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Journal articles on the topic 'Business Process Monitoring'

Author: Grafiati

Published: 4 June 2021

Last updated: 21 February 2023

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1

Santoso, Ario, and Michael Felderer. "Specification-driven predictive business process monitoring." Software and Systems Modeling 19, no. 6 (2019): 1307–43. http://dx.doi.org/10.1007/s10270-019-00761-w.

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Abstract Predictive analysis in business process monitoring aims at forecasting the future information of a running business process. The prediction is typically made based on the model extracted from historical process execution logs (event logs). In practice, different business domains might require different kinds of predictions. Hence, it is important to have a means for properly specifying the desired prediction tasks, and a mechanism to deal with these various prediction tasks. Although there have been many studies in this area, they mostly focus on a specific prediction task. This work

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2

Kien Sia, Siew, and Boon Siong Neo. "Business process reengineering, empowerment and work monitoring." Business Process Management Journal 14, no. 5 (2008): 609–28. http://dx.doi.org/10.1108/14637150810903020.

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3

Spree, Florian. "Business Process Models in the Context of Predictive Process Monitoring." Revista de Informática Teórica e Aplicada 28, no. 1 (2021): 39–46. http://dx.doi.org/10.22456/2175-2745.106828.

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Predictive process monitoring is a subject of growing interest in academic research. As a result, an increased number of papers on this topic have been published. Due to the high complexity in this research area a wide range of different experimental setups and methods have been applied which makes it very difficult to reliably compare research results. This paper's objective is to investigate how business process models and their characteristics are used during experimental setups and how they can contribute to academic research. First, a literature review is conducted to analyze and discuss

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4

Sucharittham, Nanthawadee, Choochart Haruechaiyasak, Hieu Chi Dam, and Thanaruk Theeramunkong. "Multidimensional Sentiment Cube Mining for Process Monitoring." Trends in Sciences 19, no. 9 (2022): 3682. http://dx.doi.org/10.48048/tis.2022.3682.

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Process monitoring is essential for quality improvement because it is necessary to find the answers to which business issues need to be understood. In the era of social media, many critiques concern the business domain, including life insurance, which is one of the significant business sectors in Thailand. To utilize this useful cloud corpus for the business improvement process, we propose a novel methodology for process monitoring using the concept of multidimensional sentiment cube (MDSC) mining to raise usefulness with the business process model notation (BPMN). As the ability of MDC raise

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5

Oksanych, I., I. Shevchenko, O. Kaliuzhnyi, P. Savushkin, and V. Mizin. "ARCHITECTURE OF BUSINESS PROCESS MONITORING AND DISPATCHING SYSTEM." Transactions of Kremenchuk Mykhailo Ostrohradskyi National University 3 (June 23, 2020): 106–13. http://dx.doi.org/10.30929/1995-0519.2020.3.106-113.

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6

Metzger, Andreas, Philipp Leitner, Dragan Ivanovic, et al. "Comparing and Combining Predictive Business Process Monitoring Techniques." IEEE Transactions on Systems, Man, and Cybernetics: Systems 45, no. 2 (2015): 276–90. http://dx.doi.org/10.1109/tsmc.2014.2347265.

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7

Kang, Dongwoo, Sunjae Lee, Kwangsoo Kim, and Jae Yeol Lee. "An OWL-based semantic business process monitoring framework." Expert Systems with Applications 36, no. 4 (2009): 7576–80. http://dx.doi.org/10.1016/j.eswa.2008.09.027.

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8

Knuplesch, David, Manfred Reichert, and Akhil Kumar. "A framework for visually monitoring business process compliance." Information Systems 64 (March 2017): 381–409. http://dx.doi.org/10.1016/j.is.2016.10.006.

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9

Przemyslaw, Dadel, Balawajder Mariusz, Radziszowski Dominik, and Zielinski Krzysztof. "Adaptive SOA Stack-Based Business Process Monitoring Platform." Computer Science 15, no. 2 (2014): 173. http://dx.doi.org/10.7494/csci.2014.15.2.173.

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10

Fardbastani, Mohammad Ali, Farshad Allahdadi, and Mohsen Sharifi. "Business process monitoring via decentralized complex event processing." Enterprise Information Systems 12, no. 10 (2018): 1257–84. http://dx.doi.org/10.1080/17517575.2018.1522453.

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11

Comuzzi, Marco, and Samuil Angelov. "Patterns and tools for business process monitoring customization." Service Oriented Computing and Applications 10, no. 3 (2015): 253–71. http://dx.doi.org/10.1007/s11761-015-0185-y.

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12

Maamar, Zakaria, Noura Faci, Mohamed Sellami, et al. "On business process monitoring using cross-flow coordination." Service Oriented Computing and Applications 11, no. 2 (2017): 203–15. http://dx.doi.org/10.1007/s11761-017-0206-0.

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13

Amali, Lanto Ningrayati, Muhammad Rifai Katili, Sitti Suhada, and Tri Alfandra Labuga. "Business process monitoring system in supporting information technology governance." Bulletin of Electrical Engineering and Informatics 10, no. 5 (2021): 2884–91. http://dx.doi.org/10.11591/eei.v10i5.3147.

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Information technology (IT) is essential in supporting an organization's business sustainability and growth, making it critically dependent on IT. Therefore, a focus on IT governance, consisting of leadership, organizational structure, and process ensuring that IT organization supports and expands the organizational strategies and goals is required. When the business supports the strategic significance of IT investment, the implementation of an IT strategy will lead to the adoption of an IT governance model. It will support and help the description of the benefit roles and responsibilities fro

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14

Turisová, Renáta, Michal Tkáč, and Miloš Pachta. "Monitoring of process performance by means of financial indicators." Problems and Perspectives in Management 16, no. 3 (2018): 477–87. http://dx.doi.org/10.21511/ppm.16(3).2018.38.

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The paper deals with problematic nature of measuring of process performance. It includes a designed procedure of process performance monitoring, evaluation of logistic processes quality, and also measuring of the impact of marketing activities on the profitability of process output, i.e. a product, by means of appropriate indicator.There are several performance indicators that companies use to monitor the performance of their processes and business strategies with respect to their objectives. To monitor these indicators, enterprises rely on dashboards that present one or more indicators along

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15

Owczarek, Tomasz, and Piotr Janke. "Predictive Business Process Monitoring with Tree-based Classification Algorithms." Logistics and Transport, no. 40 (2018): 73–82. http://dx.doi.org/10.26411/83-1734-2015-4-40-10-18.

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Predictive business process monitoring is a current research area which purpose is to predict the outcome of a whole process (or an element of a process i.e. a single event or task) based on available data. In the article we explore the possibility of use of the machine learning classification algorithms based on trees (CART, C5.0, random forest and extreme gradient boosting) in order to anticipate the result of a process. We test the application of these algorithms on real world event-log data and compare it with the known approaches. Our results show that.

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16

Kang, Bokyoung, Jae‐Yoon Jung, Nam Wook Cho, and Suk‐Ho Kang. "Real‐time business process monitoring using formal concept analysis." Industrial Management & Data Systems 111, no. 5 (2011): 652–74. http://dx.doi.org/10.1108/02635571111137241.

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17

Kang, Bokyoung, Dongsoo Kim, and Suk‐Ho Kang. "Periodic performance prediction for real‐time business process monitoring." Industrial Management & Data Systems 112, no. 1 (2012): 4–23. http://dx.doi.org/10.1108/02635571211193617.

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18

Jiang, Wei, Tom Au, and Kwok-Leung Tsui. "A statistical process control approach to business activity monitoring." IIE Transactions 39, no. 3 (2007): 235–49. http://dx.doi.org/10.1080/07408170600743912.

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19

AlMahmoud, Abdelrahman, Maurizio Colombo, Chan Yeob Yeun, and Hassan Al Muhairi. "Secure communication protocol for real-time business process monitoring." International Journal of Internet Technology and Secured Transactions 5, no. 3 (2014): 223. http://dx.doi.org/10.1504/ijitst.2014.065183.

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20

Comuzzi, Marco, Irene Vanderfeesten, and Tingting Wang. "Optimized cross-organizational business process monitoring: Design and enactment." Information Sciences 244 (September 2013): 107–18. http://dx.doi.org/10.1016/j.ins.2013.04.036.

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21

Hao, Yong Ping, Wei Ping Shao, and Li Lun He. "Research of Workflow Modeling System for Business Process Management." Applied Mechanics and Materials 16-19 (October 2009): 219–23. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.219.

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Establish an environment-independent process flow definition for Business Process Management that can realize the common flow chart conversion with the help of flow engine. It adopts a browser-based client-side development mode to realize friendly flow user interface, and has the role-based task allocation mode and the user’s allocation-based task allocation mode, which can implement the system with the datasheet-based flow monitoring and the graphics-based flow monitoring.

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22

AIELLO, MARCO, and ALEXANDER LAZOVIK. "MONITORING ASSERTION-BASED BUSINESS PROCESSES." International Journal of Cooperative Information Systems 15, no. 03 (2006): 359–89. http://dx.doi.org/10.1142/s0218843006001396.

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Business processes that span organizational borders describe the interaction between multiple parties working towards a common objective. They also express business rules that govern the behavior of the process and account for expressing changes reflecting new business objectives and new market situations. We developed a service request language and support framework that allow users to formulate their requests against standard business processes.19 In this paper, we extend the approach by presenting a framework capable of automatically associating business rules with relevant processes involv

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23

Soegoto, E. S., and R. Sani. "Development of Information Technology Structural Scheme For Monitoring Business Process." IOP Conference Series: Materials Science and Engineering 407 (September 26, 2018): 012001. http://dx.doi.org/10.1088/1757-899x/407/1/012001.

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24

Dominguez, Eladio, Beatriz Perez, Angel L. Rubio, Maria A. Zapata, Juan Lavilla, and Alberto Allue. "Occurrence-Oriented Design Strategy for Developing Business Process Monitoring Systems." IEEE Transactions on Knowledge and Data Engineering 26, no. 7 (2014): 1749–62. http://dx.doi.org/10.1109/tkde.2013.166.

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25

Macedo, Julio, R. Ruiz Usano, and J. Framifiñan Torres. "A Real Time Cost Monitoring System for Business Process Reengineering." IFAC Proceedings Volumes 30, no. 1 (1997): 411–16. http://dx.doi.org/10.1016/s1474-6670(17)44667-2.

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26

Koetter, Falko, and Monika Kochanowski. "A model-driven approach for event-based business process monitoring." Information Systems and e-Business Management 13, no. 1 (2014): 5–36. http://dx.doi.org/10.1007/s10257-014-0233-8.

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27

Meroni, Giovanni, Luciano Baresi, Marco Montali, and Pierluigi Plebani. "Multi-party business process compliance monitoring through IoT-enabled artifacts." Information Systems 73 (March 2018): 61–78. http://dx.doi.org/10.1016/j.is.2017.12.009.

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28

Di Francescomarino, Chiara, Marlon Dumas, Marco Federici, et al. "Genetic algorithms for hyperparameter optimization in predictive business process monitoring." Information Systems 74 (May 2018): 67–83. http://dx.doi.org/10.1016/j.is.2018.01.003.

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29

Comuzzi, Marco, Jochem Vonk, and Paul Grefen. "Measures and mechanisms for process monitoring in evolving business networks." Data & Knowledge Engineering 71, no. 1 (2012): 1–28. http://dx.doi.org/10.1016/j.datak.2011.07.004.

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30

Eldin Adam Hamza, Salah. "Monitoring and controlling design process using control charts and process sigma." Business Process Management Journal 15, no. 3 (2009): 358–70. http://dx.doi.org/10.1108/14637150910960611.

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31

Varol, Cihan, and Henry Neumann. "Real-Time Data Quality Monitoring System for Data Cleansing." International Journal of Business Intelligence Research 3, no. 1 (2012): 83–93. http://dx.doi.org/10.4018/jbir.2012010106.

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To assist business intelligence companies dealing with data preparation problems, different approaches have been developed to handle the dirty data. However, these data cleansing approaches do not have real-time monitoring capabilities. Therefore, business intelligence companies and their clients are not able to predict the final outcome before running all business process. This yields an extra cost for the company if the data are highly corrupted. Therefore, to reduce cost for these types of businesses, the authors design a framework that monitors the quality attributes during the data cleans

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32

Zelt, Sarah, Jan Recker, Theresa Schmiedel, and Jan vom Brocke. "A theory of contingent business process management." Business Process Management Journal 25, no. 6 (2019): 1291–316. http://dx.doi.org/10.1108/bpmj-05-2018-0129.

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Purpose Many researchers and practitioners suggest a contingent instead of a “one size fits all” approach in business process management (BPM). The purpose of this paper is to offer a contingency theory of BPM, which proposes contingency factors relevant to the successful management of business processes and that explains how and why these contingencies impact the relationships between process management and performance. Design/methodology/approach The authors develop the theory by drawing on organizational information processing theory (OIPT) and applying an information processing (IP) perspe

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33

Glykas, Michael, George Valiris, Angelika Kokkinaki, and Zoi Koutsoukou. "Banking Business Process Management Implementation." International Journal of Productivity Management and Assessment Technologies 6, no. 1 (2018): 50–69. http://dx.doi.org/10.4018/ijpmat.2018010104.

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Scholars and practitioners in the fields of Business Process Management (BPM), performance measurement and business information systems tend to use different approaches for implementing BPM Programs without arguing about the quality strategy set to ensure successful implementation and adoption. This lack of quality standards makes it difficult for researchers and practitioners to build on each other's work. The purpose of this article is to present a model for a BPM Program implementation in the banking sector. The authors' four steps implementation model is based on a quality strategy monitor

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34

SRDIC, GREGOR, and MATJAZ B. JURIC. "MODEL FOR INTEGRATED MONITORING OF BPEL BUSINESS PROCESSES." International Journal of Cooperative Information Systems 22, no. 02 (2013): 1350008. http://dx.doi.org/10.1142/s0218843013500081.

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Business process execution language (BPEL) does not provide a native support for defining data and metrics, required to perform business activity monitoring (BAM). Existing industry solutions are vendor-specific while platform-independent scientific approaches separate tightly coupled monitoring definitions from the core BPEL processes into external descriptors, thus increasing the complexity of the development, packaging and deployment processes. Furthermore, existing monitoring solutions reuse platform-specific audit trail events. This requires monitor model developers to be familiar with th

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35

Korobeynikova, Svetlana, and Ludmila Dukanich. "PROCESS MANAGEMENT IN RUSSIAN BUSINESS EDUCATION." CBU International Conference Proceedings 1 (June 30, 2013): 188–95. http://dx.doi.org/10.12955/cbup.v1.33.

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The current management system in Russian business education is predominantly based on the principle of functional management, which in turn does not comprehensively address the emerging objectives and terms of modern-day education providers in Russia. The countries’ business schools are of the particular concern of the issue, considering the factors of their recent establishment and revenue-based financing. Presented in this paper is the outcome of implementation of the process-orientated approach to business education based on the experience of one of the leading Russian business schools. The

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36

Baek, Su-Jin, and Young-Jae Song. "Process Evaluation Model based on Goal-Scenario for Business Activity Monitoring." Journal of information and communication convergence engineering 9, no. 4 (2011): 379–84. http://dx.doi.org/10.6109/jicce.2011.9.4.379.

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37

Kim, Min-Soo, and Young-Seok Ock. "Business Process Monitoring under Extended-GMA Environment with Complex Event Handling." Journal of the Korea Academia-Industrial cooperation Society 11, no. 6 (2010): 2256–62. http://dx.doi.org/10.5762/kais.2010.11.6.2256.

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38

Proboyekti, Umi, Charoline Septa, and Budi Susanto. "Implementasi Business Process Modeling dalam Workflow Aplikasi Monitoring Electronic Data Capturer." Jurnal Terapan Teknologi Informasi 6, no. 1 (2022): 75–82. http://dx.doi.org/10.21460/jutei.2022.61.208.

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Business Process Modeling (BPM) adalah representasi visual berbasis data untuk memodelkan alur kerja bisnis untuk mengoptimalkan proses bisnis. Notasi BPM membuat model mudah dipahami oleh semua pemangku kepentingan yang berperan dalam mengembangkan proses bisnis. Makalah ini akan menjelaskan penerapan BPM dalam alur kerja Electronic Data Capturer (EDC) Monitoring Application (EDCMA). Proses pemodelan alur kerja menggunakan perangkat lunak Bonitasoft yang mencakup pembuatan proses bisnis untuk antarmuka pengguna dan mesin proses. EDCMA merupakan proses untuk menyelesaikan permasalahan pada pro

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39

Jalayer, Abdulrahman, Mohsen Kahani, Asef Pourmasoumi, and Amin Beheshti. "HAM-Net: Predictive Business Process Monitoring with a hierarchical attention mechanism." Knowledge-Based Systems 236 (January 2022): 107722. http://dx.doi.org/10.1016/j.knosys.2021.107722.

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40

Bauman, Yu I., and S. T. Tsaplin. "COMPARATIVE ANALYSIS OF BUSINESS PROCESS MONITORING TOOLS IN THE FINANCIAL SECTOR." Вестник Московского финансово-юридического университета, no. 3 (2021): 92–103. http://dx.doi.org/10.52210/2224669x_2021_3_92.

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41

Kim, Jongchan, and Marco Comuzzi. "A diagnostic framework for imbalanced classification in business process predictive monitoring." Expert Systems with Applications 184 (December 2021): 115536. http://dx.doi.org/10.1016/j.eswa.2021.115536.

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42

Barnawi, Ahmed, Ahmed Awad, Amal Elgammal, Radwa El Shawi, Abdullah Almalaise, and Sherif Sakr. "Runtime self-monitoring approach of business process compliance in cloud environments." Cluster Computing 18, no. 4 (2015): 1503–26. http://dx.doi.org/10.1007/s10586-015-0494-0.

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43

Pérez-Álvarez, José Miguel, Alejandro Maté, María Teresa Gómez-López, and Juan Trujillo. "Tactical Business-Process-Decision Support based on KPIs Monitoring and Validation." Computers in Industry 102 (November 2018): 23–39. http://dx.doi.org/10.1016/j.compind.2018.08.001.

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44

Comuzzi, Marco. "Alignment of process compliance and monitoring requirements in dynamic business collaborations." Enterprise Information Systems 11, no. 6 (2016): 884–908. http://dx.doi.org/10.1080/17517575.2015.1135482.

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45

Loreti, Daniela, Federico Chesani, Anna Ciampolini, and Paola Mello. "A distributed approach to compliance monitoring of business process event streams." Future Generation Computer Systems 82 (May 2018): 104–18. http://dx.doi.org/10.1016/j.future.2017.12.043.

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46

Shevchenko, Ihor, Denys Vasyliev, Serhii Prytchyn, and Andrii Samoilov. "Business processes monitoring based on fuzzy cognitive maps." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 3 (October 4, 2022): 110–20. http://dx.doi.org/10.32620/reks.2022.3.08.

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The subject matter of the article is a toolkit and monitoring processes of weakly structured business processes using fuzzy cognitive maps (FCMs). The goal is to create a model for monitoring and forecasting the course of business processes based on the FCMs, which provide flexibility and the ability to adapt to the conditions of changing circumstances in the process to be monitored, as well as insurance of the possibility of applying unstable FCM.s The task is to develop a formal monitoring system model; develop a computational FCM model; develop a method of using unstable FCMs: to develop a

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47

Kubrak, Kateryna, Fredrik Milani, Alexander Nolte, and Marlon Dumas. "Prescriptive process monitoring: Quo vadis?" PeerJ Computer Science 8 (September 29, 2022): e1097. http://dx.doi.org/10.7717/peerj-cs.1097.

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Prescriptive process monitoring methods seek to optimize a business process by recommending interventions at runtime to prevent negative outcomes or address poorly performing cases. In recent years, various prescriptive process monitoring methods have been proposed. This article studies existing methods in this field via a systematic literature review (SLR). In order to structure the field, this article proposes a framework for characterizing prescriptive process monitoring methods according to their performance objective, performance metrics, intervention types, modeling techniques, data inpu

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48

Künzle, Vera, Barbara Weber, and Manfred Reichert. "Object-Aware Business Processes." International Journal of Information System Modeling and Design 2, no. 2 (2011): 19–46. http://dx.doi.org/10.4018/jismd.2011040102.

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Despite the increasing maturity of process management technology not all business processes are adequately supported by it. Support for unstructured and knowledge-intensive processes is missing, especially since they cannot be straight-jacketed into predefined activities. A common characteristic of these processes is the role of business objects and data as drivers for process modeling and enactment. This paper elicits fundamental requirements for effectively supporting such object-aware processes; i.e., their modeling, execution, and monitoring. Imperative, declarative, and data-driven proces

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49

Yanti, Yanti. "MODEL RANCANGAN SISTEM INFORMASI PROJECT MONITORING." CommIT (Communication and Information Technology) Journal 3, no. 2 (2009): 59. http://dx.doi.org/10.21512/commit.v3i2.515.

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Economic development makes the property industry growing very rapidly. The property development is supported by the development of contractor’s company that conducts property development. Inside the contracting company doing business can not perform their own procurement because of the many items that must be provided. For the purposes of the construction company entered into an agreement with the subcontractor as vendor conduct procurement in accordance with the needs of contracting companies. To simplify the procurement process, generally conducted by a process called a tender / auction. Thi

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50

Wiratama, Jansen. "Analysis and Design of Production Monitoring Information Systems on Label Shoe Manufacturing Companies." Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika 20, no. 1 (2022): 12–23. http://dx.doi.org/10.33751/komputasi.v20i1.6075.

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Digital technology can be used to solve problems that arise from business activity. One company that has not optimally used digital technology is PT Tiga Tapak Mutiara, which is engaged in manufacturing shoe labels. In its business process, each related division collects data, and the data collection results will be reported to the manager to unify work activities. The production data collection process has not been carried out optimally by the relevant divisions because the conventional recording is still carried out using a spreadsheet application which can slow down the reporting process to

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