This study was aimed to determine the challenges of developing an Integrated Farming System (IFS). IFS is one of the solutions for agricultural development in Indonesia by integrating agriculture, livestock, fisheries, forestry and other sciences related to agriculture. It is expected to be able to increased land productivity. This research was conducted with a comparative study from various countries such as Brazil, India, US, sub-Saharan Africa countries regarding development issues, implementation, and constraints that occur in an IFS. The method of study is literature study. The results of the study show that the implementation of the IFS system poses various challenges, including: a) lack of understanding of farmers towards IFS, b) limited ability of farmers to utilize agricultural technology and c) financial support. However, IFS can increase agricultural food security and increased farmer welfare and expand employment. The implementation of IFS requires government support to create opportunities to increase farm scale in line with farmers’ income.

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.

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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 Indonesian government has set a target of 0 extreme poverty by 2024. Pandemic covid-19 make this target become more challenges. Various strategies have been designed by the government to achieve the poverty target, such as digitalization. The purpose of this article is to estimate the impact of digitalization on poverty reduction and economy growth in Indonesia. Using data from 34 provinces in Indonesia from 2015 to 2020. This article's empirical analysis is based on panel data, Random Effect Model (REM) with an estimation technique of Two Stages Least Square (2SLS). Our results show, digitization has a significant effect on reducing poverty. On the other hand, digitalization has negative impact on economic growth. In order for digitalization to have a major impact in encouraging poverty alleviation, various things are needed, including increasing community capacity and supporting regulations made by the government. Capacity building is carried out so that the community is able to take advantage of digitalization for productive activities so as to encourage increased community welfare. Government policy support is also needed to support the wider use of digitalization.