Determination Of Calculation Quota Exporters Of Skin Reticulated Python (Python Reticulatus Scheider 1801) Environmental In Indonesia.
Sari, Eka Nurmala
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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).