| dc.description.abstract | Optimal utilization of fish resources is strongly influenced by fishing technology applied by the fisherman. There are many factors that may affect the level of fishing technology adoption by fisherman. Binary logistic regression approach is used to determine which factors that influence on the rate of fisherman’s technology adoption, while to determine importance of the factors, dominance analysis is used by the McFadden’s measures of model fit ( ) as the comparison value. Based on the analysis of binary logistic regression resulting six variables which are significant at the level of 5%, there are variables of fisherman’s age, fishing experience, fisherman’s income, the activity of searching for information, fisherman’s perception, and fisherman’s group support. The ranking predictors using dominance analysis result in three groups of predictors based on level of importance. The first group contains predictors with the highest level of importance, namely the perception of fisherman (X6). The second group contains three predictors, they are the fisherman’s age (X1), the fishing experience (X3), and the fisherman’s group support (X9). The third group contains two predictors that have lowest interest rate, they are the fisherman’s income (X4) and activity of searching for information (X5). | en |
