Luthfiyah, Andini Diva
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Pengelompokan Pengguna Spotify Berdasarkan Data Tipe Campuran Menggunakan Algoritma K-Prototype Luthfiyah, Andini Diva; Mukhti, Tessy Octavia
Imajiner: Jurnal Matematika dan Pendidikan Matematika Vol 8, No 3 (2026): Imajiner: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/imajiner.v8i3.27264

Abstract

Competition in streaming music services requires a better understanding of user behavior and churn tendencies. This study aims to segment Spotify users and analyze churn patterns based on demographic characteristics and service usage behavior using the K-Prototypes method on mixed-type data. The optimal number of Cluster was determined using the Elbow method, while the churn variable was used to evaluate the clustering results. The analysis shows that three user cluster were formed with distinct characteristics. The first cluster represents younger premium users with relatively high usage intensity, the second cluster represents student users with the highest churn proportion, and the third cluster represents free users with high ad exposure but the lowest churn proportion. These findings indicate that the K-Prototypes method is effective in grouping Spotify users and provides useful information for understanding user behavior and churn tendencies.