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INDONESIA
Eduvest - Journal of Universal Studies
Published by Green Publisher Indonesia
ISSN : 27753735     EISSN : 27753727     DOI : 10.36418
Core Subject : Health, Science, Social, Engineering,
Aerospace Engineering Computer Science & IT Health Professions Neuroscience Social Sciences
Eduvest - Journal of Universal Studies is a double blind peer-reviewed academic journal and open access to multidiciplinary fields. The journal is published monthly by Green Publisher Indonesia. Eduvest - Journal of Universal Studies provides a means for sustained discussion of relevant issues that fall within the focus and scopes of the journal which can be examined empirically. This journal publishes research articles multidisciplinary sciences, which includes: Humanities and social sciences, contemporary political science, Educational sciences, religious sciences and philosophy, economics, Engineering sciences, Health sciences, medical sciences, design arts sciences and media. Published articles are from critical and comprehensive research, studies or scientific studies on important and current issues or reviews of scientific books.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 2,734 Documents
 270   271   272   273   274 
Financial Information System on Marketplace XYZ Based on PSAK 2025 Using the Laravel Framework Effendy, Kelvin; Hermanto, Agus
Eduvest - Journal of Universal Studies Vol. 6 No. 3 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i3.52845

Abstract

This research is based on the complexity of financial management in the XYZ marketplace, which still relies on manual processes, resulting in a high risk of errors, time inefficiencies, and inaccuracies in financial statements. This research aims to develop a financial information system based on PSAK 2025 with accounting automation to improve the efficiency and accuracy of financial data management. This research uses a qualitative prototyping method, comprising requirements gathering, module prototyping (COA, journals, AP, AR, financial reports), expert evaluation, refinement, and dummy data testing. Primary data comes from interviews with accounting experts, while secondary data comes from literature and documentation. The results showed that the system managed to achieve 100% recording accuracy, reduce reporting time by 99.9% (from 8 hours to under 5 seconds), and meet the PSAK 2025 standards in account classification, revenue recognition, and financial report presentation. The system also implements Role-Based Access Control (RBAC) for data security and automated transaction processing for typical marketplace transactions. This research contributes to the provision of a fully integrated, real-time, and audit-ready financial information system that can serve as a reference for similar digital platforms in Indonesia.
Comparison of F1-Score Naive Bayes, Logistic Regression, K-Nearest Neighbors, and SVM for Sentiment Classification X in Police Institutions Hartanto Wijaya, Robertos
Eduvest - Journal of Universal Studies Vol. 6 No. 3 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i3.53005

Abstract

Background: Social media, especially platform X, is the main channel for the public to express their opinions on public institutions, including the police. Analysis of public sentiment on this platform can provide insight into police performance. This study aims to compare the performance of machine learning algorithms in the classification of negative sentiment towards policing, focusing on unbalanced social media data. Objective: This study aims to compare the performance of machine learning algorithms—Naive Bayes, Logistic Regression, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM)—in classifying negative sentiments towards policing on social media X, as well as overcoming data imbalances using the SMOTE method. Method: The dataset consisted of 1,274 Indonesian-language data collected by crawling, then processed using preprocessing techniques such as text cleaning, stopword removal, and TF-IDF feature extraction. Testing is conducted with and without the implementation of SMOTE for data balancing. Evaluate the model's performance using F1-Score. Result: Without SMOTE, all algorithms fail to recognize neutral classes. After the implementation of SMOTE, Logistic Regression showed the best performance with an F1-Score of 80.85%, followed by SVM, Naive Bayes, and KNN. The implementation of SMOTE significantly improves the model's ability to classify negative sentiments. Conclusion: The combination of Logistic Regression and SMOTE is the best approach to classifying public sentiment towards policing, which can help police agencies understand public sentiment more accurately.
The Effectiveness of Clicker-Assisted Peer Instruction on Improving High School Students' Understanding of Electromagnetism Concepts Nurdiansyah, Doni; Rochman, Chaerul; Permanasari, Anna
Eduvest - Journal of Universal Studies Vol. 6 No. 3 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i3.53014

Abstract

Electromagnetism is a fundamental yet challenging topic in high school physics, as students often struggle to develop deep conceptual understanding through conventional lecture-based instruction. This study aims to examine the effectiveness of clicker-assisted Peer Instruction (PI) in improving students’ understanding of electromagnetism concepts. A quasi-experimental pretest–posttest control group design was employed involving two intact grade-11 classes (N = 58). The experimental group was taught using Peer Instruction supported by clickers, while the control group received conventional lecture-based instruction over a four-week period. Data were collected using a 25-item conceptual test with a reliability coefficient (KR-20) of 0.82. Data analysis included descriptive statistics, independent-samples t-test, ANCOVA with pretest scores as covariates, and effect size calculation using Hedges’ g. The results show that the experimental group achieved a significantly higher normalized gain (〈g〉 = 0.62) compared to the control group (〈g〉 = 0.35). Statistical analysis revealed a highly significant difference between groups (p < 0.001) with a very large effect size (Hedges g = 1.64). The findings indicate that clicker-assisted Peer Instruction not only enhances conceptual understanding but also reduces performance variability among students. In conclusion, the integration of clickers within the Peer Instruction framework is highly effective in improving students’ conceptual mastery of electromagnetism. This approach is recommended as an alternative instructional strategy to promote active learning and meaningful engagement in physics education.
Bank Customer Churn Prediction Using a Hybrid Ensemble Soft Voting Approach Based on Tabnet and XGBOOST Mohamad Syazimmi Hersyaputra; Shintami Chusnul Hidayati
Eduvest - Journal of Universal Studies Vol. 6 No. 4 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i4.52494

Abstract

In an increasingly competitive banking industry, the ability to predict potential customer churn is a strategic factor in maintaining business profitability and sustainability. Churn has a direct impact on a bank’s revenue and operational efficiency; therefore, a prediction model is needed that is not only accurate but also stable and adaptive to variations in customer data. This study proposes a hybrid ensemble soft voting approach based on TabNet and XGBoost to improve the performance and robustness of churn prediction. TabNet, with its sequential attention mechanism, can selectively identify important features, while XGBoost excels at handling nonlinear relationships and controlling overfitting through gradient boosting regularization. The two models are combined using a probability-based soft voting mechanism to produce more balanced and consistent predictions. To address class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied so that the data distribution is more proportional and churn patterns can be better represented. The experimental results show that the proposed approach achieves optimal performance, with an accuracy of 96.74%, precision of 90.09%, recall of 89.53%, and an F1-score of 89.81%. These values indicate that the model is able to maintain a balance between accurate churn detection and the minimization of misclassification. This hybrid ensemble soft voting approach has proven to be superior to single models in terms of predictive stability and generalization capability, making it an effective framework to support data-driven customer retention strategies in the banking sector.
Analysis of Enterprise Risk Management Maturity Level at PT. XYZ Pratama, Muhamad Rifnaldy; Priyarsono, Dominicus Savio; Jahroh, Siti
Eduvest - Journal of Universal Studies Vol. 6 No. 4 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i4.52563

Abstract

This research aims to evaluate the maturity level of the implementation of Enterprise Risk Management (ERM) at PT. XYZ through a maturity assessment process based on the Technical Guidelines for the Assessment of the Risk Maturity Index (RMI) issued by the Ministry of SOEs, namely Number SK-8/DKU.MBU/12/2023 and PER-2/MBU/03/2023. The research background is based on the increasing complexity of global risks and regulatory demands, which require companies to implement risk management effectively. This study uses a combination of primary and secondary data collected through questionnaires, in-depth interviews, and analysis of company documents. Data analysis was carried out descriptively using a scoring system, as well as SWOT and PESTEL analyses to formulate improvement strategies. The results of the study are expected to illustrate the actual conditions of ERM implementation at PT. XYZ, measure its maturity level based on the five dimensions of the RMI, and develop the necessary follow-up strategies to strengthen the effectiveness of risk management in a sustainable manner. These findings provide practical contributions for companies in improving risk governance, as well as academic contributions by enriching the literature on the application of maturity assessments in corporate risk management.
The Effect of Entrepreneurial Orientation on International Performance of SMES in Bandung City with Business Model Innovation as a Mediating Variable Muchlizardy, Yudhya
Eduvest - Journal of Universal Studies Vol. 6 No. 4 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i4.52635

Abstract

MSMEs have a strategic role in the national economy, especially in creating jobs and encouraging economic growth. However, many MSMEs in the City of Bandung face challenges in improving their international performance. This study aims to analyze the influence of Entrepreneurial Orientation (EO) on International Performance (IP) with Business Model Innovation (BMI) as a mediating variable in MSMEs. The research method used is a quantitative approach with the Partial Least Squares (PLS) analysis technique. Data were collected through a survey of MSME actors in the City of Bandung. The results of the study show that EO has a positive effect on BMI and IP. In addition, BMI is proven to be a significant mediating variable in the relationship between EO and IP. These findings indicate that innovation in business models is a key factor in increasing the competitiveness of MSMEs in the international market. Therefore, MSME actors are advised to strengthen their entrepreneurial orientation and continue to innovate in business models in order to compete globally.
Quality Management of Indonesian Language Learning in Improving Students' Reading Literacy in Elementary Schools Nurhayati, Enur; Wasliman, Eva Dianawati
Eduvest - Journal of Universal Studies Vol. 6 No. 4 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i4.52653

Abstract

Reading literacy is a fundamental skill for elementary school students, serving as the foundation for mastering various fields of knowledge. However, students’ literacy skills still face challenges such as limited reading materials, lack of varied teaching methods, and an underdeveloped literacy culture. In this context, the quality management of Indonesian language learning plays a key role in ensuring effective and systematic teaching aligned with the Merdeka Curriculum. This study aims to analyze how quality management of Indonesian language learning supports the improvement of reading literacy at SDN Kertajadi and SDN Kiarangupuk, Cidaun District, Cianjur Regency. Using a qualitative case study approach, data were collected through observation, in-depth interviews, and documentation, and analyzed with Miles & Huberman’s model, which includes data reduction, data display, and conclusion drawing. The findings reveal that lesson planning referred to the Merdeka Curriculum but was limited by inadequate reading resources and less varied strategies. Learning implementation involved interactive approaches such as group discussions and text-based learning, yet literacy culture beyond the classroom remained weak. Evaluation used formative and summative assessments, but follow-up actions were not fully integrated into continuous improvement programs. The study concludes that quality management has contributed positively to students’ reading literacy but requires strengthening through sufficient resources, teacher training, and sustainable literacy programs involving the whole school community.
Utilization of Academic Applications to Support the Education Administration System at the Academic Hospital of Gadjah Mada University Rusetiyanti, Nurwestu; Fitria Widyasar, Domas; Afandi, Yusuf; Mahitala, Anindita; Supoyo, Agung
Eduvest - Journal of Universal Studies Vol. 6 No. 4 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i4.52682

Abstract

Digitalization in academic hospital settings is essential to improve the efficiency and quality of educational administrative services. Teaching hospitals face challenges in developing innovative, user-friendly, and efficient systems that can support clinical education processes. In response to this need, the Academic Hospital of Gadjah Mada University (RSA UGM) developed a mobile-based application called “Akademik” to facilitate student registration and administrative processes. This research aims to evaluate the utilization of the “Akademik” application in supporting the educational administration system at RSA UGM. A descriptive quantitative method was used, with simple random sampling involving 47 respondents. Data were collected through questionnaires and analyzed using descriptive statistics with SPSS. The results show that 95.7% of respondents stated that the application instructions were clear and easy to understand, 95.7% perceived the application as easy to use, 89.4% expressed satisfaction with the application, and 87.2% reported that the student registration process became faster. These findings indicate that the “Akademik” application contributes positively to improving administrative efficiency and user experience. In conclusion, the “Akademik” application effectively enhances the educational administration process at RSA UGM by making it more efficient, user-friendly, and environmentally sustainable through reduced paper usage. However, continuous system development and integration are necessary to further optimize its performance and support the broader clinical education system.
Analysis of Waste Material Using Lean Construction and Fault Tree Analysis Approaches Kaca Sungkana, Sapna Rezain; Ratnaningsih, Anik; Krisnamurti, Krisnamurti
Eduvest - Journal of Universal Studies Vol. 6 No. 4 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i4.52747

Abstract

This research analyzes waste material in construction projects using Lean Construction and Fault Tree Analysis approaches. The study was conducted on three building projects: Building X in Makassar, Building Y in Batam, and Building Z in Kediri. The objectives are to estimate waste cost from material waste during structural and architectural work, identify the highest waste material indicators, and determine optimization strategies to improve waste cost efficiency. The Waste Assessment Model method was used to identify waste variables, while Fault Tree Analysis was employed to determine root causes and calculate the probability of waste occurrence. Data collection was conducted through direct field observations, interviews with contractors, and questionnaires. Results showed that waste costs in Building X project amounted to Rp. 1,371,690,630 (4.93% of contract value), Building Y project Rp. 1,434,910,750 (3.75% of contract value), and Building Z project Rp. 1,573,029,639 (3.36% of contract value). Waste Assessment Model analysis revealed three critical waste types across all projects: Defects (19.95-20.09%), Overproduction (18.19-18.32%), and Inventory (16.16-16.27%). Fault Tree Analysis identified that the highest probability variable causing waste material was A1 "Human or Group Failure" (0.6066-0.6565), while the lowest was C2 "Storage Capacity and Method" (0.3040-0.3623). This research provides strategies for waste cost efficiency through identification of dominant causes and probability calculations of waste occurrence.
Network Governance Dynamics in Zero-Burning Land Management Policy: Lessons from South Sumatra Alnema, Ujang; Alfitri, Alfitri; Putra, Raniasa; Nadjib, Abdul
Eduvest - Journal of Universal Studies Vol. 6 No. 4 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i4.52963

Abstract

Forest and land fires remain a persistent environmental challenge in South Sumatra, Indonesia, despite the implementation of the Zero-Burning Land Management Policy. This study examines the dynamics of network governance in the implementation of the policy by integrating Social Network Analysis (SNA) and in-depth interviews within a mixed-method framework. The research aims to analyze the structure of governance networks, coordination mechanisms, conflict and power dynamics, and adaptive responses among key actors, including provincial and district governments, plantation companies, NGOs, and local communities. The findings reveal a moderately centralized governance structure, with the provincial government acting as the dominant coordinating entity. While the network exhibits characteristics of a lead organization model, horizontal collaboration—especially in operational coordination—is also evident. Formal mechanisms such as inter-agency meetings and integrated task forces are complemented by informal coordination based on trust and personal relationships. However, the network is influenced by unequal capacities, resource imbalances, and overlapping authorities, which affect the stability and effectiveness of collaboration. The research also identifies adaptive responses, including the formation of integrated task forces, technology-based fire monitoring systems, and adjustments to local regulations. While these responses demonstrate institutional flexibility, adaptation remains largely reactive to crises rather than being integrated into systematic learning processes. Theoretically, the findings contribute to adaptive network governance by highlighting the interdependence of network structure, coordination quality, and adaptive capacity in environmental policy. For developing countries facing ecological pressures, strengthening trust, data integration, and institutional continuity is key to improving policy resilience and long-term fire prevention effectiveness.

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