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All Journal Journal of Dinda : Data Science, Information Technology, and Data Analytics
Idfian Azhar Hidayat
Institut Teknologi Telkom Purwokerto
Computer Science & IT

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Classification of Sleep Disorders Using Random Forest on Sleep Health and Lifestyle Dataset Idfian Azhar Hidayat
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 3 No 2 (2023): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v3i2.1215

Abstract

This study aims to classify sleep disorders using Random Forest method on the Sleep Health and Lifestyledataset. This dataset contains information about sleep, lifestyle, and relevant health factors. In this study, thedataset was processed and divided into training and testing subsets. The Random Forest model was trained usingthe training subset with sleep and health-related features. The split quality in each decision tree wasmeasured using the Gini Index. The model was evaluated using the testing subset to measure its accuracy andclassification performance. The evaluation results showed that the Random Forest model could accurately predict sleep disorders. Analysis of class distributions, correlation relationships between features,and visualization by gender provided insights into the factors that influence sleep disorders. This research can potentially contribute to the field of health and medicine, especially in the recognition and diagnosis of sleepdisorders.
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