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p-Index From 2021 - 2026
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All Journal Accounting and Management Journal Journal of Educational Studies
Triwahyuni Triwahyuni
Pusat Biomedis dan Teknologi Dasar Kesehatan Jl. Percetakan Negara No. 23 Jakarta 10560 Indonesia
Humanities Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Social Sciences Other

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Pencegahan Fraud pada Mantri PT Bank Rakyat Indonesia (Persero) Tbk Kantor Cabang Gombong: Peran Pengendalian Internal, Kesesuaian Kompensasi, dan Budaya Etis Organisasi Triwahyuni, Triwahyuni; Prasetyo, Anton
JURNAL AKUNTANSI DAN MANAJEMEN Vol 5 No 2 (2021): Accounting and Management Journal
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/amj.v5i2.2272

Abstract

Tujuan penelitian ini yaitu menganalisis apakah variable-variabel independen dalam penelitian ini memiliki pengaruh pada pencegahan fraud. Sampel dari penelitian ini adalah Mantri Bank BRI Cabang Gombong dengan masa kerja minimal satu tahun sebanyak 96 responden dengan menggunakan kuesioner. Penentuan sampel yaitudengan teknik nonprobability sampling dan sampel jenuh. Analisis data dengaan menggunakan SPSS 22 for windows yangameliputi ujiainstrumen validitasadan reliabilitas,auji asumsi klasikadan uji regresiaberganda. Dalam penelitian ini diperoleh hasil pengendalian internal,akesesuaian kompensasiadan budaya etisaorganisasi berpengaruhapositif dan signifikanapada pencegahan fraud secara parsial maupun simultan.
Implementation Of Deep Learning As An Adaptive Learning Approach For Students With Diverse Learning Styles At SD-IT Ass-Shiddiqin Suharyani, Suharyani; Festy Maharani, Jessica; Triwahyuni, Triwahyuni; Dwi Wardani, Sugita
Journal of Educational Studies Vol. 4 No. 1 (2026): April
Publisher : Lembaga Bale Literasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58218/jes.v4i1.2715

Abstract

This study examines the effectiveness of deep learning as an adaptive learning method for elementary students with diverse learning styles at SD-IT Ass-Shiddiqin. It is based on the challenge that students exhibit varied learning preferences—visual, auditory, reading/writing, kinesthetic, and multimodal—requiring more personalized instructional approaches. Deep learning, as part of artificial intelligence, enables real-time analysis of student interaction data to identify learning patterns that are difficult to detect manually. This capability allows the system to deliver learning materials tailored to individual student needs. The research employed a quasi-experimental design using a non-equivalent control group approach. Two classes were involved: an experimental group that used deep learning-based adaptive learning and a control group that applied conventional methods. Instruments included a VARK questionnaire to identify learning styles, pre-tests and post-tests to measure learning outcomes, as well as observation and documentation. Data analysis involved tests of normality, homogeneity, t-test, and ANOVA.The findings revealed a significant improvement in the experimental group’s academic performance. Post-test scores increased markedly compared to pre-test results and were higher than those of the control group. The t-test indicated a significant difference (p < 0.05), while the effect size (Cohen’s d = 1.32) showed a very strong impact. ANOVA results also confirmed that learning styles significantly influenced adaptive learning outcomes (p < 0.05). Overall, deep learning-based adaptive learning proved effective in enhancing motivation, engagement
Co-Authors Anton Prasetyo Dwi Wardani, Sugita Festy Maharani, Jessica Suharyani Suharyani