Article Per Year (5 Year)
p-Index From 2019 - 2024
0.61
P-Index
This Author published in this journals
All Journal Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Indonesia Journal of Engineering and Education Technology (IJEET)
Daniel Pasaribu
Unknown Affiliation
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Education Social Sciences

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Government with Algorithm: Strategy to Improve Synchronous Public Service Using Artificial Intelligence (AI) in Indonesia Faizal Madya; Rulinawaty Rulinawaty; Daniel Pasaribu
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 5, No 2 (2022): Budapest International Research and Critics Institute May
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v5i2.5272

Abstract

This study reviews how government by algorithm uses AI in the public sector. Artificial intelligence has been heralded as the next source of business value in the public and private sectors. Building on organizational resource-based theory and recent work on AI in organizational contexts, this study (1) identifies AI-specific resources that together create AI capabilities, (2) develops models to capture AI capabilities in public services, and (3) looks at public trust capabilities, and (3) examines the relationship between AI capabilities and creativity and organizational performance. The research method uses a qualitative approach with a case study strategy. This type of case study is explanatory. Empirical findings show that Artificial Intelligence (AI) changes how government agencies carry out their functions and roles to improve performance, compliance, and security activities in public service and public goods. Rapid developments in AI can reduce essential governance costs and improve quality and power-based administrative data so that government performance is more efficient and effective. The implications prove that AI capabilities result in increased creativity and organizational performance.
Public Opinion Formation in the Digital Age : A Review of Literature Diah Fatma Sjoraida; Bucky Wibawa Karya Guna; Aat Ruchiat Nungraha; Daniel Pasaribu; Novianty Djafri
Indonesia Journal of Engineering and Education Technology (IJEET) Vol. 2 No. 2 (2024): Indonesia Journal of Engineering and Education Technology (IJEET)
Publisher : AKADEMI TEKNIK ADI KARYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61991/ijeet.v2i2.52

Abstract

The digital age has brought significant changes in the way people access and process information. Social media and other online platforms have become a major source of information and public opinion. This study aims to review the literature on public opinion formation in the digital age. This study uses the literature review method to analyze literature relevant to the research topic. A literature review shows that the digital age has had a significant impact on the formation of public opinion. Social media and other online platforms have become the primary means for individuals to access information, share ideas, and exchange opinions. This has led to changes in the way public opinion is formed and disseminated. The formation of public opinion in the digital age is a complex and dynamic phenomenon. Social media and other online platforms have an important role to play in shaping public opinion. A better understanding of the process of forming public opinion in the digital age is needed to develop effective communication strategies and build a more democratic society.
The Impact of Machine Learning Technology on E-Learning Platforms on Student Learning Behavior Asrul Sani; Tomi Apra santosa; Ratih Dheviana Puru Hitaningtyas; Daniel Pasaribu; Yohanis Yakubun
Indonesia Journal of Engineering and Education Technology (IJEET) Vol. 2 No. 2 (2024): Indonesia Journal of Engineering and Education Technology (IJEET)
Publisher : AKADEMI TEKNIK ADI KARYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61991/ijeet.v2i2.77

Abstract

This study aims to determine the influence of Machine Learning Technology on the E-Learning Platform on student learning behavior. This research is a type of meta-analysis research. The data source comes from 10 national journals indexed by SINTA published in 2022-2024. Deep collection technique through direct observation. The process of searching for virgin sources through google scholar, ERIC, and IEEE. Data analysis is statistical data analysis by calculating the effect size value with the help of the JSAP application. The results of the study concluded that the average effect size value was 0.791 in the medium effect size category. These findings explain that there is a significant influence of machine learning technology on e-learning platforms on student learning behavior.
Co-Authors Aat Ruchiat Nungraha Asrul Sani Bucky Wibawa Karya Guna Diah Fatma Sjoraida Faizal Madya Novianty Djafri Ratih Dheviana Puru Hitaningtyas Rulinawaty Rulinawaty Tomi Apra Santosa Yohanis Yakubun