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All Journal JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA
Irvandi, Firzakalpa Syafiq
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Pemodelan M-Adaptive Generalized Poisson Regression Spline Pada Kasus MDR-TB Di Kalimantan Barat Irvandi, Firzakalpa Syafiq; Debataraja, Naomi Nessyana; Yudhi, Yudhi
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol. 10 No. 2 (2023): Jurnal Derivat (Agustus 2023)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jderivat.v10i2.4481

Abstract

Tuberculosis is a disease caused by the Mycobacterium tuberculosis. Multi-Drug Resistant Tuberculosis (MDR-TB) is the term used to describe Mycobacterium tuberculosis that is resistant to one or more Anti-TB drugs. This study aims to determine the factors that affect the number of patients recovering from MDR-TB, by modeling the number of MDR-TB cured patients using Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS) method. The predictor variables are the average age (X1), percentage of patients who fail category 2 treatment (X2), percentage of patients who fail category 1 treatment (X3), percentage of patients relapsed (X4), percentage of patients neglecting treatment (X5), and percentage history of close contact with other patients (X6). A combination of BF (Basis function), MI (Maximum interaction), and MO (Minimum observation), the BF value is two to four times of predictor variables, MI has value of 1,2, and 3, and MO has value of0,1,2, and 3. From the result, the best model was obtained from the combination of BF=24, MI=3, and MO=1, with GCV values of 0,3504 and R2 of 88,3%, and there are 14 BF that affect the response variable . The most influential predictors variables in a row, are X6, X3, X5, and X2.  Keywords: Poisson, basis function, GCV
Pemodelan M-Adaptive Generalized Poisson Regression Spline Pada Kasus MDR-TB Di Kalimantan Barat Irvandi, Firzakalpa Syafiq; Debataraja, Naomi Nessyana; Yudhi, Yudhi
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol. 10 No. 2 (2023): Jurnal Derivat (Agustus 2023)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jderivat.v10i2.4481

Abstract

Tuberculosis is a disease caused by the Mycobacterium tuberculosis. Multi-Drug Resistant Tuberculosis (MDR-TB) is the term used to describe Mycobacterium tuberculosis that is resistant to one or more Anti-TB drugs. This study aims to determine the factors that affect the number of patients recovering from MDR-TB, by modeling the number of MDR-TB cured patients using Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS) method. The predictor variables are the average age (X1), percentage of patients who fail category 2 treatment (X2), percentage of patients who fail category 1 treatment (X3), percentage of patients relapsed (X4), percentage of patients neglecting treatment (X5), and percentage history of close contact with other patients (X6). A combination of BF (Basis function), MI (Maximum interaction), and MO (Minimum observation), the BF value is two to four times of predictor variables, MI has value of 1,2, and 3, and MO has value of0,1,2, and 3. From the result, the best model was obtained from the combination of BF=24, MI=3, and MO=1, with GCV values of 0,3504 and R2 of 88,3%, and there are 14 BF that affect the response variable . The most influential predictors variables in a row, are X6, X3, X5, and X2.  Keywords: Poisson, basis function, GCV
Co-Authors Debataraja, Naomi Nessyana Yudhi