Segmentation of Student Lifestyle Patterns for Insomnia Risk Identification Using the K-Means Algorithm - Athiyyah Anandira; Azzah Ulima Rahma; Amanda Putri Lestari; Dewi Fatmarani Surianto (Program Studi Teknik Komputer, 2025)
Insomnia is a common sleep disorder that occurs in college students due to unbalanced lifestyle patterns. This study aims to categorize students based on their lifestyle patterns and identify the risk of insomnia by applying the K-Means algorithm. Data were obtained from 198 active students of JTIK UNM batch 2021-2024 through a questionnaire. Five main variables were analyzed, such as sleep duration, caffeine consumption, gadget use, number of assignments per week, and hours of sleep. After the researchers transformed and normalized data, the clustering process had resulted in two clusters. The first cluster showed a higher risk of insomnia due to late bedtime and excessive gadget usage, while the second cluster tended to undergo a healthier lifestyle. The Davies-Bouldin Index value of 0.22 indicates superlative clustering qualities. This study provides an overview of student characteristics based on lifestyle and potential risk of insomnia.