BibTex Citation Data :
@article{J.Gauss16131, author = {Puji Retnowati and Rita Rahmawati and Agus Rusgiyono}, title = {ANALISIS FAKTOR-FAKTOR PRODUKSI PERIKANAN TANGKAP PERAIRAN UMUM DARATAN DI JAWA TENGAH MENGGUNAKAN REGRESI BERGANDA DAN MODEL DURBIN SPASIAL}, journal = {Jurnal Gaussian}, volume = {6}, number = {1}, year = {2017}, keywords = {inland openwater capture fisheries production, maximum likelihood, spatial durbin mode}, abstract = { Indonesia’s inland openwater is the second largest in Asia after China. It’s estimated Indonesia’s inland openwater capture fisheries potential reached 3.034.934 tons per year. Central Java is one of the provinces that have great potential in the field of fisheries. In this study will be discussed about the factors suspected to affect inland openwater capture fisheries production. The method used are multiple regression analysis with maximum likelihood estimation and spatial durbin models. Spatial durbin models is the development of linear regression which location factors are also considered. The results of spatial dependences shows there is spatial dependence in the inland openwater capture fisheries production variable, fisheries establishments variables and the number of boats variable. So spatial durbin models can be used for analysis. In spatial durbin models, variables that significantly influence inland openwater capture fisheries production is the number of fishing gear, the number of boats, and the number of fishing trip with coefficient of determination (R 2 ) of 0,9054. While in the multiple regression analysis showed that the only number of fishing trip variable that significantly, where the value of the coefficient of determination (R 2 ) is 0,857. Thus better spatial durbin models used to analyze inland openwater capture fisheries production, in addition more significant variables also have the coefficient of determination (R 2 ) that is greater than the multiple regression analysis. Keywords: inland openwater capture fisheries production, maximum likelihood, spatial durbin model.}, issn = {2339-2541}, pages = {141--150} doi = {10.14710/j.gauss.6.1.141-150}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/16131} }
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Indonesia’s inland openwater is the second largest in Asia after China. It’s estimated Indonesia’s inland openwater capture fisheries potential reached 3.034.934 tons per year. Central Java is one of the provinces that have great potential in the field of fisheries. In this study will be discussed about the factors suspected to affect inland openwater capture fisheries production. The method used are multiple regression analysis with maximum likelihood estimation and spatial durbin models. Spatial durbin models is the development of linear regression which location factors are also considered. The results of spatial dependences shows there is spatial dependence in the inland openwater capture fisheries production variable, fisheries establishments variables and the number of boats variable. So spatial durbin models can be used for analysis. In spatial durbin models, variables that significantly influence inland openwater capture fisheries production is the number of fishing gear, the number of boats, and the number of fishing trip with coefficient of determination (R2) of 0,9054. While in the multiple regression analysis showed that the only number of fishing trip variable that significantly, where the value of the coefficient of determination (R2) is 0,857. Thus better spatial durbin models used to analyze inland openwater capture fisheries production, in addition more significant variables also have the coefficient of determination (R2) that is greater than the multiple regression analysis.
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