Analysis on productivity achievement of rubber industry in Selangor

Abstract

The primary aim of this study is to determine which factors have more contributions to the achievement of productivity of rubber industry in Selangor. This study is expected to provide significant information necessary for Rubber Industry Smallholders' Development Authority (RISDA) to plan strategies to increase the number of smallholders to achieve the target productivity. The independent variables are the age of rubber trees, the number of rubber trees tapped per year, the type of clone used, the type of tapping system, and the usage of stimulation. Logistic regression would be undertaken in analyzing the productivity achievement of rubber tappers. Additionally, the misclassification rate had been used as the criterion for judging the efficacy of a classifier of productivity and also sensitivity and specificity were statistical measure of the performance of binary classification. Based on the Wald test; land area, age of rubber trees, rubber land area, and usage of stimulation contribute significantly to the model. Logistic regression model fits the data based on the Hosmer and Lemeshow Goodness of Fit Test. Overall, 91.3% of the cases are classified correctly and this model posses good predictive efficiency. The results of the study indicate that the factors influence the achieving the target productivity were identified and therefore appropriate actions can be taken to promote and enable the smallholders to achieve the target productivity.