Segmentasi Pengalaman Pelanggan Pengguna Aplikasi Youtube Streaming Pada Daerah Jakarta Selatan Menggunakan Metode K-Means (Studi Kasus PT. XL AXIATA Tbk.)

Abstract

YouTube is one of the largest video sharing sites on the internet. More than 1.9 billion users per month visit YouTube. 70% of total YouTube watch time comes from mobile phones. Therefore, as a network service provider, PT XL Axiata Tbk. intends to improve the quality of service and quality of customer experience by targeting high value customers. One way is to track the customer experience of watching videos on the internet, one of which is on YouTube. Segmentation is one way to find and identify the quality of the experience that customers receive. To choose the right quality problem handling, service providers need to look at network service quality parameters, such as throughput, delay, and latency. Segmentation is carried out using a data mining approach, to be precise with the K-means clustering technique. The working method follows the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. Through the data preparation stage, 4 important attributes are obtained for modeling. Determination of the optimal number of clusters using the Elbow Method shows that there are 3 clusters formed, with cluster 2 as the best cluster, and cluster 1 as the most dominant cluster of users. This research can be used for PT XL Axiata Tbk. as input in the quality of network services for customers.