Implementation of Data Mining Technique for Performance of WFH and WFO Agents Using the K-Means Method Case Study Study of PT. Infomedia Telkom Consumer Profiling Services

Jaja Jaja (Faculty of Computer Science, Universitas Subang, Indonesia)
Nandi Priatna (Faculty of Computer Science, Universitas Subang, Indonesia)
Tazkia Salsabila Ardan (Faculty of Computer Science, Universitas Subang, Indonesia)

Budapest International Research in Exact Sciences (BirEx Journal)
Vol 3, No 2 (2021): Budapest International Research in Exact Sciences, April

Outbound Call Center PT. Infomedia, consumer profiling service PT. Telkom during the pandemic period divided its agents into 80% WFH agents (Work at Home) and 20% agents WFO (Work from Office). For the division of the working mechanism, it is necessary to measure its performance. In the discussion of this paper, we will discuss the measurement with the application of data mining using the K-Means method, so it is hoped that it will provide an overview, how the cluster of each WFH or WFO agent in terms of performance. The results of this discussion indicate that there is a significant difference between the performance of WFH and WFO Agents.