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K Kadeni
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science

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Building Smart Learners: AI-Deep Learning, Digital Literacy, and Self-Regulation as Predictors of IPAS Outcomes Subiantoro, Anang; K Kadeni; Anasrulloh, Muhammad; Trisnantari, Hikmah Eva
SAGA: Journal of Technology and Information System Vol. 3 No. 3 (2025): August 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v3i3.569

Abstract

The rapid advancement of digital technology has made it imperative to adopt innovative instructional approaches in elementary-level IPAS (Natural and Social Science) education in Indonesia. Baseline data from Cluster 2, Pule District revealed that only 40.19% of Grade VI students met the minimum mastery criterion (KKM) in 2024/2025. This study examines the effects of AI-based IPAS learning through deep learning (X1), digital literacy (X2), and learning independence (X3) on student learning outcomes (Y) using a quantitative correlational non-experimental design. A proportional random sample of 129 students was drawn from 190 Grade VI students across 12 elementary schools. Data were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4.0. The measurement model confirmed satisfactory convergent validity (all AVE > 0.50), discriminant validity (Fornell–Larcker criterion), and composite reliability (all CR > 0.90). The structural model yielded R² = 0.784, indicating that the three variables jointly explain 78.4% of the variance in learning outcomes (GoF = 0.752, very high). All four hypotheses were accepted: AI-Deep Learning (β = 0.324, t = 4.872, p < 0.05), Digital Literacy (β = 0.287, t = 4.215, p < 0.05), Learning Independence (β = 0.412, t = 6.134, p < 0.05), and their simultaneous effect (F = 124.567, p < 0.05). Learning independence emerged as the dominant predictor (f² = 0.892). These findings advocate for an integrated digital-autonomous learning ecosystem as a systemic response to persistent IPAS underachievement in Indonesian elementary schools.
The Effect of Computer-Based Test (CBT) Utilization, Digital Literacy, and Internet Access on Grade V Students’ Science and Social Studies (SASS) Learning Outcomes Huda, Syamsul; K Kadeni; Dirgantoro, Ajar; Sukwatus Suja'i, Imam
SAGA: Journal of Technology and Information System Vol. 3 No. 4 (2025): November 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v3i4.567

Abstract

This study aims to analyze the effects of Computer-Based Test (CBT) utilization, digital literacy, and internet access on Grade V students’ Science and Social Studies (SASS) learning outcomes in public elementary schools in Ngunut District during the 2025/2026 academic year, both partially and simultaneously. The study employed a quantitative approach with an explanatory ex-post facto design. The population consisted of 587 students, and 233 respondents were selected using proportional random sampling with a 5% margin of error (Slovin formula). Data were collected through a 39-item Likert-scale questionnaire and documentation of students’ SASS achievement scores. Multiple linear regression analysis was conducted after fulfilling classical assumption tests, including normality, multicollinearity, heteroscedasticity, and linearity. The findings indicate that CBT utilization (β = 0.173; p = 0.018) and digital literacy (β = 0.432; p < 0.001) have positive and significant effects on learning outcomes, with digital literacy identified as the most dominant predictor. Internet access (β = 0.114; p = 0.176) does not have a significant partial effect. However, simultaneously, the three independent variables significantly influence learning outcomes (F = 58.871; p < 0.001). The coefficient of determination (R² = 0.435) shows that 43.5% of the variance in learning outcomes is explained by the model. These findings highlight that digital literacy competence is a key determinant in optimizing technology-based learning in primary education.
The Influence of AI Coding and Technology Tools on Human Resource Readiness Through Digital Literacy Setyorini, Wulan; K Kadeni; Anasrulloh, Muhammad; Purwananti, Yepi Sedya
SAGA: Journal of Technology and Information System Vol. 3 No. 3 (2025): August 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v3i3.572

Abstract

The era of Society 5.0 demands the integration of technology and character building in education to prepare superior human resources (HR). However, preliminary observations at public elementary schools in Rejotangan District reveal a gap between policy and reality, characterized by low digital literacy and limited availability of AI-based learning tools. This study aims to analyze the influence of AI Coding-based learning implementation and the availability of technological devices on the readiness of intelligent and competitive HR, mediated by students' digital literacy in science and social studies (SASS). This research employs a quantitative approach with an associative design. The population comprises 319 Grade 5 students, with a sample of 178 students determined using the Slovin formula and proportional stratified random sampling. Data analysis utilizes Structural Equation Modeling (SEM-PLS). The findings indicate that both AI coding learning and device availability significantly influence HR readiness through digital literacy as a mediator. This research provides a model for integrating AI coding in elementary education.
Co-Authors DIRGANTORO, AJAR Muhammad Anasrulloh Purwananti, Yepi Sedya Setyorini, Wulan Subiantoro, Anang Sukwatus Suja'i, Imam Syamsul Huda Trisnantari, Hikmah Eva