PREDICTION OF THE STATE LOSS RISKO POTENCY USING SEMIVARIOGRAM AND AREA-TO-AREA POISSON KRIGING INTERPOLATION (CASE STUDY: TRANSPARENT LOBSTER SEEDS IN LOMBOK ISLAND)

• Main Author: Puspa S, Febrina
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/84183
• Institution: Institut Teknologi Bandung

The risk mapping of transparent lobster seeds in the on shore south of Lombok Islands can be predicted spatially using semivariogram model and Poisson Kriging interpolation with area-to-area approach. Risk identification has been carried out to quantify all the possible possibility outcomes because of the governance policies of transparent lobster seeds. This identification approach is carried out from the perspective of government surveillance of transparent lobster seeds fishing by the fishermen, a good surveillance is that can further minimize the risk. Risk potency formulated by the Government policy and the existed research data related to the survival rate, economic value, illegal export of transparent lobster seeds. The risk formula which are then processed spatially are risk (????????(????)) and each of its transformation, subrisk (????????(????), ????????(????), ????????(????)), aggregate risk (????(????)) and its transformation, subaggregate risk ????(????), risk determinant (????????(????)), and coefficient ????+(,) and ????-. The output of spatial data processing are semivariogram model parameters, contour map, and risk prediction in an unobserved location. The best theoretical model chosen in this theses is an exponential model, with the parameters for each risk ????????(????), ????????(????), ????????(????), and ????(????), in a row: sills (6,564 × 10!"; 3,617 × 10!#; 8,678 × 10!$; 8,676 × 10!$), and ranges (1; 1; 1; 1). Whereas the risk transformation are ????????(????) ?, ????????(????) ?, ????????(????) ?, and ????(????) ? in a row are sills (2,132×10-4; 7,540×10-5; 2,771×10-1; 2,005×10-1) and ranges (1; 2; 1; 1). At the end of data processing, the transformation risk is retransformed to be ????????(????) ??????(????) ?? then compare with the original risk, ????????(????)????(????), to check the error. The result shows that the value of retransform risk ????????(????) ??????(????) ?? is not significantly different from the risk ????????(????)????(????).