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All Journal International Transactions on Artificial Intelligence (ITALIC)
Cicilia Sriliasta
University of Esa Unggul
Computer Science & IT Control & Systems Engineering Library & Information Science

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Functions of Artificial Intelligence, Income Investment Instrument, and Crypto Money in Era of The Fourth Revolution Cicilia Sriliasta; Dewi Sri Surya Wuisan; Tatik Mariyanti
International Transactions on Artificial Intelligence Vol. 1 No. 1 (2022): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i1.205

Abstract

This research examines those related to Artificial Intelligence, stock robotics, and revenue intruments portfolio diversity in the context of the Fourth Industrial Revolution era, artificial intelligence, and concern for the environment. First, our results suggest that a portfolio of these assets is highly dependent, suggesting that large mutual losses are likely to occur during times of disruption in the economy. Second, it supports a large market mood in the near future, indicating that this disruption in the approaching time can increase the market mood of assets, while to support the market mood decreases for a long time.
Stepping Forward: Enhancing Cognitive Learning Outcomes through Hybrid RCCR-Based Learning on Circulatory System Material Cicilia Sriliasta; Dewi Sri Surya Wuisan
International Transactions on Artificial Intelligence Vol. 2 No. 1 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v2i1.404

Abstract

The time constraints at the end of the semester often lead to suboptimal delivery of circulatory system materials, which consequently affect students' learning outcomes. Hence, this research aims to delve into the impact of applying the RCCR (Reflect-Collaborate-Convey-Record) approach based on Hybrid Learning on enhancing cognitive learning outcomes. This study utilizes a quasi-experimental design, encompassing a control group with pretests and posttests, though they are not equivalent. Evaluation of cognitive learning outcomes involves multiple-choice questions in both the pretest and posttest phases. The data from these evaluations are quantitatively analyzed in-depth. After the learning process, the average posttest score for the control group reached 71.61, while the experimental group achieved a score of 81.25. Statistical analysis indicates a significant difference in posttest results between the experimental and control groups. The analysis of change scores (N-gain) also shows a significant difference between the experimental and control groups (p<0.05). These findings highlight a strong connection between cognitive learning outcomes and metacognitive skills mastery (r=0.83). Consequently, this learning model presents a valuable alternative for overcoming classroom time constraints and effectively enhancing cognitive learning outcomes.
Co-Authors Tatik Mariyanti Wuisan, Dewi