East Timor is one of the youngest nations in the world, having been established in 2002. The majority of East Timor's population works in the agricultural sector, yet the mining sector (oil and gas) plays a dominant role in contributing to the country's GDP. The management of oil revenue in East Timor is adapted from the model implemented in Norway, known as Norway Plus. Aware that oil and gas resources must be supported by other economic sectors in the long term, this study aims to analyze potential scenarios for developing East Timor's key economic sectors, as well as to propose potential policy pathways. The research approach uses prospective methods (SMIC-Prob analysis and MULTIPOL), which are suitable for policy formulation due to their future-oriented nature. Data collection was conducted through Focus Group Discussions (FGD) involving experts from both the government and academia. The results from the SMIC-Prob analysis show that the oil and gas sector indeed has the highest probability. However, in the long term, the agricultural sector emerges as a crucial alternative. Furthermore, the MULTIPOL analysis indicates that in scenarios focusing on the development of non-oil and gas sectors, policies should prioritize the development of local economic sectors. The government of East Timor is recommended to seriously develop non-oil and gas sectors by utilizing revenue from oil and gas extraction. Additionally, environmental governance is also a critical consideration to achieve sustainable, inclusive development.

Poverty is a complex and multidimensional social problem faced by almost all countries including Indonesia. Poverty alleviation efforts require accurate and up-to-date data to ensure that social welfare programs can effectively run and target appropriate beneficiaries. Bekasi Regency, as one of the regions that faces significant challenges in managing poverty, needs the right strategy in updating and utilizing poverty data to support social welfare programs. This study analyzes a policy framework for updating and utilizing the poverty data. The data were collected from focus group discussions with experts and stakeholders who were competent in updating and utilizing the poverty data. MULTIPOL method was used to analyze the data. The results of the study show that the best strategy for updating and utilizing poverty data in the scenario is to integrate scenarios with priority policy with digital budgeting policy, as well as priority actions providing incentives. This study makes an important contribution to regional development planning, especially poverty alleviation strategies based on accurate and integrative data.