Data Mining techniques have been applied in many application areas. A Data Mining project has been often described as a process of automatic discovery of new knowledge from large amounts of data. However the role of the domain knowledge in this process and the forms that this can take, is an issue that has been given little attention so far. Based on our experience with a large scale Data Minin...

Basically, medical diagnosis problems are the most effective component of treatment policies. Recently, significant advances have been formed in medical diagnosis fields using data mining techniques. Data mining or Knowledge Discovery is searching large databases to discover patterns and evaluate the probability of next occurrences. In this paper, Bayesian Classifier is used as a Non-linear dat...

Day by day the number of organizations is increasing which using process mining to understand the way of execution of operational processes. For ssystematically drive the innovation in the digitalized world is used by Process Mining. The aim of Process mining is to get the knowledge of an organization's business processes by transforming the event data recorded in information systems. This...

The majority of process mining techniques focuses on control flow. Decision Point Analysis (DPA) exploits additional data attachments within log files to determine attributes decisive for branching of process paths within discovered process models. DPA considers only single attribute values. However, in many applications, the process environment provides additional data in form of consecutive m...

ABSTRAK Proses Discovery merupakan teknik utama dalam proses mining yang bertujuan untuk menghasilkan sebuah model dari event log. Namun implementasinya ditemukan masalah, karena banyak varian terdapat pada Hal ini membuat hasil discovery sulit dipahami. Penelitian di awali dengan mengelompokan log menggunakan metode K-Means sebagai tahap pre-processing. Hasil pre-processing kemudian modelkan m...

Data mining is used to extract useful information from the large amount of data. It is used to implement and solve different types of research problems. The research related areas in data mining are text mining, web mining, image mining, sequential pattern mining, spatial mining, medical mining, multimedia mining, structure mining and graph mining. Text mining also referred to text of data mini...

Process discovery—discovering a process model from example behavior recorded in an event log—is one of the most challenging tasks in process mining. The primary reason is that conventional modeling languages (e.g., Petri nets, BPMN, EPCs, and ULM ADs) have difficulties representing the observed behavior properly and/or succinctly. Moreover, discovered process models tend to have deadlocks and l...

Process mining techniques allow for extracting information from event logs. For example, the audit trails of a workflow management system or the transaction logs of an enterprise resource planning system can be used to discover models describing processes, organizations, and products. Traditionally, process mining has been applied to structured processes. In this paper, we argue that process mi...