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MEASURING RELIGIOUS MODERATION AMONG STUDENTS Amirudin Amirudin; Suyono Suyono; Soeprijanto Soeprijanto; Lu’luil Maknun
Penamas Vol 35 No 2 (2022): Volume 35, Issue 2, July-December 2022
Publisher : Balai Penelitian dan Pengembangan Agama Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31330/penamas.v35i2.624

Abstract

This article aims to describe the results of research on the analysis of factors that influence religious moderation and the influence of religiosity on religious moderation for students of UIN Syarif Hidayatullah Jakarta. The research was conducted at UIN Syarif Hidayatullah Jakarta in the odd semester of the 2022/2023 academic year. The approach used is quantitative. Data collection techniques through surveys and data analysis using simple linear regression analysis. The results of this study are 1) the correlation coefficient between graduated with religious moderation is 0.286 or 28.6%, 2) the correlation coefficient value between religious organization background and religious moderation is 0.124 or 12.4%. 3) the value of the correlation coefficient between gender and religious moderation is 0.095 or 9.5%, 4) the average value of religiosity is 4.4665 with a standard deviation of 0.23404. based on these factors, it was found that the religiosity factor had an effect on religious moderation, as evidenced by the results of the study the R2 value of 0.025 or 2.5%, . The conclusions are: 1) there is no relationship between educational background and student religious moderation, 2) there is no relationship between gender (gender) and religious moderation, 3) there is no relationship between the background of students' religious organizations and religious moderation, 4) there is the relationship between religiosity and religious moderation 5) there is an influence of the dimension of religiosity on religious moderation.
Optimizing Moodle E-Learning Page Features to Enhance Student Achievement in Business Economics Raidil Fitran; Soeprijanto Soeprijanto; Muksin Muksin
Journal of Pedagogi Vol. 2 No. 1 (2025): Journal of Pedagogi - February
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/rdb52f40

Abstract

This study investigates how optimizing Moodle e-learning features can enhance student achievement in Business Economics courses. Grounded in constructivist learning theories and empirical research on Learning Management Systems, the investigation addresses the growing need for effective, technology-driven instructional strategies. A quasi-experimental research design was employed across one academic semester, involving undergraduate students enrolled in a Business Economics course at a public university. Participants were divided into two groups: one that accessed a standard Moodle environment and another that engaged with enhanced Moodle features, including adaptive release of content, personalized feedback tools, and gamified assessments. Data were collected through pre- and post-course tests, platform usage logs, and student perception surveys. Statistical analyses, including t-tests and multiple regression, indicated that students using the optimized Moodle platform demonstrated significantly higher achievement scores and engagement levels than those in the control group. Correlation results further revealed that interactive quizzes and targeted feedback strongly influenced student performance. Qualitative feedback underscored the benefits of gamified elements and user-friendly navigation in fostering deeper learning and motivation. These findings reinforce the vital role of thoughtfully tailored LMS interventions in improving learning outcomes, particularly within complex disciplines like Business Economics. The study concludes by discussing implications for educators, administrators, and platform developers seeking to maximize the pedagogical potential of e-learning systems. Future research should explore longitudinal effects, larger sample sizes, and cross-institutional validations to further refine and generalize these insights