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.

Future global economic stability is under significant threat from environmental risks. Rural peat areas are particularly susceptible due to their elevated levels of hazard, vulnerability, and limited capacity. Acknowledging these risks is pivotal for fostering a low-carbon development trajectory. This study analyzes the environmental risk in rural peat areas within Riau Province. The PROMETHEE method, incorporating Shannon Entropy weighting for data analysis, was employed. The findings reveal that four regencies are exhibiting favorable environmental risk conditions and five regencies facing adverse conditions. The criteria influencing the environmental risk of rural peat in Riau Province showcase various positive and negative contributions across each regency. The sensitivity analysis underscores the resilience of forest fires and the social forest program in three regencies. Recognizing environmental risk can serve as a foundation for decision-makers to formulate sustainable development policies.

Tourist village program is one development priority program for rural development. Despite numerous opportunities to develop tourist villages such as the availability of natural resources and high demand for tourist villages recently, some challenges are still faced to develop tourist villages, especially in a developing country such as Indonesia. Governance problems, infrastructure, and effective partnership are among other factors that remain challenging in developing tourist villages. This study attempts to identify factors that determine the state of tourist villages in Indonesia and determine the appropriate strategies for better tourist village development. Using the case of tourist villages in Kedung Ombo, Central Java, a water based attractive tourist village, this study uses both machine learning and multicriteria approaches by means of Promethee in order to address the objective of the study. This study shows that government support, application of information technology, infrastructure, local participation, partnership, and attractive variations, are among the determinant factors that affect tourist village development. The study also reveals that the appropriate strategies for tourist village development include, improving infrastructure, institutional strengthening, and capacity building. This study could be used to assist local national as well as sub-national governments to effectively manage tourist villages in Indonesia.

Vulnerability is one of the prominent features of rural areas due to their distinctive characteristics, such as remoteness, geographical conditions, and socio-economic dependence on primary sectors. Addressing the vulnerability of rural areas in terms of the rural development paradigm is both urgent and relevant. This study aims to address this issue using the current state-of-the-art machine learning method, using the socio-ecological framework and integrated vulnerability index of villages in Lampung Province in Indonesia. The study attempts to predict and classify villages' vulnerability to be applied for better planning and rural development. Based on random forest classification and decision tree algorithm, the results show that the village governance system represented by rural water management and the level of education of village leaders are suitable prediction variables related to the low vulnerability index. This study can draw lessons learned to improve rural development in developing countries.

The application of ICT in central and regional governments to cities in Indonesia seems to be the new face of the National bureaucracy, not least with digital public transportation services, Surabaya is a pilot application of smart cities because one of them implementing the Surabaya Smart Transportation System (SITS), this condition further strengthens that policy Public digital services are taken to make it easier for the public to monitor the crowd or the density of the highway, unfortunately, if you review the SITS comment column on Google Play, the negative sentiment is far big more than the positive sentiment. So, this study aims to capture the phenomenon of resistance by exploring the quality of information and system quality as predictors of public acceptance of the application of SITS. A result, empirically the quality of information and the quality of the system indirectly affect public acceptance of the application of SITS, as among the findings served that system quality is more dominant in influencing acceptance. So, it is highly recommended that the city government pays attention to the development of SITS applications based on system reliability.

Emotional factors in the use of technology have the potential to be studied, since the important role of user engagement in the information technology development cycle, emotional plays a role in influencing the relationship between consumers and service providers. Previous research has examined various emotional factors of a person in operating digital services through online sites, but it is necessary to find an empirical correlation between emotional variables and one's intention to reuse (IR) online services. This study aims to determine whether users' emotions affect their decision to reuse Government to Citizen (G2C) online tourism services in Indonesia through the HEART Metrics approach. Furthermore, this quantitative study distributed questionnaires using simple random sampling to respondents who had used online tourism. Then analyse 260 research data using the SEM-PLS method by running Warp-PLS 5.0. The findings of this study are among the 5 HEART Metrics factors, 3 of which affect IR, namely Engagement, Retention, and Task Success, while Happiness and Adoption empirically have no significant effect on IR. Our results show that to gain consumer engagement with online services, service providers must consider the emotional elements of the users so that service reuse goals can be achieved. Furthermore, this research can be considered as an alternative recommendation for online tourism service providers, as well as the findings of a new model proposed to contribute to similar research in the future.