OLAP Cube Processing of Production Planning Real-life Event Log: A Case Study
- Rachmadita Andreswari, Mohammad Arif Rasyidi
- Corresponding Author
- Rachmadita Andreswari
Available Online March 2019.
- https://doi.org/10.2991/icoiese-18.2019.27How to use a DOI?
- process mining; OLAP; heuristic miner; production planning
- Business process modeling in an application log can be done by using process mining technique. To analyze the process flow in more detail in several dimensions needs cube process. Multidimensional depiction in star schema to perform Online Analytical Processing (OLAP) can be done by drill-down, roll-up, slice, and dice method. This research was conducted to analyze log characteristic in production planning module by performing cube process. The analysis was done by performing process cube on a set of log module of production planning. In this study the dimensions used in process cube are event class, timestamp and activity. Data that had been processed with the cube was modeled by using heuristic miner algorithm. The results obtained from this study is that for the three parts of data that have been processed with the cube, the best measurement value for fitness was obtained by female of 1 while the best precision in male is at 0.56, and the value of each structure is at 1 for each data. The result of measurement also shows that the number of transitions and places in a process model influences the measurement of conformance value. Overall, the existence of cube process performed has influenced the process model and the resulting measurement.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Rachmadita Andreswari AU - Mohammad Arif Rasyidi PY - 2019/03 DA - 2019/03 TI - OLAP Cube Processing of Production Planning Real-life Event Log: A Case Study BT - 2018 International Conference on Industrial Enterprise and System Engineering (ICoIESE 2018) PB - Atlantis Press SN - 2589-4943 UR - https://doi.org/10.2991/icoiese-18.2019.27 DO - https://doi.org/10.2991/icoiese-18.2019.27 ID - Andreswari2019/03 ER -