Factors that influence the payment for Rubber Replanting Program (TSGG) : Based on National Key Economic Area (NKEA) at Kelantan / Nur Ayuni Naseri

Rubber Industry Smallholders Development Authority (RISDA) Kelantan is one of the government companies in Kelantan State which produce one of the National Key
Economic Areas (NKEAs) as mention in the Tenth Malaysia Plan which includes palm oil and rubber. One of the major programs organized by RISDA was replanting. For this program, RISDA was responsible for implementing old rubber trees with either rubber or other approved crops for smallholder sector. This program was introduces to increase the productivity of smallholder sector. Factors such as districts and approved areas were used in this study with total of 227 observations. This study was conducted to check the significant of correlations between the variables (approved area, district and payment), to determine which variables (approved area or district) most affected to the payment given based on rubber replanting program and to determine which variables (approved area or payment) has different means between the districts. To answer all objectives and to test the hypotheses, analysis in this study were done by using IBM SPSS Statistics 21. To
illustrate, first the researcher used descriptive analysis to get the percentage and frequency of each district which involved in the study and to get the means for both
approved area and payment. Next the researcher used correlation coefficients to check whether the correlations between the variables (approved area, district and
payment) were significant. Besides, the output also shows whether it has strong, moderate or weak and either positive or negative correlations. Before proceed with
Multiple Linear Regression (MLR), model adequacy checking was used to check whether the assumptions (normality, homogeneity and independence) were satisfied.
If one of the assumptions does not satisfy, transformations method was used until all assumptions were satisfy. Then the Analysis Of Variance (ANOVA) was used to check the significant of the model and the variables. The existent of multicollinearity also can be detected by looking at the value of VIF and Tolerance. Next, one-way ANOVA was used to comparing whether the means (approved area and payment) were significantly different or not between the district. Lastly, the researcher used Post-Hoc Test if there if different for means between the district. The study
concluded that the correlations were significant. Besides, the result shows that the best model was when only APPROVED_A as the independent variables. Lastly, it
also can be concluded that there is no difference in payment mean between districts. But, each district shows that the approved area means were significantly different