Hasil untuk "Management of special enterprises"

Eogenie Lakilaki

This study explores the embodiment of sharia accounting values in traditional wedding practices in Lahat Regency, South Sumatra, through an Islamic epistemological lens. Using a qualitative interpretive approach, it examines indigenous rituals as culturally embedded accounting practices that govern financial and social obligations. The findings indicate that these traditions reflect the core objectives of Maqasid al-Shariah: hifz al-diin (preservation of religion) through the sanctification of marriage, hifz al-nafs (life) via collective responsibility and social harmony, hifz al-‘aql (intellect) through ethical deliberation and knowledge transmission, hifz al-nasl (lineage) by regulating marital legitimacy, and hifz al-maal (wealth) through transparent and fair financial arrangements. These practices function as a decentralized, community based form of Islamic accounting governed by ‘urf (custom) in alignment with sharia principles. This study challenges institution centric perspectives in Islamic accounting and contributes to a culturally grounded framework for Islamic financial ethics rooted in lived community practices.

Ankush Agarwal, Harsh Vishwakarma, Suraj Nagaje et al.

Deploying AI agents in enterprise environments requires balancing capability with data sovereignty and cost constraints. While small language models offer privacy-preserving alternatives to frontier models, their specialization is hindered by fragmented development pipelines that separate tool integration, data generation, and training. We introduce EnterpriseLab, a full-stack platform that unifies these stages into a closed-loop framework. EnterpriseLab provides (1) a modular environment exposing enterprise applications via Model Context Protocol, enabling seamless integration of proprietary and open-source tools; (2) automated trajectory synthesis that programmatically generates training data from environment schemas; and (3) integrated training pipelines with continuous evaluation. We validate the platform through EnterpriseArena, an instantiation with 15 applications and 140+ tools across IT, HR, sales, and engineering domains. Our results demonstrate that 8B-parameter models trained within EnterpriseLab match GPT-4o's performance on complex enterprise workflows while reducing inference costs by 8-10x, and remain robust across diverse enterprise benchmarks, including EnterpriseBench (+10%) and CRMArena (+10%). EnterpriseLab provides enterprises a practical path to deploying capable, privacy-preserving agents without compromising operational capability.

Mutia Khoirun Nisa, Rohmi Salamah, Nastiti Wijayanti

Background: Murraya koenigii (Curry) leaves are herbal plants that have bioactive compounds such as phenolics, flavonoids, and alkaloids that function as antioxidants and anti-cancers. Aims: This study aimed to quantitatively determine the bioactive compounds in curry leaves by calculating phenolic, flavonoid, and alkaloid content. Its potential as an antioxidant and anti-proliferative compound in T47D breast cancer cell lines was also analyzed. Methods: Murraya koenigii leaves extract was obtained by maceration using 80% methanol (1:5 w/v), then the antioxidant and anti-proliferative test was carried out using the 1,1-Diphenyl-2-Pycrylhidracyl (DPPH) and MTT (-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide) assay, respectively, followed by flow cytometry to determine the apoptotic activity of the extract on T47D breast cancer cell lines. Results: The results for the bioactive compounds in the methanol extract of Murraya koenigii leaves were 156.62±1.49 mg/g phenolics, 99.19±0.25 mg/g flavonoids, and 2.90±0.01 mg/g alkaloids. The IC50 value for antioxidant activity was 25.058±2.2 μg/ml and showed an anti-proliferative effect on T47D cells in a dose-dependent manner with IC50 74.71±5.45 μg/ml for cytotoxicity. Furthermore, flow cytometry showed that a concentration of 1/16 IC50 has the best results for apoptosis.  Conclusion: The methanolic extract of Murraya koenigii leaves has the potential as an antioxidant and anti-proliferative agent and can induce apoptosis of T47D cells.

Shamnad Mohamed Shaffi

Enterprises today face increasing cybersecurity threats that necessitate robust digital forensics and risk mitigation strategies. This paper explores these challenges through an imaginary case study of an organization, a global identity management and data analytics company handling vast customer data. Given the critical nature of its data assets, EP has established a dedicated digital forensics team to detect threats, manage vulnerabilities, and respond to security incidents. This study outlines an approach to cybersecurity, including proactive threat anticipation, forensic investigations, and compliance with regulations like GDPR and CCPA. Key threats such as social engineering, insider risks, phishing, and ransomware are examined, along with mitigation strategies leveraging AI and machine learning. By detailing security framework, this paper highlights best practices in digital forensics, incident response, and enterprise risk management. The findings emphasize the importance of continuous monitoring, policy enforcement, and adaptive security measures to protect sensitive data and ensure business continuity in an evolving threat landscape

Boyuan Lu, Wei Wang, Nick Jordan et al.

Understanding coastal geomorphic change is essential for advancing the United Nations Sustainable Development Goals (SDGs) through a multi-scale coastal management framework. In particular, characterization of coastal geomorphic change across multiple spatial and temporal scales can provide essential insights and context-specific knowledge that can inform and empower local communities. In this study, we present a multi-scale assessment of coastal geomorphic change in southwestern Lake Michigan in the Laurentian Great Lakes. Three spatial scales: county, reach, and transect and two temporal scales: long-term and short-term were examined using nine sets of historical aerial imagery spanning 1937 to 2020. The site-averaged long-term (1937-2020) change rates for the bluff crest, bluff toe, and shoreline were -0.22, -0.17, and -0.16 m/year, respectively. In the short term (1995-2020), the corresponding rates were -0.22, -0.15, and -0.32 m/year, indicating an increasing shoreline erosion in recent years. The coastal geomorphic changes at county, reach, and transect scales were further characterized, showing regional and localized distributions of coastal erosion in our study sites. The mechanisms driving coastal change,particularly wave impacts, were also examined to assess their correlation with coastal geomorphic change across different spatial scales. The results indicate that wave impacts influence coastal environments at certain scales more strongly than at others. Several erosion "hotspots" were examined to identify local factors contributing to severe site-specific erosion. Lastly, the spatial uniformity of coastal geomorphology was examined between the county and reach scales. Overall, the findings suggest that multi-scale analyses provide a valuable insight for effective management of coastal geomorphology.

Suprokash Hazra

In this article, we introduce special domains and discuss the geometry of these domains, which includes showing that every pseudoconvex truncated tube domain is a special domain. Next, we prove a theorem for the envelope of special domains in $\C^n ~(n\geq 2)$. Our theorem on special domains is a generalization of a recent result by Jarnicki-Pflug on the envelope of holomorphy of truncated tube domains in $\C^n$. We also establish a result on schlichtness in complex dimension 2, and conclude this article with two higher-dimensional generalizations of the same result by Jarnicki-Pflug mentioned above.

A. Choudhary, J. Harding, M. Tiwari

In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas, including product and process design, assembly, materials planning, quality control, scheduling, maintenance, fault detection etc. Data mining has emerged as an important tool for knowledge acquisition from the manufacturing databases. This paper reviews the literature dealing with knowledge discovery and data mining applications in the broad domain of manufacturing with a special emphasis on the type of functions to be performed on the data. The major data mining functions to be performed include characterization and description, association, classification, prediction, clustering and evolution analysis. The papers reviewed have therefore been categorized in these five categories. It has been shown that there is a rapid growth in the application of data mining in the context of manufacturing processes and enterprises in the last 3 years. This review reveals the progressive applications and existing gaps identified in the context of data mining in manufacturing. A novel text mining approach has also been used on the abstracts and keywords of 150 papers to identify the research gaps and find the linkages between knowledge area, knowledge type and the applied data mining tools and techniques.

Анна Жураковська, Дар’я Лукашова, Роман Павлов

The article focuses on the study of current challenges and peculiarities of ensuring economic security of enterprises in times of crisis. Different approaches to understanding the concept of economic security and its components are analyzed. It is determined that the key element is financial security, which requires special attention in the context of martial law. The influence of external threats on the activities of enterprises is investigated and the basic principles of financial security management are systematized. Innovative approaches to the transformation of business processes, including digitalization, data management and supply chain optimization, are considered. The main components of the financial security mechanism are highlighted: information and organizational, functional and analytical, control and monitoring.

I. Riepina

Formulation of the problem. In the conditions of global competition, lean production acquires special importance. For enterprises all over the world, the only way to survive in the market is to produce goods and provide services that most fully satisfy the demands of consumers, while using advanced management methods and technologies. Lean manufacturing is one of the modern tools of production organization and management technology, which is used to improve the quality of products and services, the most complete satisfaction of consumer needs, while ensuring a careful attitude to the company's resources and their savings. The purpose of the study is the further development of methodological, methodical and practical approaches to the concept of Lean manufacturing to improve the quality of the enterprise's business processes. Research methods. The research used scientific methods, such as theoretical generalization, comparison, analysis, synthesis. Result. In the process of research, a comparison of traditional business management and the concept of lean production was made and revealed. that the concept of lean production has such advantages as the transition from centralized, vertical management to horizontal, involvement of all employees in the process, teamwork, focus on rational use of resources. The concept of lean production is aimed at eliminating the following main types of losses: overproduction of goods; waiting for raw materials, semi-finished products, necessary service information; unnecessary movement of materials; redundant processing steps arising due to errors in the design of business processes; excessive stocks and business processes leading to their occurrence; unjustified rotation of personnel in the work process; production of waste; underutilization of employees' creative potential. Conclusions. Six main elements and 52 components (requirements) of Lean manufacturing are defined based on the SAE J4000 standard for more successful application of lean manufacturing ideas in practice production to analyze the levels of implementation of lean manufacturing methodology components and elements. The main elements of the concept of lean manufacturing, the development and improvement of which should be focused on, are: company management and trust in it; enterprise personnel; information environment; chain "supplier – organization – consumer"; product; business processes. An important role in the concept of lean manufacturing is played by the 5S ordering system and the system of general maintenance of TPM equipment . Keywords: lean manufacturing; losses; flow of value creation; 5S ordering system; system of general maintenance of TPM equipment; SAE standard J4000.

Miryam Menila Zai, Chrisostomus Susmono Widagdo

The purpose of this research is to examine the complexities of financial management and their impact on the survival of micro, small, and medium-sized enterprises (UMKM) in Semarang district, with special emphasis on Wahana Parfum Shop in Karangjati. Although UMKM continues to flourish in Semarang district, many are facing obstacles in managing their finances effectively, as only a small fraction are active and skilled to manage their financial affairs. Conversations with business owners have found that the main challenge lies in their lack of understanding of the benefits of financial statements and incomplete financial controls. Besides, perfume entrepreneurs show a lack of confidence when comparing financial plans to real life circumstances. It underscores the need to overcome gaps in financial literacy and financial management to improve the performance and resilience of SMEs in the region. Recommendations include offering training and education to enhance understanding of financial management, maximize the use of business control, and cultivate a deeper understanding of the principles of finance management.

Seyed Mojtaba Mahmoudzadeh, Esmaeil Ghaderi, Danial Khalaj

The present research was conducted with the aim of knowing the motivational factors affecting the demand for literary tourism in Iran by using the theory of push and pull motivational factors, the ranking of the motivational factors affecting the demand for literary tourism, has been discussed.This research is practical in terms of purpose and descriptive-survey in terms of method. The structural equation modeling method was used to analyze the data. The main tool for data collection was a questionnaire. The questionnaire was distributed among the domestic and foreign literary tourists, using non-probability random sampling.The results of the surveys showed that the driving factors, the highest average is related to psychological factors. Among the tensile factors, the highest average is associated to intangible factors. In general, psychological factors have the highest average and search factors, intangible factors, tangible factors, physical factors and social interactions have the next ranks respectively.

W. Li, J. Cai, C. Wang et al.

This paper focuses on studying the evaluation index system for the production efficiency of tobacco enterprises. Considering the limitations of existing evaluation methods in accurately assessing the production quality of cigarette enterprises, a mathematical model based on the Analytic Hierarchy Process (AHP) is established. This model constructs an evaluation framework for the production efficiency of cigarette enterprises and subsequently analyzes the significance of each index within this framework. To comprehensively analyze the multi-index and feasibility aspects of the selected projects, the AHP method is employed to establish a comprehensive feasibility research and evaluation structure model. The result of this feasibility study provides the conclusion that the construction of an evaluation index system for the production efficiency of cigarette enterprises can indeed promote the enhancement of their production efficiency.

Matthew J. Schneider, Rufus Rankin, Prabir Burman et al.

The M6 Competition assessed the performance of competitors using a ranked probability score and an information ratio (IR). While these metrics do well at picking the winners in the competition, crucial questions remain for investors with longer-term incentives. To address these questions, we compare the competitors' performance to a number of conventional (long-only) and alternative indices using standard industry metrics. We apply factor models to measure the competitors' value-adds above industry-standard benchmarks and find that competitors with more extreme performance are less dependent on the benchmarks. We also uncover that most competitors could not generate significant out-performance compared to randomly selected long-only and long-short portfolios but did generate out-performance compared to short-only portfolios. We further introduce two new strategies by picking the competitors with the best (Superstars) and worst (Superlosers) recent performance and show that it is challenging to identify skill amongst investment managers. We also discuss the incentives of winning the competition compared to professional investors, where investors wish to maximize fees over an extended period of time.

Urtzi Otamendi, Mikel Maiza, Igor G. Olaizola et al.

Managing resources effectively in uncertain demand, variable availability, and complex governance policies is a significant challenge. This paper presents a paradigmatic framework for addressing these issues in water management scenarios by integrating advanced physical modelling, remote sensing techniques, and Artificial Intelligence algorithms. The proposed approach accurately predicts water availability, estimates demand, and optimizes resource allocation on both short- and long-term basis, combining a comprehensive hydrological model, agronomic crop models for precise demand estimation, and Mixed-Integer Linear Programming for efficient resource distribution. In the study case of the Segura Hydrographic Basin, the approach successfully allocated approximately 642 million cubic meters ($hm^3$) of water over six months, minimizing the deficit to 9.7% of the total estimated demand. The methodology demonstrated significant environmental benefits, reducing CO2 emissions while optimizing resource distribution. This robust solution supports informed decision-making processes, ensuring sustainable water management across diverse contexts. The generalizability of this approach allows its adaptation to other basins, contributing to improved governance and policy implementation on a broader scale. Ultimately, the methodology has been validated and integrated into the operational water management practices in the Segura Hydrographic Basin in Spain.

Milan Zdravković, H. Panetto, G. Weichhart

ABSTRACT This paper considers Enterprise Information Systems functional architecture and carries out review of AI applications integrated in Customer Relationship Management, Supply Chain Management, Inventory and logistics, Production Planning and Scheduling, Finance and accounting, Product Lifecycle Management and Human Resources, with special attention to the manufacturing enterprises. Enhanced capabilities are identified and proposed as AI services. AI-enablement implements improved decision-making or automation by using Machine Learning models or logic-based systems. It is a process of the enterprise transformation leading to the convergence of the four major disruptive technologies, namely Industrial Internet of Things, Agent-based Distributed Systems, Cloud Computing and Artificial Intelligence.

Indry Kumala Dewi, Maria Yovita R.Pandin, Ahmad Daeng GS

From the research entitled "The Influence of Financial Management in Improving the Performance of Micro, Small and Medium Enterprises (UMKM) in Surabaya" this study aims to analyze good financial management in improving the performance of UMKM. This research was conducted in Surabaya, East Java. The object of this research, namely the influence of financial planning, financial records, and the separation of personal financial statements and business finances on the performance of UMKM. This study uses a sample of UMKM in Surabaya. In this study, the sampling technique used a non-probability sample, because the researcher did not get the details of the respondent's identity needed in making the sampling frame. Non-probability method using purposive sampling technique. Purposive sampling is a sampling technique based on special criteria, namely business actors in Surabaya. The analysis used is multiple linear regression. The results of this study are that the value of the financial planning variable has a value of 0.21, and financial records have a value of 0.19, and the separation of personal financial statements and business finances has a value of 0.15 which means that each of these variables has a significant effect on the performance of UMKM..

Erry Sunarya, Tuah Nur, Ike Rachmawati et al.

The importance of environmentally friendly issues related to manufacturing industry activities in Makassar City is currently a special concern. Green supply chain management integrates supply chain management with environmental management, so it is important to reduce environmental impacts. This study aims to determine the antecedents of green supply chain collaborative innovation on the performance of Small and Medium Enterprises in the Tourism Sector. Data was collected by distributing questionnaires. The unit of research analysis is Small and Medium Enterprises in the Tourism Sector in West Java. Respondents who were used as samples were 311 respondents. The analytical method used in testing the hypothesis is Partial Least Square (PLS). The results show: green supply chain management has a positive and significant effect on the performance of Small and Medium Enterprises in the Tourism Sector in West Java, green supply chain management mediates the effect of green innovation and transformational leadership on the performance of Small and Medium Enterprises in the Tourism Sector.

A. M. Fadeev, A. A. Spiridonov

This article discusses strategic approaches to ensuring technological sovereignty in the energy industry. Special attention is paid to the development of the Russian standardization system for oil and gas equipment and technologies based on the established Institute of Oil and Gas Technological Initiatives, which includes Russian and foreign oil and gas companies. Effective forms and methods of implementing import substitution programs, consolidating industry demand for oil and gas equipment and technologies, preparing standards and conducting conformity assessments of enterprises on them, as well as possible options for international cooperation based on the creation of a unified legal field in the field of standardization are proposed. The research carried out by the author made it possible to formulate strategic priorities for the implementation of domestic technological policy in the oil and gas complex, aimed at solving topical issues of import substitution and ensuring technological sovereignty. Ensuring technological sovereignty in the energy sector is a strategic task that requires consolidation of efforts at the state, industry and corporate levels of management.

Alicia Martin-Navarro, Maria Paula Lechuga Sancho, Jose Aurelio Medina-Garrido

Business Process Management Systems (BPMS) represent a technology that automates business processes, connecting users to their tasks. There are many business processes within the port activity that can be improved through the use of more efficient technologies and BPMS in particular, which can help to coordinate and automate critical processes such as cargo manifests, customs declaration the management of scales, or dangerous goods, traditionally supported by EDI technologies. These technologies could be integrated with BPMS, modernizing port logistics management. The aim of this work is to demonstrate, through a systematic analysis of the literature, the state of the art in BPMS research in the port industry. For this, a systematic review of the literature of the last ten years was carried out. The works generated by the search were subsequently analysed and filtered. After the investigation, it is discovered that the relationship between BPMS and the port sector is practically non-existent which represents an important gap to be covered and a future line of research.

Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammed Atiquzzaman

The widespread adoption of Internet of Things (IoT) devices in smart cities, intelligent healthcare systems, and various real-world applications have resulted in the generation of vast amounts of data, often analyzed using different Machine Learning (ML) models. Federated learning (FL) has been acknowledged as a privacy-preserving machine learning technology, where multiple parties cooperatively train ML models without exchanging raw data. However, the current FL architecture does not allow for an audit of the training process due to the various data-protection policies implemented by each FL participant. Furthermore, there is no global model verifiability available in the current architecture. This paper proposes a smart contract-based policy control for securing the Federated Learning (FL) management system. First, we develop and deploy a smart contract-based local training policy control on the FL participants' side. This policy control is used to verify the training process, ensuring that the evaluation process follows the same rules for all FL participants. We then enforce a smart contract-based aggregation policy to manage the global model aggregation process. Upon completion, the aggregated model and policy are stored on blockchain-based storage. Subsequently, we distribute the aggregated global model and the smart contract to all FL participants. Our proposed method uses smart policy control to manage access and verify the integrity of machine learning models. We conducted multiple experiments with various machine learning architectures and datasets to evaluate our proposed framework, such as MNIST and CIFAR-10.