Implementation of Business Intelligence for Monitoring Technician Performance Using Google Looker Studio (Case Study: PT Telkom Akses Bengkulu)

Aliffatun Khoiriyah; Yudi Setiawan; Yopy Linarto

doi:10.70656/ijcse.v3i02.895

Authors

Aliffatun Khoiriyah Information System Study Program, Department of Engineering, University of Bengkulu
Yudi Setiawan Information System Study Program, Department of Engineering, University of Bengkulu
Yopy Linarto Pt Telkom Akses Bengkulu

DOI:

https://doi.org/10.70656/ijcse.v3i02.895

Keywords:

Business Intelligence, Dashboard, Performance Monitoring, Data Visualization, Technician Performance

Abstract

IndiHome's customer service disruption handling activities at PT Telkom Akses Bengkulu produce operational data that continue to grow every day, but the data is still managed in the form of scattered raw data, making it difficult to monitor and analyze the performance of technicians. The purpose of this practical work is to process data on handling customer service interruptions, monitor technician performance, and present information in the form of an easy-to-understand dashboard. The method used in this study is business intelligence with the stages of data cleaning, data transformation, and data visualization, using Google Looker Studio as a data visualization tool. The data used is operational data on technician assignments in the period of the end of 2025 to early 2026 with a total of 448 work data points that include the name of the technician and the work area. The results of the study indicated that the dashboard was able to present information on the number of technician jobs, the average job per technician, and the distribution of jobs by region in a more structured manner. The dashboard can also show which technicians have the most jobs and how much each technician's work contributes, which makes it easier to keep track of the performance process. With the application of this business intelligence, companies can monitor the performance of technicians more effectively and support data-based decisionmaking.

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