Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control

Rice pest control is a critical challenge in the agricultural sector that requires a deep understanding of rice pest management. Regression analysis is a statistical method capable of describing and predicting cause-and-effect relationships between individuals. In real-life applications, not all rel...

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Main Authors: Laila Nur Azizah, Adji Achmad Rinaldo Fernandes, Ni Wayan Surya Wardhani
Format: Article
Language:English
Published: Mathematics Department UIN Maulana Malik Ibrahim Malang 2025-03-01
Series:Cauchy: Jurnal Matematika Murni dan Aplikasi
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Online Access:https://ejournal.uin-malang.ac.id/index.php/Math/article/view/29773
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author Laila Nur Azizah
Adji Achmad Rinaldo Fernandes
Ni Wayan Surya Wardhani
author_facet Laila Nur Azizah
Adji Achmad Rinaldo Fernandes
Ni Wayan Surya Wardhani
author_sort Laila Nur Azizah
collection DOAJ
description Rice pest control is a critical challenge in the agricultural sector that requires a deep understanding of rice pest management. Regression analysis is a statistical method capable of describing and predicting cause-and-effect relationships between individuals. In real-life applications, not all relationships exhibit a known curve pattern, and non-identifiable curve forms are often observed. Additionally, a single cause may affect more than one outcome, and the outcomes themselves can have interrelationships. Such relationships can be approached through a multi-response semiparametric regression using a truncated spline multi-group model. This study aims to develop a multi-response semiparametric multi-group regression model using the truncated spline approach to understand the variables influencing rice pest control under light and dark conditions. This model is applied to secondary and simulated data with various scenarios to determine the best model. The study results indicate that the optimal model for secondary data is a semiparametric regression model with a linear order and a single knot point, achieving a determination coefficient of 89.17%. Simulation results show that the scenario 1 model (linear with a single knot point) produces a high determination coefficient. This multi-response regression model proves more optimal when error variance and multicollinearity levels are kept low to moderate.
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language English
publishDate 2025-03-01
publisher Mathematics Department UIN Maulana Malik Ibrahim Malang
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series Cauchy: Jurnal Matematika Murni dan Aplikasi
spelling doaj-art-b2fc56bc0d6b4a998270c7c659482da12025-08-20T03:48:30ZengMathematics Department UIN Maulana Malik Ibrahim MalangCauchy: Jurnal Matematika Murni dan Aplikasi2086-03822477-33442025-03-01101365210.18860/cauchy.v10i1.297738637Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest ControlLaila Nur Azizah0Adji Achmad Rinaldo Fernandes1Ni Wayan Surya Wardhani2Brawijaya UniversityBrawiajaya UniversityBrawijaya UniversityRice pest control is a critical challenge in the agricultural sector that requires a deep understanding of rice pest management. Regression analysis is a statistical method capable of describing and predicting cause-and-effect relationships between individuals. In real-life applications, not all relationships exhibit a known curve pattern, and non-identifiable curve forms are often observed. Additionally, a single cause may affect more than one outcome, and the outcomes themselves can have interrelationships. Such relationships can be approached through a multi-response semiparametric regression using a truncated spline multi-group model. This study aims to develop a multi-response semiparametric multi-group regression model using the truncated spline approach to understand the variables influencing rice pest control under light and dark conditions. This model is applied to secondary and simulated data with various scenarios to determine the best model. The study results indicate that the optimal model for secondary data is a semiparametric regression model with a linear order and a single knot point, achieving a determination coefficient of 89.17%. Simulation results show that the scenario 1 model (linear with a single knot point) produces a high determination coefficient. This multi-response regression model proves more optimal when error variance and multicollinearity levels are kept low to moderate.https://ejournal.uin-malang.ac.id/index.php/Math/article/view/29773multi-groupmulti-responses semiparametric regressionrice pesttruncated splineweighted least square
spellingShingle Laila Nur Azizah
Adji Achmad Rinaldo Fernandes
Ni Wayan Surya Wardhani
Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control
Cauchy: Jurnal Matematika Murni dan Aplikasi
multi-group
multi-responses semiparametric regression
rice pest
truncated spline
weighted least square
title Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control
title_full Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control
title_fullStr Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control
title_full_unstemmed Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control
title_short Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control
title_sort simulation study and development of semiparametric multiresponse multigroup truncated spline regression for rice pest control
topic multi-group
multi-responses semiparametric regression
rice pest
truncated spline
weighted least square
url https://ejournal.uin-malang.ac.id/index.php/Math/article/view/29773
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AT niwayansuryawardhani simulationstudyanddevelopmentofsemiparametricmultiresponsemultigrouptruncatedsplineregressionforricepestcontrol