No abstract

Indonesia Village Fund policy aims to foster local democracy and rural development through direct funds allocation. During the last seven years (2015-2022), the government has provided Village Fund 400,1 trillion rupiahs (278,3 billion dollars) and continues to increase every year. Numerous studies discover the Village Fund impact on economic conditions but are limited to village scale. This study intends to analyze the impact of the Village Fund on a macro scale, point on the economic growth of a region, specifically on disadvantaged regions. The study conducted through quantitative methods used the panel data approach. The data covers 416 districts from 2015 to 2019. The result shows that the Village Fund has a significant effect, but the value of the effect on GDPR (Gross Domestic Product of Region) is lower than other variables. The effect of Village Fund in disadvantaged regions is greater than in non-disadvantaged regions, which indicates growth acceleration in disadvantaged regions.

Indonesia is one of the countries with a fairly high level of disaster proneness. Based on the results of the 2020 Indonesia Disaster Risk Index (IRBI) published by BNPB, out of the number of 514 districts, there are 237 districts with high risk, while 277 districts with moderate risk. The high number of Indonesian disasters can also be seen from the number of disaster events. So far, disaster identification is limited to the district. The disaster risk index also has an area only up to the district. Whereas each village has different location characteristics so that disaster management cannot be equated. Therefore, this study tried to look at the risk of disaster-prone at the village level. The data used is the 2020 Village Potential data by looking at the number of disaster events and also the number of fatalities in each village from 2019 to March 2020. The method used an analysis description approach through data exploration. In addition, using quantitative methods principal analysis components to create an Index that will classify a village whether prone to disaster or not. The results of identification are still many villages that are prone to disaster. From these results, it is mapped that there are 1,158 villages that have high risk, 27,061 medium risk and 46,446 villages are in low risk. This means that about 38 thousand still have a risk of being prone to disasters.

The village as an area that rests on local potential always needs development in product innovation and a sustainable market. In the world of agriculture, digital technology has been developing from nurseries to post-harvest. Included in the integrated agricultural system from upstream to downstream. Integrated smart farming system as an agricultural system that combines all components needed in agriculture (include the digitalization) were attracting young farmer’s interest. This paper aims to describe an integrated agriculture model in Bali. The research was conducted by a descriptive analysis method of existing conditions. The results showed there was an upstream stage of agricultural development carried out through technology for seeding and breeding to produce more quality seedlings. The process involves young farmers who act as an organization that bridges farmers through funding for farmers, quality control, stock management, and farmer organizing. The downstream stage focuses on post-harvest processing, so farmers can sell their crops to market to meet retail and export needs. As the conclusion, the development of potential products through the use of the Integrated Smart Farming System can provide economic added value and encourage the economic growth of villages.

Building a sustainable economy for rural areas must be based on good public literacy of the surrounding natural conditions. Therefore, it needs to formulate recommendations for lending decisions so that the economic resilience of rural communities remains good when natural disasters occur due to climate change. This study uses descriptive analysis, a decision tree model, and interviews as a basis for analyzing to get the right decisions for financial service providers in providing credit loans to certain economic sectors in West Java rural communities. The novelty of this research is able to explain the disaster risk index in the village which can be taken into consideration in the process of making credit decisions by financial service providers. Therefore, the value of credit restructuring due to natural disasters can be minimized and not become a loss so that it does not become an obstacle to the economic resilience of rural communities.