An operational support approach for Mining Unstructured Business Processes

The refined process mining framework contains a set of activities that use extracted information from event logs, discovered models and normative ones. Among these activities, we find those dealing with running events in a Structured Business Process (SBP) context, which are the Detect, the Predict and the Recommend activities. These three activities are nominated as an operational support system that aims at detecting deviations, predicting events and recommending actions. In this regard, operational support systems perform well on SBP while, it stills a challenging task for an Unstructured Business Process (UBP). This puts forward the difficulty of predicting events and recommending actions for UBP, because of its complex structure. In this context, simplification and structuring operations must be applied. Therefore, the intervention of other process mining activities is required for business process simplification and structuring. To this end, we present an operational support approach dealing with UBP, using the refined process mining framework activities.

Pengembangan Sistem Penunjang Operasional dan Pengelolaan Sumber Daya Manusia untuk Laboratorium Komputer

Human resources are an important asset in the entire company operations activity. A human resources management support system should be provided to improve performance in accordance with the company target. The purpose of this study is to design a model of operational and human resource management support systems that can integrate employee performance data, simplify management of employee data, and generate reports in the form of Key Performance Indicator (KPI) and Binusian Level. Methodology used in this study is using literature study, design, and test a model to make operational and human resource management information system. Index Terms - human resources, operational support system, Key Performance Indicator (KPI)