Fitting the rice production model using generalized additive mixed model and generalized estimating equation with shiny web application. (May 2020)

• Record Type: Journal Article
• Authors: Darmawan, A S; Anggraeni, D; Tirta, I M
• Is Part Of: Journal of physics. Volume 1538(2020)
• Publication Date: 2020-05
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1538/1/012032
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Banyuwangi is a district in East Java province in Indonesia which is known as the Rice Barn of East Java. Banyuwangi region is facing challenges such as population growth, increased consumption of rice, reduced agricultural land because there are several agricultural land used as non-agricultural land. Because of there are production it is not enough from objects with just one period, therefore the use of data panels is one solution because it considers the time period and objects needed to determine the factors that influence rice production. In this study the analysis to model panel data from rice production in Banyuwangi was Generalized Additive Mixed Model (GAMM) and Generalized Estimating Equation GEE. In general GAMM as a mixed model, contains random effects so that this model is very useful when inference about individual differences is a major interest. While GEE is a model used to provide the population averaged effect. GEE also has the feature of smoothing natural cubic spline and B-spline so that it can be called GEE (+ NS/BS) which aims to improve the goodness of fitting a model. In this study, we want to see the effect of the total rainfall, harvest area, and population density on rice production. we also develop GAMM in the form of web interface to make users easier to analyze data using GAMM through http://statslab-rshiny.fmipa.unej.ac.id/RProg/MSD/.