhancing HRM Practices A Comparative Study Across Industries Wibowo, Eko Putro; Avian, Zakhi Bailatul Nur; Tarigan, Frandy Putra Perdamen; Erlangga, Irwan Syah; Soenanta, Andy
Management Studies and Business Journal (PRODUCTIVITY) Vol. 1 No. 9 (2024): Management Studies and Business Journal (PRODUCTIVITY)
Publisher : Penelitian dan Pengembangan Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62207/yqwrzp72

Abstract

Application of artificial intelligence (AI) in Human Resource Management (HRM) is increasingly important in various industries to increase employee engagement and productivity. However, the impact of AI in HRM varies based on the specific characteristics of each industry, such as technology, manufacturing, services, and healthcare, demanding a targeted approach. This research aims to provide a comprehensive analysis of the role of AI in increasing employee engagement and productivity through a systematic literature review that examines research methods, industry distribution, and contextual factors that influence the effectiveness of AI in HRM. Using PRISMA methodology, a number of studies that met the inclusion and exclusion criteria were selected for analysis. The research results show that AI has a positive impact on employee engagement and productivity, but the impact varies across industries, influenced by organizational culture, skills requirements, and ethical and legal regulations. These findings provide guidance for HRM practitioners in effectively adopting AI according to the unique needs of each sector.
Co-Authors Avian, Zakhi Bailatul Nur Dede Umar Frandy Putra Perdamen Tarigan Lantri Ternasih Nugroho, Cahyo Adi Perdana, Janatika Putra Rachmat, Asep Ferry Soenanta, Andy Tarigan, Frandy Putra Perdamen Tirtoadisuryo, Dendy Wibowo, Eko Putro