| dc.description.abstract | Trade of reptiles in regional and international have been increased every
year. The trade of reptiles was divided into three namely pet reptile, consumption
reptile and reptile skin. The trade of skin reptile greater than pest, because the
skin of reticulated python is the most popular and to be excellent among
exporters. Quotas export is all of number of quota exporter should be traded by
exporter to international. This study aimed to identify of key variables exporter
and formulation of calculation quota exporters of reticulated python.
Data were collected from 44 exporter skin of phyton from June to November
2015. The methods used in this research were examination of administrative
documents exporters and direct observation to the enclosure to 44 exporter skin of
phyton reticulated. Processing and data analysis includes the identification of
variables of exporter performance. Variables performance of exporter were
export realization ofthe previous year (X1), labor (X2), finished product (X3),
crusted product (X4), investment value (X5), yield (X6), PNBP (X7), state of export
(X8), time of realization (X9), conservation activities (X10), chemicals (X11), and
electricity (X12). Data was analyzed using pearson correlation, multikolinearitas
and regression on SPSS version 23.
Results showed that key variables that have a correlation to the calculation
of quotas exporter and has no multikolenieritas between independent variables
are finished product (X3) , the product crusted ( X4 ) , the investment value ( X5 ) ,
yield ( X6 ) , PNBP (X7) , time realization ( X9 ) , conservation activities (X10) and
chemicals ( X11 ) . Based on the analysis of linier regression formula obtained
quota determination exporter: Y = 2.001 + 0.002 X3 + 0.072 X4 + 0.080 X5 +
0.030 X6 – 0.384 X9 + 0.059 X10. The result of regression equation of adjusted R
square is 0.916. It means that the quation of regression linear is 91.6% for
calculation of quotas as it could be explained by finished product, products
crusted, yield, investment, time of realization and conservation activities, while
8.4% is explained by variables that are not included in of this research. Variables
were positively related to the calculation of export quotas include finished
product (X3), product crusted (X4), investments (X5), yield (X6), and conservation
activities (X10), while the variables that have a negative relationship is time of
realization ( X9). | id |
