期刊名称：International Journal of Energy Economics and Policy
电子版ISSN：2146-4553
出版年度：2019
卷号：9
期号：2
页码：390-398
DOI：10.32479/ijeep.7223
出版社：EconJournals
摘要：Indonesia has many areas with the various tourism potentials but faces obstacles in the management, one of them is Suranadi Tourism Village in Narmada District, West Lombok Regency. This research aimed to analyze 1) the potential and tourism management system in Suranadi Tourism Village; 2) internal and external factors affecting the development of Suranadi Tourism Village; 3) the development strategy of Suranadi Tourism Village. This research applies some theories such as tourism destination development theory by Cooper (1993), irridex theory by Doxey (1976), and tripartite attraction design theory by Gunn (1972). This research used qualitative approach with descriptive method. Data obtained through interviews and observation. The method of data analysis in this research is by qualitative data analysis and SWOT analysis. The results showed that the potential of Suranadi Village as a cultural tourism village that is the potential of nature and culture. The various of potentials in the Suranadi Tourism Village as a whole has not managed professionally and optimally so that economic benefits are not fully felt for local community. The results of SWOT matrix analysis showed that there are four alternative strategies generated such as SO strategy (Strengths-Opportunities), ST strategy (Strengths-Threats), WO strategy (Weaknesses-Opportunities), WT strategy (Weaknesses-Threats).
其他摘要：Owing to its simplicity and less restrictions, the vector autoregressive with exogenous variable (VARX) model is one of the statistical analyses frequently used in many studies involving time series data, such as finance, economics, and business. The VARX model can explain the dynamic behavior of the relationship between endogenous and exogenous variables or of that between endogenous variables only. It can also explain the impact of a variable or a set of variables on others through the impulse response function (IRF). Furthermore, VARX can be used to predict and forecast time series data. In this study, PTBA and HRUM energy as endogenous variables and exchange rate as an exogenous variable were studied. The data used herein were collected from January 2014 to October 2017. The dynamic behavior of the data was also studied through IRF and Granger causality analyses. The forecasting data for the next one month was also investigated. On the basis of the data provided by these different models, it was found that VARX (3,0) is the best model to assess the relationship between the variables considered in this work. Keywords : VAR model, VARX model, Granger causality, Impulse Response Function, Forecasting. JEL Classifications : C32, Q4, Q47 DOI: https://doi.org/10.32479/ijeep.7223
