Open AccessPENERAPAN METODE PARTIAL LEAST SQUARE REGRESSION (PLSR) PADA KASUS SKIZOFRENIA
Author(s) -
Ni Wayan Ari Sundari,
I Gusti Ayu Made Srinadi,
Made Susilawati
Publication year - 2021
Publication title -
e-jurnal matematika
Language(s) - English
Resource type - Journals
ISSN - 2303-1751
DOI - 10.24843/mtk.2021.v10.i02.p333
Subject(s) - partial least squares regression , statistics , mathematics , principal component regression , regression analysis , principal component analysis , linear regression , value (mathematics) , regression , latent variable , variable (mathematics) , mathematical analysis
Partial Least Square Regression (PLSR) is a method that combines principal component analysis and multiple linear regression, which aims to predict or analyze the dependent variable and more than one independent variable. The purpose of this study is to determine the equation model for the recurrence of schizophrenia patients using the PLSR method. The best number of components to form a PLSR model in this study is one component with a minimum RMSEP value of 0.6094 and an adjR2 value of 80.09 percent.