PROSES MINING UNTUK OPTIMASI PROSES BISNIS

Organizations currently need to conduct an analysis of their business processes in order to improve business performance and productivity. In addition, this analysis can be a way to compete with competitors. However, the analysis of this business process if done manually requires considerable time. Process mining is a technique that helps solve this problem. Information systems that are owned by a company certainly store their every business activity. This data can be processed to find business processes that occur. This data is usually called an event log. Event logs help organizations to find gaps between business processes that occur with those expected. Based on this gap business processes can later be evaluated for later improvement.Organisasi saat ini perlu melakukan analisis terhadap proses bisnis mereka dalam rangka meningkatkan kinerja serta produktifitas bisnis. Selain itu analisis ini dapat menjadi suatu cara untuk bersaing dengan kompetitor. Akan tetapi analisis proses bisnis ini jika dilakukan secara manual membutuhkan waktu yang cukup banyak. Hal yang dapat dilakukan untuk mengatasi permasalahan ini adalah dengan melakukan proses mining. Sistem Informasi yang dimiliki oleh sebuah perusahaan tentunya menyimpan setiap aktifitas bisnis mereka. Data yang tersimpan ini dapat diolah untuk menemukan proses bisnis yang terjadi. Data ini biasa disebut event log. Event log membantu organisasi untuk menemukan kesenjangan diantara antara proses bisnis yang terjadi dengan yang diharapkan. Berdasarkan kesenjangan inilah nantinya proses bisnis dapat dievaluasi untuk kemudian diperbaiki

Benefícios da utilização da mineração de processos / Benefits of using process mining

A mineração de processos é um tema que tem apresentado relevância nos últimos anos, tendo em vista a constante necessidade de melhoria de processos de negócios em ambientes competitivos. Assim, num contexto em que se busca melhorias de eficiência, a presente pesquisa objetiva identificar os principais benefícios resultantes da utilização de mineração de processos nas organizações. Para se alcançar o objetivo proposto pelo estudo, foi realizada uma revisão sistemática de literatura, proposta por Cooper (1984), objetivando, a partir da pesquisa e análise dos estudos primários, realizar a discussão e a síntese dos resultados. A partir da metodologia utilizada, foram selecionados estudos primários que dispunham sobre os benefícios decorrentes da aplicação da mineração de processos. Foram identificados diversos benefícios decorrentes da utilização da técnica nas organizações, classificados em 14 modalidades distintas.O presente estudo se justifica pela relevância do tema e pela falta de achados, na literatura, de estudos que abordem, de forma sistemática, os benefícios identificados por pesquisas primárias, decorrentes da aplicação da mineração de processos.

Aplicação do Process Mining na Auditoria de Processos Governamentais

A auditoria de processos de negócios é um tema de relevância crescente na literatura. No entanto, técnicas tradicionais e manuais demonstram-se insatisfatórias ou insuficientes, visto que as mesmas são custosas, podem ser tendenciosas e passíveis de erros, além de envolverem grande quantidade de recursos temporais, humanos e materiais. Nesse sentido, o presente estudo vem demonstrar como a técnica de process mining pode ser utilizada, de forma automática, na auditoria de processos governamentais, a partir de um sistema de informação e de uma ferramenta de mining denominada ProM. A partir de técnicas de verificação de conformidade, realizou-se a comparação entre os processos reais e seus respectivos modelos oficiais de uma organização governamental. Os resultados obtidos demonstram algumas divergências entre eles, e indicam que a técnica pode ser utilizada como um meio auxiliar na realização de auditoria de processos de negócios

Verslo procesų prognozavimo ir imitavimo taikant sisteminių įvykių žurnalų analizės metodus tyrimas

Business process (BP) analysis is one of the core activities in organisations that lead to improvements and achievement of a competitive edge. BP modelling and simulation are one of the most widely applied methods for analysing and improving BPs. The analysis requires to model BP and to apply analysis techniques to the models to answer queries leading to improvements. The input of the analysis process is BP models. The models can be in the form of BP models using industry-accepted BP modelling languages, mathematical models, simulation models and others. The model creation is the most important part of the BP analysis, and it is both time-consuming and costly activity. Nowadays most of the data generated in the organisations are electronic. Therefore, the re-use of such data can improve the results of the analysis. Thus, the main goal of the thesis is to improve BP analysis and simulation by proposing a method to discover a BP model from an event log and automate simulation model generation. The dissertation consists of an introduction, three main chapters and general conclusions. The first chapter discusses BP analysis methods. In addition, the process mining research area is presented, the techniques for automated model discovery, model validation and execution prediction are analysed. The second part of the chapter investigates the area of BP simula-tion. The second chapter of the dissertation presents a novel method which automatically discovers Bayesian Belief Network from an event log and, furthermore, automatically generates BP simulation model. The discovery of the Bayesian Belief Network consists of three steps: the discovery of a directed acyclic graph, generation of conditional probability tables and their combination. The BP simulation model is generated from the discovered directed acyclic graph and uses the belief network inferences during the simulation to infer the execution of the BP and to generate activity data dur-ing the simulation. The third chapter presents the experimental research of the proposed network and discusses the validity of the research and experiments. The experiments use selected logs that exhibit a wide array of behaviour. The experiments are performed in order to test the discovery of the graphs, the inference of the current process instance execution probability, the predic-tion of the future execution of the process instances and the correctness of the simulation. The results of the dissertation were published in 9 scientific publica-tions, 2 of which were in reviewed scientific journals indexed in Clarivate Analytics Science Citation Index