LOGISTIC REGRESSION MODELING OF REDUCTANT HERBICIDE IN PAGARALAM COFFEE FARMING

The presence of weeds can affect the productivity of coffee plants. The use of herbicides that are not wise in controlling weeds can have a negative impact on the quality of coffee production and land. This study aims to obtain a binary logistic regression model of the use of reductant herbicides by...

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Main Authors: Irmeilyana Irmeilyana, Ngudiantoro Ngudiantoro, Sri Indra Maiyanti, Siddiq Makhalli
Format: Article
Language:English
Published: Universitas Pattimura 2023-12-01
Series:Barekeng
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Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9099
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author Irmeilyana Irmeilyana
Ngudiantoro Ngudiantoro
Sri Indra Maiyanti
Siddiq Makhalli
author_facet Irmeilyana Irmeilyana
Ngudiantoro Ngudiantoro
Sri Indra Maiyanti
Siddiq Makhalli
author_sort Irmeilyana Irmeilyana
collection DOAJ
description The presence of weeds can affect the productivity of coffee plants. The use of herbicides that are not wise in controlling weeds can have a negative impact on the quality of coffee production and land. This study aims to obtain a binary logistic regression model of the use of reductant herbicides by coffee farmers in Pagaralam South Sumatera. This research involved 165 coffee farmers, consisting of 81 farmers who used reductants and 85 farmers who did not use reductants. In the results of bivariate analysis, variables that have a significant effect on the status of using reductant herbicides, do not necessarily have a significant effect on the logistic regression model. Overall prediction accuracy of the model results of the enter method and backward method are respectively 78.2% and 76.4%. The two best models obtained show that farmer age, number of trees, number of family workers, and land productivity can reduce the probability value of farmers using reductant herbicide. On the other hand, variables that can increase the opportunity value of using reductants, starting with the greatest effect, are net income, length of harvest, frequency of herbicide use, frequency of use of organic fertilizers, and age of trees. Based on the factors that affect the use of reductants, coffee farmers should set aside costs for land maintenance, including costs for environmentally friendly weed control, so that they can support the coffee plants to continue producing optimally.
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spelling doaj-art-c86eca3e593e408e9c725fdc42d56f652025-08-20T03:36:37ZengUniversitas PattimuraBarekeng1978-72272615-30172023-12-011741957196810.30598/barekengvol17iss4pp1957-19689099LOGISTIC REGRESSION MODELING OF REDUCTANT HERBICIDE IN PAGARALAM COFFEE FARMINGIrmeilyana Irmeilyana0Ngudiantoro Ngudiantoro1Sri Indra Maiyanti2Siddiq Makhalli3Department of Mathematics, Faculty of Mathematics and Natural Science, University of Sriwijaya, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Science, University of Sriwijaya, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Science, University of Sriwijaya, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Science, University of Sriwijaya, IndonesiaThe presence of weeds can affect the productivity of coffee plants. The use of herbicides that are not wise in controlling weeds can have a negative impact on the quality of coffee production and land. This study aims to obtain a binary logistic regression model of the use of reductant herbicides by coffee farmers in Pagaralam South Sumatera. This research involved 165 coffee farmers, consisting of 81 farmers who used reductants and 85 farmers who did not use reductants. In the results of bivariate analysis, variables that have a significant effect on the status of using reductant herbicides, do not necessarily have a significant effect on the logistic regression model. Overall prediction accuracy of the model results of the enter method and backward method are respectively 78.2% and 76.4%. The two best models obtained show that farmer age, number of trees, number of family workers, and land productivity can reduce the probability value of farmers using reductant herbicide. On the other hand, variables that can increase the opportunity value of using reductants, starting with the greatest effect, are net income, length of harvest, frequency of herbicide use, frequency of use of organic fertilizers, and age of trees. Based on the factors that affect the use of reductants, coffee farmers should set aside costs for land maintenance, including costs for environmentally friendly weed control, so that they can support the coffee plants to continue producing optimally.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9099logistic regression modelnet incomepagaralam coffeeprobabilityreductant herbicides
spellingShingle Irmeilyana Irmeilyana
Ngudiantoro Ngudiantoro
Sri Indra Maiyanti
Siddiq Makhalli
LOGISTIC REGRESSION MODELING OF REDUCTANT HERBICIDE IN PAGARALAM COFFEE FARMING
Barekeng
logistic regression model
net income
pagaralam coffee
probability
reductant herbicides
title LOGISTIC REGRESSION MODELING OF REDUCTANT HERBICIDE IN PAGARALAM COFFEE FARMING
title_full LOGISTIC REGRESSION MODELING OF REDUCTANT HERBICIDE IN PAGARALAM COFFEE FARMING
title_fullStr LOGISTIC REGRESSION MODELING OF REDUCTANT HERBICIDE IN PAGARALAM COFFEE FARMING
title_full_unstemmed LOGISTIC REGRESSION MODELING OF REDUCTANT HERBICIDE IN PAGARALAM COFFEE FARMING
title_short LOGISTIC REGRESSION MODELING OF REDUCTANT HERBICIDE IN PAGARALAM COFFEE FARMING
title_sort logistic regression modeling of reductant herbicide in pagaralam coffee farming
topic logistic regression model
net income
pagaralam coffee
probability
reductant herbicides
url https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9099
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