scholarly journals Gap analysis business process model by using structural similarity

2020 ◽  
Vol 18 (1) ◽  
pp. 124
Author(s):  
Afrianda Cahyapratama ◽  
Kelly Rosa Sungkono ◽  
Riyanarto Sarno
Keyword(s):  
Business Process ◽  
Process Model ◽  
Gap Analysis ◽  
Graph Matching ◽  
Structural Similarity ◽  
Process Models ◽  
Dice Coefficient ◽  
Matching Algorithm ◽  
Event Log ◽  
Percent Similarity

<span>Gap analysis process model is a study that can help an institution to determine differences between business process models, such as a model of Standard Operating Procedure and a model of activities in an event log. Gap analysis is used for finding incomplete processes and can be obtained by using structural similarity. Structural similarity measures the similarity of activities and relationships depicting in the models.  This research introduces a graph-matching algorithm as the structural similarity algorithm and compares it with dice coefficient algorithms. Graph-matching algorithm notices parallel relationships and invisible tasks, on the contrary dice coefficient algorithms only measure closeness between activities and relationships. The evaluation shows that the graph-matching algorithm produces 76.76 percent similarity between an SOP model and a process model generating from an event log; while, dice coefficient algorithms produces 70 percent similarity. The ability in detecting parallel relationships and invisible tasks causes the graph-matching algorithm produces a higher similarity value than dice coefficient algorithms.</span>

scholarly journals Common Process Extraction pada Model Proses Bisnis Tebang Muat Angkut (TMA)

2020 ◽  
Vol 7 (2) ◽  
pp. 71-76
Author(s):  
Salma Fatia ◽  
Muhammad Ainul Yaqin ◽  
Adi Heru Utomo
Keyword(s):  
Business Process ◽  
Process Modeling ◽  
Process Model ◽  
Structural Similarity ◽  
Business Process Modeling ◽  
Process Models ◽  
Business Process Models ◽  
Common Fragment ◽  
Behavioral Similarity ◽  
Business Process Modeling Notation

Abstract— In an organizational environment, there are various business process models with the same procedures. If an organization builds a system with the same procedure repeatedly, it will undoubtedly incur a lot of effort and money. Therefore, it is necessary to extract common fragments to save effort. This research uses four scenarios of business process models: sequence, branching, nested branching, and looping. This study uses Business Process Modeling Notation (BPMN) notation so that the process model consists of activities, connectors, and gateways. Structural similarity is measured using the Jaccard similarity formula by comparing the process model. The similarity of behavior is measured using the Transition Adjacency Relations (TARs) method to obtain common fragments. The results show that the sequence process model will produce a common fragment that tends to be sequential too. The branching will produce a common fragment that tends to branch, and nested branching will produce a common fragment that tends to be branched and nested, as well as looping will produce a common fragment contains looping too. The experimental results show that the proposed method can extract common fragments based on the available business process models. Keywords—BPMN; common fragment; behavioral similarity; TARs   Abstrak— Dalam lingkungan organisasi, terdapat berbagai model proses bisnis dengan prosedur yang sama. Jika suatu organisasi membangun sistem dengan prosedur yang sama secara berulang-ulang, niscaya akan mengeluarkan banyak tenaga dan biaya. Oleh karena itu, perlu mengekstrak fragmen umum untuk menghemat tenaga. Penelitian ini menggunakan empat skenario model proses bisnis yaitu sequence, branching, nested branching, dan looping. Penelitian ini menggunakan notasi Business Process Modeling Notation (BPMN) sehingga model proses terdiri dari aktivitas, konektor, dan gateway. Kemiripan struktural diukur menggunakan rumus kemiripan Jaccard dengan membandingkan model proses. Kesamaan perilaku diukur menggunakan metode Transition Adjacency Relations (TARs) untuk mendapatkan fragmen yang sama. Hasil penelitian menunjukkan bahwa model sequence process akan menghasilkan common fragment yang cenderung berurutan juga. Percabangan akan menghasilkan fragmen umum yang cenderung bercabang, dan percabangan bersarang akan menghasilkan fragmen umum yang cenderung bercabang dan bersarang, serta perulangan akan menghasilkan fragmen umum yang berisi perulangan juga. Hasil eksperimen menunjukkan bahwa metode yang diusulkan dapat mengekstrak fragmen umum berdasarkan model proses bisnis yang tersedia. Keywords—BPMN; common fragment; kemiripan perilaku; TARs

scholarly journals Event Log Preprocessing for Process Mining: A Review

2021 ◽  
Vol 11 (22) ◽  
pp. 10556
Author(s):  
Heidy M. Marin-Castro ◽  
Edgar Tello-Leal
Keyword(s):  
Business Process ◽  
Process Model ◽  
Process Mining ◽  
Data Cleaning ◽  
Data Preprocessing ◽  
Process Models ◽  
Event Data ◽  
Event Logs ◽  
Event Log ◽  
Preprocessing Technique

Process Mining allows organizations to obtain actual business process models from event logs (discovery), to compare the event log or the resulting process model in the discovery task with the existing reference model of the same process (conformance), and to detect issues in the executed process to improve (enhancement). An essential element in the three tasks of process mining (discovery, conformance, and enhancement) is data cleaning, used to reduce the complexity inherent to real-world event data, to be easily interpreted, manipulated, and processed in process mining tasks. Thus, new techniques and algorithms for event data preprocessing have been of interest in the research community in business process. In this paper, we conduct a systematic literature review and provide, for the first time, a survey of relevant approaches of event data preprocessing for business process mining tasks. The aim of this work is to construct a categorization of techniques or methods related to event data preprocessing and to identify relevant challenges around these techniques. We present a quantitative and qualitative analysis of the most popular techniques for event log preprocessing. We also study and present findings about how a preprocessing technique can improve a process mining task. We also discuss the emerging future challenges in the domain of data preprocessing, in the context of process mining. The results of this study reveal that the preprocessing techniques in process mining have demonstrated a high impact on the performance of the process mining tasks. The data cleaning requirements are dependent on the characteristics of the event logs (voluminous, a high variability in the set of traces size, changes in the duration of the activities. In this scenario, most of the surveyed works use more than a single preprocessing technique to improve the quality of the event log. Trace-clustering and trace/event level filtering resulted in being the most commonly used preprocessing techniques due to easy of implementation, and they adequately manage noise and incompleteness in the event logs.

scholarly journals Business processes exceptions in relation to operational performance

2019 ◽  
Vol 25 (5) ◽  
pp. 908-922 ◽  
Author(s):  
Remco Dijkman ◽  
Oktay Turetken ◽  
Geoffrey Robert van IJzendoorn ◽  
Meint de Vries
Keyword(s):  
Business Process ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Operational Performance ◽  
Normal Flow ◽  
Throughput Time ◽  
Content Type ◽  
Business Process Models ◽  
Practical Implications

Purpose Business process models describe the way of working in an organization. Typically, business process models distinguish between the normal flow of work and exceptions to that normal flow. However, they often present an idealized view. This means that unexpected exceptions – exceptions that are not modeled in the business process model – can also occur in practice. This has an effect on the efficiency of the organization, because information systems are not developed to handle unexpected exceptions. The purpose of this paper is to study the relation between the occurrence of exceptions and operational performance. Design/methodology/approach The paper does this by analyzing the execution logs of business processes from five organizations, classifying execution paths as normal or exceptional. Subsequently, it analyzes the differences between normal and exceptional paths. Findings The results show that exceptions are related to worse operational performance in terms of a longer throughput time and that unexpected exceptions relate to a stronger increase in throughput time than expected exceptions. Practical implications These findings lead to practical implications on policies that can be followed with respect to exceptions. Most importantly, unexpected exceptions should be avoided by incorporating them into the process – and thus transforming them into expected exceptions – as much as possible. Also, as not all exceptions lead to longer throughput times, continuous improvement should be employed to continuously monitor the occurrence of exceptions and make decisions on their desirability in the process. Originality/value While work exists on analyzing the occurrence of exceptions in business processes, especially in the context of process conformance analysis, to the best of the authors’ knowledge this is the first work that analyzes the possible consequences of such exceptions.

scholarly journals Pengujian Unit Plugin Pemberian Anotasi Efek Secara Semantik pada Proses Bisnis BPMN

2021 ◽  
Vol 6 (3) ◽  
pp. 170
Author(s):  
Hilman Nuril Hadi
Keyword(s):  
Business Process ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Unit Testing ◽  
Business Process Model ◽  
Testing Technique ◽  
Modeling Tools ◽  
Path Testing ◽  
Future Business

Business process model was created to make it easier for business process stakeholders to communicate and discuss the structure of the process more effectively and efficiently. Business process models can also be business artifacts and media that can be analyzed further to improve and maintain organizational competitiveness. To analyze business processes in a structured manner, the effect/results of the execution of business processes will be one of the important information. The effect/result of the execution of certain activities or a business process as a whole are useful for managing business processes, including for improvements related to future business processes. This effect annotation approach needs to be supported by business process modeling tools to assist business analysts in managing business processes properly. In previous research, the author has developed a plugin that supports business analysts to describe the effects semantically attached to activities in the Business Process Model and Notation (BPMN) business process model. In this paper, the author describes the unit testing process and its results on the plugin of semantic effect annotation that have been developed. Unit testing was carried out using the basic path testing technique and has obtained three test paths. The results of unit test for plugin are also described in this paper.

scholarly journals Data Model and Software Architecture for Business Process Model Generator

2018 ◽  
Vol 2 (4-2) ◽  
pp. 349
Author(s):  
Ivaylo Kamenarov ◽  
Katalina Grigorova
Keyword(s):  
Software Architecture ◽  
Business Process ◽  
Data Model ◽  
Process Model ◽  
Process Models ◽  
Process Chain ◽  
Business Process Models ◽  
Model Generator ◽  
The Individual ◽  
Natural Way

This paper describes the internal data model for a business process generator. Business process models are stored in an Event-driven process chain notation that provides a natural way to link the individual elements of a process. There is a software architecture that makes it easy to communicate with users as well as external systems.

scholarly journals Business Process Models in the Context of Predictive Process Monitoring

2021 ◽  
Vol 28 (1) ◽  
pp. 39-46
Author(s):  
Florian Spree
Keyword(s):  
Process Monitoring ◽  
Business Process ◽  
Process Model ◽  
Academic Research ◽  
Research Area ◽  
Process Models ◽  
Business Process Model ◽  
Business Process Models ◽  
Wide Range ◽  
Predictive Process

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 the awareness of business process models in experimental setups. Secondly, the paper discusses identified research problems and proposes the concept of a web-based business process model metric suite and the idea of ranked metrics. Through a metric suite researchers and practitioners can automatically evaluate business process model characteristics in their future work. Further, a contextualization of metrics by introducing a ranking of characteristics can potentially indicate how the outcome of experimental setups will be. Hence, the paper's work demonstrates the importance of business process models and their characteristics in the context of predictive process monitoring and proposes the concept of a tool approach and ranking to reliably evaluate business process models characteristics.

scholarly journals Collaborative method to maintain business process models updated

2014 ◽  
Vol 11 (2) ◽  
pp. 461-480 ◽  
Author(s):  
Nuno Castela ◽  
Paulo Dias ◽  
Marielba Zacarias ◽  
José Tribolet
Keyword(s):  
Case Studies ◽  
Business Process ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Organizational Environment ◽  
Business Process Model ◽  
Business Process Models ◽  
Definition Of ◽  
Over Time

Business process models are often forgotten after their creation and its representation is not usually updated. This appears to be negative as processes evolve over time. This paper discusses the issue of business process models maintenance through the definition of a collaborative method that creates interaction contexts enabling business actors to discuss about business processes, sharing business knowledge. The collaboration method extends the discussion about existing process representations to all stakeholders promoting their update. This collaborative method contributes to improve business process models, allowing updates based in change proposals and discussions, using a groupware tool that was developed. Four case studies were developed in real organizational environment. We came to the conclusion that the defined method and the developed tool can help organizations to maintain a business process model updated based on the inputs and consequent discussions taken by the organizational actors who participate in the processes.

scholarly journals Towards Aspects Identification in Business Process Through Process Mining

2015 ◽  
Author(s):  
Bruna Brandão ◽  
Flávia Santoro ◽  
Leonardo Azevedo
Keyword(s):  
Programming Languages ◽  
Business Process ◽  
Process Model ◽  
Process Mining ◽  
Process Models ◽  
Preliminary Evaluation ◽  
Crosscutting Concerns ◽  
Business Process Models ◽  
Event Logs ◽  
Initial Results

In business process models, elements can be scattered (repeated) within different processes, making it difficult to handle changes, analyze process for improvements, or check crosscutting impacts. These scattered elements are named as Aspects. Similar to the aspect-oriented paradigm in programming languages, in BPM, aspect handling has the goal to modularize the crosscutting concerns spread across the models. This process modularization facilitates the management of the process (reuse, maintenance and understanding). The current approaches for aspect identification are made manually; thus, resulting in the problem of subjectivity and lack of systematization. This paper proposes a method to automatically identify aspects in business process from its event logs. The method is based on mining techniques and it aims to solve the problem of the subjectivity identification made by specialists. The initial results from a preliminary evaluation showed evidences that the method identified correctly the aspects present in the process model.

Business Semantics Alignment for Business Process Model Integration

2013 ◽  
pp. 91-112
Author(s):  
Janina Fengel
Keyword(s):  
Business Process ◽  
Process Model ◽  
Process Models ◽  
Modeling Languages ◽  
Semantic Matching ◽  
Domain Experts ◽  
Business Operations ◽  
Novel Approach ◽  
Support Domain ◽  
Processing Techniques

Business process modeling has become an accepted means for designing and describing business operations. However, due to dissimilar utilization of modeling languages and, even more importantly, the natural language for labeling model elements, models can differ. As a result, comparisons are a non-trivial task that is presently to be performed manually. Thereby, one of the major challenges is the alignment of the business semantics contained, which is an indispensable pre-requisite for structural comparisons. For easing this workload, the authors present a novel approach for aligning business process models semantically in an automated manner. Semantic matching is enabled through a combination of ontology matching and information linguistics processing techniques. This provides for a heuristic to support domain experts in identifying similarities or discrepancies.

Ontology-Based Framework for Quality in Configurable Process Models

2020 ◽  
pp. 464-478
Author(s):  
Loubna El Faquih ◽  
Mounia Fredj
Keyword(s):  
Business Process ◽  
Process Modeling ◽  
Process Model ◽  
Business Processes ◽  
Research Work ◽  
Process Models ◽  
Novel Method ◽  
Ontology Languages ◽  
Variability Management

In recent years, business process modeling has increasingly drawn the attention of enterprises. As a result of the wide use of business processes, redundancy problems have arisen and researchers introduced the variability management, in order to enhance the business process reuse. The most approach used in this context is the Configurable Process Model solution, which consists in representing the variable and the fixed parts together in a unique model. Due to the increasing number of variants, the configurable models become complex and incomprehensible, and their quality is therefore impacted. Most of research work is limited to the syntactic quality of process variants. The approach presented in this paper aims at providing a novel method towards syntactic verification and semantic validation of configurable process models based on ontology languages. We define validation rules for assessing the quality of configurable process models. An example in the e-healthcare domain illustrates the main steps of our approach.

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