IDENTIFIKASI POLA TIDUR GENERASI Z (GEN-Z) MENGGUNAKAN ALGORITMA KLUSTERISASI K-MEANS

Generation Z faces great challenges in maintaining healthy sleep patterns due to lifestyle changes and high exposure to technology. This study aims to identify the sleep patterns of Generation Z as well as the main factors that affect their sleep quality using the K-Means algorithm. Data was collected from 300 participants through an online questionnaire that included variables such as sleep duration, difficulty sleeping, caffeine consumption, electronic device use, physical activity, and freshness after waking up. With a clustering approach, the results of the study showed that there were three main patterns: irregular sleep patterns (45%), healthy sleep patterns (35%), and poor sleep patterns (20%). The cluster with healthy sleep patterns had an average of 7-8 hours of sleep, high physical activity, and low caffeine consumption, while irregular sleep patterns were less dominated by the use of electronic devices before bedtime, high caffeine consumption, and low physical activity. These findings highlight the importance of lifestyle management in improving the sleep quality of Generation Z and provide a basis for the development of more effective interventions. This study concludes that data-based clustering is a useful method to understand the sleep patterns of a particular population in more depth.

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Publication Details

Journal
Jurnal Teknik Informasi dan Komputer (Tekinkom)
Published
2024-12-31
DOI
https://doi.org/10.37600/tekinkom.v7i2.1740
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
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article

IDENTIFIKASI POLA TIDUR GENERASI Z (GEN-Z) MENGGUNAKAN ALGORITMA KLUSTERISASI K-MEANS

Riski Annisa, Panny Agustia Rahayuningsih, Anna Anna, Reymond Syahputra Hidayana et al.
Jurnal Teknik Informasi dan Komputer (Tekinkom)
Data Mining and Machine Learning Applications
article

IDENTIFIKASI POLA TIDUR GENERASI Z (GEN-Z) MENGGUNAKAN ALGORITMA KLUSTERISASI K-MEANS

Riski Annisa, Panny Agustia Rahayuningsih, Anna Anna, Reymond Syahputra Hidayana, Zulfikar Ismaya Ramadhani
article en

Abstract

Generation Z faces great challenges in maintaining healthy sleep patterns due to lifestyle changes and high exposure to technology. This study aims to identify the sleep patterns of Generation Z as well as the main factors that affect their sleep quality using the K-Means algorithm. Data was collected from 300 participants through an online questionnaire that included variables such as sleep duration, difficulty sleeping, caffeine consumption, electronic device use, physical activity, and freshness after waking up. With a clustering approach, the results of the study showed that there were three main patterns: irregular sleep patterns (45%), healthy sleep patterns (35%), and poor sleep patterns (20%). The cluster with healthy sleep patterns had an average of 7-8 hours of sleep, high physical activity, and low caffeine consumption, while irregular sleep patterns were less dominated by the use of electronic devices before bedtime, high caffeine consumption, and low physical activity. These findings highlight the importance of lifestyle management in improving the sleep quality of Generation Z and provide a basis for the development of more effective interventions. This study concludes that data-based clustering is a useful method to understand the sleep patterns of a particular population in more depth.

Jurnal Teknik Informasi dan Komputer (Tekinkom)Vol. 7(2)
Openalex Percentile: Top 56%
Data Mining and Machine Learning Applications
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IDENTIFIKASI POLA TIDUR GENERASI Z (GEN-Z) MENGGUNAKAN ALGORITMA KLUSTERISASI K-MEANS — Riski Annisa, Panny Agustia Rahayuningsih, et al. · Jurnal Teknik Informasi dan Komputer (Tekinkom) (2024) | TGRS Research Map | TGRS