BANKING FINANCE ANALYSIS ON AGRICURURAL SECTOR AND ITS EFFECT ON ECONOMIC GROWTH AND AGRICULTURAL INVESTMENT IN INDONESIA - Muhammad Zulhilmi (Universitas Trisakti, 2015)
The agriculture sectors the main in supporting national economic development in each country. Similarly with Indonesia. With the vast area and the majority of Indonesian people work as farmers, the agriculture sector has a strategic role in employment to flabor; Hence the government should focus on improving growth and investment in the agriculture sector. The main issues in the economic development of agriculture in Indonesia in the lackof capital. This is in contrast toother developing countries where the government gives subsidies to this sector. Short ages on the capital side is due to the low income of people who have an impact on the low of saving ability, thus the investment in the agriculture sector in low. While the increase in financing at the agriculture sector will pose aconsiderable influence on the Real Gross National Saving. Real Bank Landing to agriculture, Real Out-Put of Agriculture sub-Sector, Real Investmen in Agriculture and will have an impact on economic growth and investment in agriculture. This study was designed to use secondary data by using a model analysis techniques of Structural Equation Modeling. In addition, this study also uses a model approach of Tawhidi string Relation (TSR). In the premise of Tawhidi String Relations, this research will be identified quantitatively by using analysis Vector Error Correction Model (VECM) and Forecast Error Variance Decomposition (FEVD), which aims to look at the welfare of farmers in sharia. The result of the analysis shows that the level of the Real Gross National Saving, Real Bank Lending to Agriculture, Real Out-Put of Agriculture of sub-Sector. Real Investment in Agriculture and the agriculture sectore has a significant influence on sub sequent economic growth and investment. The ruselt ofthe analysis with TSR also shows a significant effect. This is indicated by the level of the biggest change in sequence, namely: variable GDP (Ѳ) 33.27%, variable (Ѳ) 22.21%, variable AGE (Ѳ) 12.45%, Variable BLAFF 11.09%, variable EAGEXP (Ѳ) of 8.01% and the variable RGNS (Ѳ) of 7.17%.