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All Journal INFOKUM International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET)
Perianus lombu
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education

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APPLICATION OF INTELLIGENT SYSTEMS (DEEP LEARNING) TOWARDS THE USE OF AI APPLICATIONS IN DAILY LIFE (PANCABUDI UNIVERSITY MEDAN) Ardiansyah; Aldy Agustian; Perianus lombu; Kiki Wulandari; Muhammad Syahputra Novelan
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 4 No. 11 (2025): OCTOBER
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijset.v5i1.1566

Abstract

As technology advances in this digital era, technology has become a very important thing for human life and has a dependency, marked by the use of digital machines that cause very rapid, significant changes to all sectors of human life, making it easier for humans to carry out activities and have dependencies. Artificial intelligence or better known as AI (Artificial Intelligence) is a major supporter in the development of intelligent systems (Intelligence Systems) that increase efficiency and innovation in various sectors of life. Therefore, the latest advances in AI's predictive capabilities can create a productive work environment. Although AI offers great potential to encourage innovation and better decision-making, there are also challenges in the use of AI such as ethical issues, data security, and infrastructure limitations that must be overcome to ensure responsible use.
CHANGES IN THE SOCIETY ENVIRONMENT ON THE EFFECTIVENESS OF COMPUTER NETWORK DISTRIBUTION Aldy Agustian; Ardiansyah; Perianus Lombu; Kiki Wulandari; Muhammad Amin
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 4 No. 10 (2025): SEPTEMBER
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijset.v5i1.1567

Abstract

The proliferation of computer networks has significantly impacted various aspects of social life. This study aims to identify and analyze the social changes resulting from the integration of computer networks into everyday life. Using a mixed-method research design, data were collected through a survey involving 300 respondents and in-depth interviews with 40 informants. The results indicate that computer networks increase the frequency of communication with family and friends (78%), facilitate access to information and education (70%), and enable more flexible work and education patterns, with 60% of respondents working from home and 50% participating in online learning. Furthermore, computer networks also increase economic opportunities such as online jobs and e-commerce businesses (68%). However, the study also reveals a digital divide, particularly in rural areas (40%), indicating the need for further efforts to ensure the equitable distribution of the benefits of technology. This study provides in-depth insights into the impact of computer networks on social transformation and can be used as a reference for policymakers, educators, and information technology professionals in developing effective strategies to leverage this technology for social and economic progress.
Digital Technology in Higher Education: Integrating Learning Analytics and Adaptive E-Learning to Improve the Quality of Student Learning Robet H Silaban; Muhammad Irfan Sarif; Perianus Lombu; Aldy Agustian; Larasati Rince Pratita Ritonga
INFOKUM Vol. 14 No. 02 (2026): Infokum, March-April 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i02.3081

Abstract

This study aims to analyze the influence of digital technology through the integration of learning analytics and adaptive e-learning on the quality of student learning in higher education. The study used a quantitative approach with an explanatory research type. Data were collected through a Likert-scale questionnaire to 120 students who use digital learning systems. The data analysis technique used multiple linear regression with the help of statistical software. The results of the study showed that learning analytics and adaptive e-learning partially and simultaneously had a positive and significant effect on the quality of student learning, with a significance value of 0.000 < 0.05. The coefficient of determination (R²) value of 0.62 indicates that 62% of the quality of learning is influenced by these two variables. This technology integration has been proven to increase student engagement, effectiveness, and learning outcomes. Thus, the application of learning analytics and adaptive e-learning can be an effective strategy in improving the quality of learning in higher education.
Co-Authors Aldy Agustian Ardiansyah KIKI WULANDARI Larasati Rince Pratita Ritonga Muhammad Amin Muhammad Irfan Sarif Muhammad Syahputra Novelan Robet H Silaban