PENGEMBANGAN MODEL PREDIKSI DURASI TIDUR TERHADAP PENGGUNAAN MEDIA ELEKTRONIK MENGGUNAKAN PENDEKATAN PEMBELAJARAN MESIN

HAFIDZOH, FARA NISSYA NUR and Passarella, Rossi (2024) PENGEMBANGAN MODEL PREDIKSI DURASI TIDUR TERHADAP PENGGUNAAN MEDIA ELEKTRONIK MENGGUNAKAN PENDEKATAN PEMBELAJARAN MESIN. Undergraduate thesis, Sriwijaya University.

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Abstract

The study aims to determine the best regression model to measure the linear relationship between electronic media use and sleep duration. as well as testing and measuring the level of impact of electronic media use on sleep duration.This study used various regression models that were developed and evaluated to determine the best model. The regression models are Linear Regression, Polynomial Regression, Lasso Regression, DecisionTree Regression, RandomForest Regression, Support Vector Regression (SVR), and Huber Regression. RandomForest regression showed the best performance with the highest R-squared and lowest MSE.Random Forest regression was selected as the best model. Although the R-squared and MSE values showed a mismatch, the mean residual value was close to 0, illustrating the model''s ability to capture the complexity of the data. The results also refuted the hypothesis that sleep duration is influenced by electronic media use

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Sleep Duration, Electronic Media, and Regression Model
Subjects:	Q Science > Q Science (General) > Q1-295 General
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Fara Nissya Nur Hafidzoh
Date Deposited:	18 Jan 2024 07:28
Last Modified:	18 Jan 2024 07:28
URI:	http://repository.unsri.ac.id/id/eprint/138762

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