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Electronic Journal of Education, Social Economics and Technology
Published by SAINTIS Publishing
ISSN : -     EISSN : 27236250     DOI : https://doi.org/10.33122/ejeset
Core Subject : Religion, Economy, Humanities, Health, Science, Education, Art, Social, Engineering,
Religion Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Veterinary Other
Electronic Journal of Education, Social Economics and Technology (eJESET) with ISSN 2723-6250 (online) is a open-access, peer-reviewed multidisciplinary international journal. The journal aims to provide an international platform for researchers, professionals and scientists for solve of problems with multidisciplinary approaches on all topics related to educational, social science, economics and technology to exchange, sharing and disseminate theoretical of current research results as widely as possible. Electronic Journal of Education, Social Economics and Technology (eJESET) publishes the latest research results in multidisciplinary approaches on all topics related to educational, social science, economics and technology. First published in 2020. The Journal is published biannually and is available in open access electronic version.
Arjuna Subject : Ilmu Sosial - Ilmu Sosial (Lain-Lain)
Articles 613 Documents
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The Influence of Education Level, Accounting Knowledge and Accounting Training on the Use of Accounting Information Moderated by Environmental Uncertainty of Small and Medium Enterprises in the Trenggalek Region Krissantina Eferyn; Meme Rukmini; Duwi Riningsih; Rahmat Yusam Awaludin; Ninik Asmarani
Electronic Journal of Education, Social Economics and Technology Vol 7, No 1 (2026)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v7i1.1116

Abstract

Examining the effects of education level, accounting knowledge, and accounting training on the use of accounting information is the goal of this study. Additionally, it seeks to determine whether environmental uncertainty moderates these associations.  The study uses the Partial Least Squares (PLS) method of Structural Equation Modeling (SEM).  With a coefficient of 0.328 and a t-statistic of 2.749, which are both above the crucial value of 1.96, the findings of the hypothesis test show that only Accounting Knowledge has a statistically significant effect on the usage of accounting information.  Accounting training and educational attainment, however, do not appear to have a major impact.  Additionally, there is no moderating effect of environmental uncertainty on the associations among education level, accounting knowledge, and accounting training with regard to the use of accounting information.  According to these findings, improving accounting expertise helps encourage the use of accounting data in decision-making more than just boosting educational requirements or providing training that lacks meaningful content.  In order to improve the efficient use of accounting data, the study emphasizes how crucial it is that public sector enterprises give technical accounting skill development top priority.
Workstation Capacity Optimization Using Theory Of Contraint and Drum-Buffer-Robe Methods mutia meilanda; Rr. Rochmoeljati
Electronic Journal of Education, Social Economics and Technology Vol 7, No 1 (2026)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v7i1.671

Abstract

A company in Pasuruan that produces speaker components is facing a bottleneck problem in cone paper production due to fluctuations in demand resulting in an imbalance in machine capacity and cycle time. This results in the cone paper production process being inefficient in meeting targets, making throughput suboptimal. To overcome these problems, you can apply Theory of Constraints (TOC) through the Drum-Buffer-Rope approach and Linear a Programming which is processed using WinQSB software. The research phase includes constraint identification, constraint exploitation, constraint subordination and constraint elevation. Based on the calculation, botlleneck occurs at the cone printing (SK -1) and coating (SK - 4) work stations. To overcome this, 2 hours of overtime was added at both work stations in August 2024 - January 2025. This step successfully increased throughput, the initial throughput of 80,669,0700 increased by 99,103,4200 or 19%. Thus, this proposal proved to be effective in optimizing throughput and maximizing production capacity utilization.
NFT Market Segmentation Classification of Buyer Behavior Based on Blockchain Type and Marketplace Platform Using Power BI Interactive Data Visualization Ananda Marcella Suratman; Alyani Intan Shaffira; Farrel Pasya Harramain; Akhmad Bakhrun
Electronic Journal of Education, Social Economics and Technology Vol 7, No 1 (2026)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v7i1.688

Abstract

The Non-Fungible Token (NFT) market has experienced rapid growth and high volatility, creating challenges for stakeholders aiming to understand transaction patterns and market behavior. This study addresses these challenges by employing an interactive Power BI dashboard to analyze and visualize NFT transaction data from 2021 to 2022. Grounded in descriptive and correlation analysis, the research is structured into three primary visual components: market summary, transactional insights, and correlation analysis. Using data visualization techniques and statistical correlation theory, the dashboard enables the identification of key performance indicators such as user activity, platform efficiency, and pricing dynamics. The findings reveal significant growth in NFT adoption, with 7,820 unique buyers, 7,872 sellers, and 4,327 creators contributing to the ecosystem. A strong positive correlation (r = 0.77) between current and sale prices indicates predictive potential in price behavior. Among blockchain platforms, Solana recorded the highest total sales US$13.0 million and royalty distributions 13,000, while LooksRare and Foundation stood out as the most profitable marketplaces for creators. The Collectibles category led in transaction volume, with collections like AbstractVerse attracting notable interest. While monthly transaction volumes varied, the overall market value remained relatively stable, peaking in December 2022. This study contributes to a deeper understanding of NFT market mechanics by combining data-driven analysis with interactive visual tools, offering valuable insights for creators, investors, and analysts navigating the digital asset landscape.

Page 62 of 62 | Total Record : 613

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