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AGUS PURWANTO
Contact Email
aguspurwanto.prof@gmail.com
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+62811700111
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journal.jiemar@gmail.com
Editorial Address
IEMAR ( Journal of Industrial Engineering & Management Research) ISSN : 2722-8878 Address: Griya Catania Blok F.08/80 Citra Raya . Kab. Tangerang Publisher: JIEMAR
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Kota tangerang,
Banten
INDONESIA
Journal of Industrial Engineering & Management Research (JIEMAR)
Published by Universitas Pelita Harapan
ISSN : -     EISSN : 27228878     DOI : https://doi.org/10.7777/jiemar
Core Subject : Economy, Humanities, Education, Engineering,
Humanities Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering
The aim of JIEMAR ( Journal of Industrial Engineering & Management Research is to publish theoretical and empirical articles that are aimed to contrast and extend existing theories, and build new theories that contribute to advance our understanding of phenomena related with industrial engineering and industrial management in organizations, from the perspectives of Production Planning/Scheduling/Inventory, Logistics/Supply Chain, Quality Management, Operations Management and Operational Research. The contributions can adopt confirmatory (quantitative) or explanatory (mainly qualitative) methodological approaches. Theoretical essays that enhance the building or extension of theoretical approaches are also welcome. JIEMAR selects the articles to be published with a double bind, peer review system, following the practices of good scholarly journals. JIEMAR is published monthly (on-line versions), following an open access policy. On-line publication allows to reduce publishing costs, and to make more agile the process of reviewing and edition. JIEMAR defends that open access publishing fosters the advance of scientific knowledge, making it available to everyone. List Scope Jpurnal JIEMAR: • Supply chain • Lean manufacturing • Operations improvement • Innovation management in operations • Operations in service industry • Operational Research • Total Quality Management • Total Productive Maintenance • How to manage workforce in operations • Logistic in general • Operational Management • Finance Management • Strategic Management • Marketing Management • Learning & Human Development Management
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Perilaku Organisasi dan Menejemen Sumber Daya Manusia
Articles 5 Documents
 1 
Search results for , issue "Vol. 6 No. 2 (2025): April 2025" : 5 Documents clear
Reclaiming Food Governance: Social Movements and Sustainable Food Systems Rulinawaty, Rulinawaty; Samboteng, Lukman; Andriyansah, Andriyansah; Alwi, Alwi
Journal of Industrial Engineering & Management Research Vol. 6 No. 2 (2025): April 2025
Publisher : AGUSPATI Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7777/jiemar.v6i3.573

Abstract

This study examines how civil society organizations and social movements engage with governance processes to achieve equitable, sustainable, and democratic transformations in food systems. Using a comparative qualitative approach, the research investigates case studies from Canada, New Zealand, France, and the United States to analyze varying governance models, including multi-stakeholder governance, collaborative governance (co-governance), and polycentric or self-governance. Results demonstrate that civil society participation within multi-stakeholder frameworks can influence policy discourses but faces significant constraints from state and private sector actors. Collaborative governance arrangements show greater potential, allowing civil society to meaningfully co-produce food governance outcomes; however, such partnerships often require movements to make pragmatic compromises. Polycentric governance and self-governance models enable civil society actors to exercise greater autonomy, particularly benefiting Indigenous and local communities, although institutional recognition remains a critical challenge. Overall, this study contributes a nuanced understanding of how social movements strategically mobilize power to reshape food governance systems, highlighting opportunities, constraints, and conditions that influence their ability to advance transformative agendas towards sustainability, social justice, and democracy in food systems governance.
Effective Strategies in Managing Educational Financing for Islamic Higher Education Institutions in the Contemporary Era Supriatna, Dasep
Journal of Industrial Engineering & Management Research Vol. 6 No. 2 (2025): April 2025
Publisher : AGUSPATI Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7777/jiemar.v6i2.574

Abstract

This study examines effective strategies for managing educational financing in Islamic higher education institutions, emphasizing adherence to Islamic finance principles[3] and addressing contemporary challenges. Utilizing a mixed-methods approach, the research explores waqf revitalization[1], sukuk implementation[2], revenue diversification, and stakeholder engagement[4] as mechanisms to enhance financial sustainability and ethical alignment. Findings reveal that institutions leveraging waqf and sukuk demonstrate improved financial resilience and reduced reliance on tuition fees. Stakeholder collaboration and capacity-building initiatives[8] emerge as critical elements for optimizing financial strategies, ensuring accessibility, and advancing institutional missions in alignment with Shariah principles.
Regulatory Compliance Strengthening Strategy through Mitigating the Risk of Violation of Fiduciary Duty : Jiwasraya Case Study in Indonesia Senjaya, Pierre; Tarsicius, Tarsicius; Tambunan, Martua E
Journal of Industrial Engineering & Management Research Vol. 6 No. 2 (2025): April 2025
Publisher : AGUSPATI Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7777/jiemar.v6i2.576

Abstract

The Jiwasraya case in Indonesia is one of the biggest financial scandals that reflects weaknesses in the implementation of regulatory compliance and internal control, especially related to fiduciary duty violations. This study aims to analyze effective risk mitigation strategies in strengthening regulatory compliance through a case study based on a literature review. By using a qualitative research method through a literature review approach, this study explores various relevant documents, reports, and previous studies. The results of the study indicate that the violation of fiduciary duty in Jiwasraya was caused by weaknesses in investment supervision, lack of transparency in financial reports, and neglect of good corporate governance principles. To address this, the proposed strategies include strengthening internal control mechanisms based on the COSO framework, implementing a whistleblowing system for early detection of violations, and integrating real-time investment monitoring technology. This study provides theoretical contributions by expanding the literature on mitigating the risk of fiduciary duty violations in the context of regulatory compliance. Practically, this study recommends strategic steps for insurance companies and regulators to prevent similar cases from recurring in the future
Proposed design of the application of chemical warehouse control systems with the water fall method Rosihin, Rosihin; Septian, Muhammad Hafizh
Journal of Industrial Engineering & Management Research Vol. 6 No. 2 (2025): April 2025
Publisher : AGUSPATI Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7777/jiemar.v6i3.577

Abstract

This study aims to make it easier for analysts to collect chemicals and maintain the accuracy of chemical inventory data because they no longer use manual recording. The research was conducted at the laboratory of PT. Mitsubishi Chemical Indonesia March 1 to May 30, 2024. Data were collected by interview and observation, and analyzed using the water fall method. Based on the research, it can be concluded that: 1) the system created can make it easier for the analyst when taking chemicals and the suitability of the inventory quantity data becomes accurate, 2) the application made can be easily understood by all analysts in the laboratory.
Analisis untuk memprediksi diabetes menggunakan data mining Hamed, Abdulhalim; Arif , Yunifa Miftachul; Faisal, M
Journal of Industrial Engineering & Management Research Vol. 6 No. 2 (2025): April 2025
Publisher : AGUSPATI Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7777/jiemar.v6i2.579

Abstract

Abstract - Data mining is crucial for extracting patterns and valuable insights from extensive datasets, utilizing artificial intelligence and advanced data analysis techniques across various domains. Diabetes, a metabolic disorder characterized by elevated blood glucose levels, poses significant health risks, including cardiovascular and renal complications if untreated. Data mining plays a pivotal role in exploring and predicting diabetes by identifying high-risk populations, thereby enabling early intervention strategies such as lifestyle modifications and timely treatment initiation. Analyzing comprehensive datasets encompassing diabetes-related factors such as weight, blood pressure, blood glucose levels, and genetic predispositions data mining constructs predictive models to assess risks and implement targeted interventions. In a comprehensive study involving 768 cases (268 positive and 500 negative) Logistic Regression achieved 70% accuracy, with a recall of 57% and an F1 score of 0.63 , Naive Bayes (GaussianNB) achieved 68% accuracy, with a recall rate of 54% and an F1 score of 0.61, Decision Tree Classifier achieved 66% accuracy, with a recall rate of 62% and an F1 score of 0.64 , Random Forest achieved 70% accuracy, with a recall rate of 59% and an F1 score of 0.64 , XGBClassifier achieved 66% accuracy, with a recall rate of 58% and an F1 score of 0.62. The analysis underscores a trade-off between precision and recall, particularly in classifying high-risk diabetes cases. High precision reduces false positives but may lower recall, potentially missing true positive cases. Conversely, emphasizing recall may increase false positives. Achieving a balance between these metrics is critical for effective diabetes prediction and tailored healthcare strategies This abstract encapsulates the pivotal role of data mining in diabetes research, emphasizing its impact on predictive modeling and healthcare decision making.

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