Aisyah Larasati, Neng Rizqi Ni'mah, Candra Nurul Laksana, Effendi Mohamad, Abdul Muid, Rudi Nurdiansyah
Defect handling is a system at PT XYZ used to identify and repair machine damage to ensure that damage repairs have been carried out and return to normal conditions on time. At PT XYZ, this system still has problems, such as not integrating defect handling reports from all factory areas, so it is difficult to analyze and monitor, and there is no visualization of data from all factory areas. This system is a key performance indicator (KPI) that must be monitored daily. Therefore, it is necessary to design a business intelligence dashboard to collect, integrate, analyze, and visualize business information defect handling system data using the online analytical processing (OLAP) method. The flow of this research process uses business intelligence roadmaps, namely justification, planning, business analysis, design, and construction. The construction consists of creating a data source, ETL process, data warehouse, and dashboard with online analytical processing (OLAP) analysis and ending with a black box test. The main tools in this research are power query, power pivot, and spreadsheet. From the black box test results, it was found that this business intelligence dashboard was suitable for use. Operations in analyzing OLAP data on the defect handling dashboard in the form of slice, dice, roll-up, drill-down, and pivoting can help analyze defect handling data throughout the factory areas. Real-time data on the dashboard helps speed up the analysis and execution of follow-up on machine damage. © 2024 IEEE.
State University of Malang, Dept. of Mechanical and Industrial Engineering, Malang, Indonesia; Khc Indonesia, Department of Continuous Improvement, Pasuruan, Indonesia; Universiti Teknikal Melaka Malaysia, Faculty of Manufacturing Engineering, Melaka, Malaysia
