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International Journal of Enterprise Modelling
Published by International Enterprise Integration Association
ISSN : 16939220     EISSN : 29878713     DOI : https://doi.org/10.35335/emod
Core Subject : Economy, Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Transportation
The International Journal of Enterprise Modelling serves as a venue for anyone interested in business and management modelling. It investigates the conceptual forerunners and theoretical underpinnings that lead to research modelling procedures that inform research and practice.
Arjuna Subject : Matematika - Matematika Terapan
Articles 5 Documents
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Search results for , issue "Vol. 18 No. 3 (2024): September: Enterprise Modelling" : 5 Documents clear
Enhancing Employee Performance Evaluation: A Decision Support System Utilizing Analytical Hierarchy Process for Fair Bonus Allocation Wibisono, Mohamad Bayu; Wahyono, Bambang Tri; Solihin, Indra Permana; Wirawan, Rio
International Journal of Enterprise Modelling Vol. 18 No. 3 (2024): September: Enterprise Modelling
Publisher : International Enterprise Integration Association

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Abstract

This research endeavors to revolutionize the process of employee performance evaluation and bonus allocation within organizational settings by introducing a sophisticated Decision Support System (DSS) underpinned by the Analytical Hierarchy Process (AHP). The study delves into the development, implementation, and testing phases of the DSS, aiming to enhance objectivity, fairness, and efficiency in decision-making methodologies. The research commences with an exploration of existing challenges in performance evaluation systems, acknowledging the subjectivity and limitations prevalent in traditional methods. The conceptual framework outlines the hierarchical structure of the DSS, encompassing diverse performance criteria and sub-criteria essential for a comprehensive evaluation. Implementation involves the integration of the AHP method into the DSS, facilitating precise pairwise comparisons, priority vector calculations, and weighted score determinations. Rigorous testing and validation phases ascertain the system's accuracy, consistency, and responsiveness in evaluating employee performance and aligning bonus allocation with contributions. Results from the testing phase illuminate the DSS's efficacy, showcasing its ability to provide transparent and data-driven evaluations, fostering fairness, trust, and intrinsic motivation among employees. The implications of employing this DSS extend beyond bonus allocation, influencing organizational performance, decision-making, and the broader organizational climate.
Optimizing Crop Selection: A Multi-Criteria Decision Support System for Sustainable Agriculture Gunawan, Muhammad Indra; Sitopu, Joni Wilson; Sechan, Gamar; Gunawan, Indra
International Journal of Enterprise Modelling Vol. 18 No. 3 (2024): September: Enterprise Modelling
Publisher : International Enterprise Integration Association

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Abstract

This research endeavors to revolutionize agricultural decision-making through the development and application of a robust Decision Support System (DSS) employing the Multi-Criteria Decision Making (MCDM) method. Recognizing the complexities inherent in crop selection, the study aims to bridge the gap between traditional manual methodologies and the need for a more comprehensive, objective, and data-driven approach. The research foundation rests on the understanding that crop selection is a multifaceted process influenced by diverse and interrelated factors. Leveraging technology and structured methodologies, the developed DSS offers a systematic and holistic evaluation of potential crops by integrating various criteria such as climate suitability, market demand, soil fertility, and sustainability metrics. The system's ability to consider multiple criteria simultaneously surpasses conventional single-factor approaches, providing stakeholders with a nuanced and comprehensive perspective. While demonstrating strengths in comprehensive evaluation and objectivity, the research also identifies areas for improvement. The dependency on data quality and quantity emerges as a limitation, urging the need for enhanced data sourcing and refinement. Additionally, further development in handling intricate trade-offs and improving user accessibility could bolster the system's applicability and acceptance within agricultural practices. The practical implications of this research reverberate across the agricultural domain.
Optimizing Vermicelli Production: Flour Evaluation Using WASPAM Methodology for Informed Decision-Making in the Food Industry Immanuela, Noviany
International Journal of Enterprise Modelling Vol. 18 No. 3 (2024): September: Enterprise Modelling
Publisher : International Enterprise Integration Association

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Abstract

This research employs the Weighted Aggregated Sum Product Assessment Method (WASPAM) to evaluate and determine the most suitable flour for vermicelli production. The study aims to streamline the complex decision-making process inherent in flour selection by considering crucial criteria texture, gluten content, and protein levels to assess multiple flour options comprehensively. The assessment highlights texture as a pivotal criterion significantly influencing the suitability of flour for vermicelli production. Flour samples excelling in texture consistently ranked higher, emphasizing its paramount importance in achieving desired consistency and mouthfeel in vermicelli noodles. Additionally, while gluten content and protein levels played substantial roles, a balanced performance across criteria often resulted in competitive suitability scores, emphasizing the necessity of a holistic approach in flour selection. The findings offer valuable insights for stakeholders in the food industry, providing guidance for optimal flour selection strategies aligned with quality preferences and market demands. The research recommends a refined approach to weight allocation, particularly considering the pronounced influence of texture.
Forecasting Outpatient Visits: Leveraging Genetic Fuzzy Systems for Enhanced Healthcare Management at Efarina Etaham Berastagi Hospital Aveno, Dicky Chandra
International Journal of Enterprise Modelling Vol. 18 No. 3 (2024): September: Enterprise Modelling
Publisher : International Enterprise Integration Association

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Abstract

The efficient management of patient influx within healthcare facilities poses a critical challenge, necessitating precise forecasting and resource allocation. This study explores the predictive modeling of outpatient visits at Efarina Etaham Berastagi Hospital employing the innovative Genetic Fuzzy Systems (GFS) method. Harnessing the synergy between genetic algorithms and fuzzy logic, this research endeavors to develop a predictive model capable of accurately anticipating the fluctuating patterns of outpatient visits. The study amalgamates historical visit records, patient demographic data, and temporal factors within the GFS framework, aiming to optimize resource allocation, refine scheduling strategies, and elevate patient care delivery. The methodology involves the integration of genetic algorithms to iteratively evolve the predictive model and fuzzy logic to handle uncertainties inherent in healthcare datasets. The model's performance is evaluated through rigorous analysis, validation against actual visitation data, and comparison against established metrics to ascertain its accuracy and reliability. The outcomes of this research unveil a predictive model capable of forecasting outpatient visits with notable accuracy, showcasing the potential of the GFS method in enhancing healthcare management.
Impacts of Wetland Reclamation for Housing Development: Balancing Urban Growth, Environmental Sustainability, and Social Equity Sebastian, Robert Pedro
International Journal of Enterprise Modelling Vol. 18 No. 3 (2024): September: Enterprise Modelling
Publisher : International Enterprise Integration Association

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Abstract

This research investigates the impacts of wetland reclamation for housing development, focusing on the complex interplay between urban expansion, environmental sustainability, and social equity. As urban populations continue to grow, the demand for housing often leads to the conversion of vital wetland ecosystems into residential and commercial areas. The study employs a multi-method approach, including case studies, stakeholder interviews, and environmental assessments, to evaluate both the positive and negative consequences of this practice. Findings indicate that while wetland reclamation can alleviate housing shortages and stimulate local economies, it incurs significant environmental costs, such as biodiversity loss, increased flooding risks, and degraded water quality. Socially, the displacement of vulnerable communities and the exacerbation of social inequalities are notable consequences of this practice. Furthermore, the research highlights the inadequacies of existing legal and policy frameworks governing wetland reclamation, calling for stronger enforcement and integrated approaches to land-use planning. By recognizing wetlands as essential resources that contribute to ecological health and community resilience, this research underscores the importance of adopting holistic strategies that balance urban growth with environmental stewardship and social responsibility.

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