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Artificial Intelligence Integration and Students’ Digital Literacy as Determinants of Learning Outcomes in an Economics Education Assessment Course Supriyadi; Ayu Nurul Amalia
Jurnal Pendidikan Ekonomi Dan Bisnis (JPEB) Vol. 13 No. 01 (2025): Jurnal Pendidikan Ekonomi & Bisnis (DOAJ & SINTA 2 Indexed)
Publisher : Faculty of Economics, Universitas Negeri Indonesia,Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JPEB.013.1.8

Abstract

Education in the era of the Industrial Revolution 4.0 and Society 5.0 has undergone a substantial paradigm shift alongside the growing adoption of disruptive technologies, particularly artificial intelligence (AI), within learning processes. This study examines the influence of AI technology implementation and students’ digital literacy on learning outcomes in the Economics Learning Evaluation course. A quantitative survey design was applied involving fifth-semester undergraduate students enrolled in the Economics Education program. From a population of 90 students, a sample of 79 respondents was selected using random sampling based on the Isaac and Michael table at a 1% significance level. Data were collected through valid and reliable instruments and analyzed using partial regression and multiple regression techniques. The findings indicate that AI technology implementation and digital literacy each have a positive and statistically significant effect on students’ learning outcomes in the Economics Learning Evaluation course. The results confirm that the integration of AI technology, accompanied by adequate digital literacy, constitutes an essential factor in improving learning outcomes in economics education at the higher education level.
The Implementation of Artificial Intelligence (AI) Technology and Students' Digital Literacy on Learning Outcomes in the Economics Learning Evaluation Course Supriyadi Supriyadi; Ayu Nurul Amalia
Smart Society Vol. 6 No. 1 (2026): Smart Society
Publisher : FOUNDAE (Foundation of Advanced Education)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/smartsociety.v6i1.1002

Abstract

The rapid development of information technology requires students to possess adequate digital literacy skills to effectively access, evaluate, and utilize information in the learning process. At the same time, the implementation of Artificial Intelligence (AI) in education offers significant potential to enhance learning effectiveness, efficiency, and personalization. Therefore, it is important to examine how these two factors contribute to students’ academic achievement. This study aims to analyze the effect of AI implementation and digital literacy on students’ learning outcomes in the Learning Evaluation course. This research employs a quantitative method with a survey approach. The population of the study consists of 90 fifth-semester students from the Economic Education Study Program. A sample of 79 students was determined using the Isaac and Michael table at a 1% significance level, and selected through random sampling techniques. Data were collected using research instruments that had been tested for validity and reliability to ensure accuracy and consistency. The data were analyzed using partial regression and multiple regression techniques to examine both individual and simultaneous effects of the independent variables on the dependent variable. The results of the study reveal that: (1) the implementation of AI has a positive and significant effect on students’ learning outcomes; (2) digital literacy also has a positive and significant effect on learning outcomes; and (3) the implementation of AI and digital literacy simultaneously have a positive and significant effect on students’ learning outcomes. These findings indicate that both technological integration and students’ competencies in utilizing digital resources play crucial roles in improving academic performance. This study contributes by providing empirical evidence regarding the influence of AI implementation and digital literacy on student learning outcomes. The findings can serve as a reference for educators and institutions in designing effective learning strategies, improving the quality of higher education, and supporting the achievement of Sustainable Development Goal 4 (SDG 4), which emphasizes inclusive and quality education for all.
The Influence of Intellectual Capital on Corporate Financial Performance Dimas Novianto Kurniawan; Supriyadi Supriyadi; Rhoma Iskandar
Applied AI and Machine Learning Journal Vol 1 No 2 (2026): June
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/aiml.v1i2.4173

Abstract

Purpose: This study aims to examine and obtain empirical evidence on the effect of intellectual capital on the financial performance of food and beverage manufacturing companies listed on the Indonesia Stock Exchange (Bursa Efek Indonesia/BEI) during 2020–2024. Research Methodology: A quantitative approach was used with secondary data from annual financial reports. Intellectual capital was measured using the Value-Added Intellectual Coefficient (VAIC™), while financial performance was assessed through Return on Assets (ROA). The sample consisted of 12 companies, with 60 firm-year observations, analyzed using descriptive statistics, Pearson’s correlation, and simple linear regression with SPSS. Results: The study found that intellectual capital has a negative and statistically insignificant effect on financial performance (? = ?4.144E?05, t = ?0.232, p = 0.817), with an R² of 0.001, indicating that intellectual capital explains only 0.1% of the variation in ROA. The Pearson correlation between VAIC™ and ROA was ?0.030 (p = 0.409).. Conclusions: The findings suggest that intellectual capital does not significantly influence financial performance in the food and beverage sector. Other factors may explain the majority of the variation in ROA. The study contributes to the accounting literature by providing empirical evidence on intellectual capital’s role in financial performance in post-pandemic Indonesia. Limitations: The study is limited by its sample size and sector focus, and the VAIC™ method may not fully capture the true value of human capital. Contributions: This research adds to the understanding of intellectual capital’s influence on financial performance in the Indonesian food and beverage industry.
The Effect of Earnings Per Share (EPS), Debt to Equity Ratio (DER), and Return on Equity (ROE) on Stock Prices Diaz Bayu Samudra; Zaharuddin Zaharuddin; Supriyadi Supriyadi
Applied AI and Machine Learning Journal Vol 1 No 2 (2026): June
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/aiml.v1i2.4174

Abstract

Purpose: This study examines the effect of Earnings Per Share (EPS), Debt to Equity Ratio (DER), and Return on Equity (ROE) on the stock prices of state-owned enterprises listed on the Indonesia Stock Exchange from 2020 to 2024. Research Methodology: Using purposive sampling, 16 firms were selected from a pool of 20, and data were collected over five years. This research employed descriptive and verification methods, analyzing secondary data through regression, correlation, F-test, t-test, and determination analyses to test the hypotheses. Results: The findings reveal that EPS, DER, and ROE simultaneously influence stock prices, with EPS having a positive significant effect and DER and ROE showing significant negative effects. Conclusions: This study concludes that EPS is a crucial factor in determining stock prices, while high DER and ROE may negatively impact investor perception. Limitations: This study is limited by its focus on state-owned enterprises, which may not represent the broader market, and by its reliance on secondary data, which could introduce reporting biases. Contributions: The findings provide valuable insights for investors and policymakers on the key financial indicators affecting stock prices, emphasizing the importance of monitoring EPS, DER, and ROE in evaluating the financial health of state-owned companies.
The Effect of Pressure, Opportunity, and Rationalization on Financial Reporting Fraud: Evidence from Manufacturing Companies Listed on the Indonesia Stock Exchange (2020–2024) Egta Ayu Fadhillah Sugiarto; Zaharuddin Zaharuddin; Supriyadi Supriyadi
Global Academy of Multidisciplinary Studies Vol. 3 No. 1 (2026): August
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/gams.v3i1.4183

Abstract

Purpose: This study investigates the influence of pressure, opportunity, and rationalization, the three elements of the fraud triangle, on financial reporting fraud among manufacturing companies listed on the Indonesia Stock Exchange (IDX) during 2020–2024. Research Methodology: A quantitative descriptive-verification design was used with secondary data from published annual financial reports. Pressure was proxied by leverage ratio, opportunity by changes in accounts receivable, and rationalization by auditor turnover (DCHANGE). Fraudulent financial reporting was measured using the Beneish M-Score. A sample of 67 companies (335 firm-year observations) was selected using proportional stratified sampling. Multiple linear regression analysis was applied. Results: The results showed that opportunity significantly affected financial reporting fraud (? = 0.891, p < 0.001), while pressure and rationalization were insignificant. Together, the three factors explained some variation in fraud risk (F = 7.812, p < 0.001, R² = 0.066). Conclusions: Opportunities, particularly changes in accounts receivable, were found to significantly influence financial reporting fraud. Pressure and rationalization, though insignificant individually, explained some variation in fraud risk. Internal controls on receivables management are critical. Further research is needed to explore additional variables and alternative fraud-measurement models. Limitations: This study focuses only on the manufacturing sector with a five-year observation period, and the DCHANGE proxy for rationalization may underestimate its true effect. Contributions: The findings offer empirical evidence on the roles of fraud triangle elements in Indonesian manufacturing, providing insights for regulators, auditors, and corporate governance practitioners in fraud prevention.