89 COPULA MODELING IN ANALYSIS OF DEPENDENCY OF OIL PALM PRODUCTION AND RAINFALL Dadan Kusnandar 1,* , Naomi Nessyana Debataraja 1 , Shantika Martha1 1 1 Department of Statistics, FMIPA, Universitas Tanjungpura, Pontianak, Indonesia *Corresponding author: dkusnand@untan.ac.id Abstract Copula is a method that examines the relationship pattern between variables. Copula is characterized as a nonparametric method with several benefits, i.e., it is independent of the assumption of the distribution, accommodates nonlinear relationship among variables, and is convenient in building joint distribution. This study investigates the relationship and prediction analysis using the copula approach. The method is applied to the monthly data of oil palm production and the amount of rainfall. The results show that the model of Frank Copula is the best model for rainfall and oil palm production relationship. Keywords Relationship, Correlation coefficient, Archimedean Copula, Elliptical Copula, Maximum Likelihood Estimation INTRODUCTION Oil palms are tropical plants that can grow well in the latitude of 12o N to 12o S. The amount of rainfall in the tropical area is considered important to the plant growth and productivity. Some studies show that the amount of rainfall and rainy days affect the productivity of the plants (Prasetyo 2009; Simanjuntak, Sipayung and Irsal 2014). The ideal rainfall for oil palm is 2000-2500 mm per year evenly distributed throughout the year without long dry months. A long dry season could reduce the production of oil palm since fewer minerals in soil are absorbed by the plants (Risza 2014). On the other hand, too much rainfall can cause erosion of topsoil especially in areas with bad topography. Copula is one method that can be used to describe the relationship between variables without any assumption of the distribution. It can reveal relation of dependency even at extreme points (Anisa and Sutikno 2015). Copula has an important role when one or both variables have an abnormal marginal distribution or have tail dependencies. The use of the copula in investigating the relationship among variables has been studied by many authors in various fields. Anisa and Sutikno (2015) and Udayani, Sumarjaya, and Susilawati (2016) used copula in the analysis of relationship in agricultural research. Murterio and Lourencio (2007) applied copula in the health care utilization, whereas Zhu, Ghosh and Goodwin (2008) used copula in modeling dependence in the design of the insurance contract. Syahrir (2011) estimated copula parameters in the field of climatology. The Copula approach resulted in better estimates even in the presence of extreme observational data and for conditions that violate normality assumptions. This paper discusses the application of the copula in modeling the relationship between two variables, namely rainfall and palm oil production. The aim of Indonesian Journal of Physics and Nuclear Applications Volume 3, Number 3, October 2018, p. 89-94 e-ISSN e-ISSN 2550-0570, © FSM UKSW Publication