Poverty is a major challenge caused by various situations as well as cultural, social, economic, and political interactions. Therefore, poverty alleviation programs and strategies require an integrated approach carried out in consistent and organized stages. It required the participation of all parties, both regional heads, Regional People’s Representative Assembly (RPRA) members, entrepreneurs, and other elements of society. This study aimed to investigate the effect of local spending efficiency on public welfare in Indonesia, using a quantitative and explanatory method. The analysis method used in this study is the panel data regression model. The research population in all provinces in Indonesia was 34 provinces, and a purposive sampling method was used, where a total of 26 provinces were selected. The research period is 2017–2021. The efficiency of local spending (education, health, and infrastructure) is estimated using the Stochastic Frontier Analysis (SFA) cost function approach. The results showed that the higher the efficiency of education spending, the more it will increase public welfare in Indonesia. Meanwhile, the health spending efficiency and the infrastructure spending efficiency do not affect public welfare. The implications of this study for the development of science are that the efficient allocation of education spending will be able to improve the quality of education which is a long-term solution to overcome poverty in Indonesia and for policymakers to be able to optimize education spending to achieve the expected educational goals.

In today’s fast-paced digital world, generative AI, especially OpenAI’s ChatGPT, has become a game-changing technology with significant effects on education. This study examines public sentiment and discourse surrounding ChatGPT’s role in higher education, as reflected on social media platform X (formerly Twitter). Employing a mixed-methods approach, we conducted a thematic analysis using Leximancer and Voyant Tools and sentiment analysis with SentiStrength on a dataset of 18,763 tweets, subsequently narrowed to 5655 through cleaning and preprocessing. Our findings identified five primary themes: Authenticity, Integrity, Creativity, Productivity, and Research. The sentiment analysis revealed that 46.6% of the tweets expressed positive sentiment, 38.5% were neutral, and 14.8% were negative. The results highlight a general openness to integrating AI in educational contexts, tempered by concerns about academic integrity and ethical considerations. This study underscores the need for ongoing dialogue and ethical frameworks to responsibly navigate AI’s incorporation into education. The insights gained provide a foundation for future research and policy-making, aiming to enhance learning outcomes while safeguarding academic values. Limitations include the focus on English-language tweets, suggesting future research should encompass a broader linguistic and platform scope to capture diverse global perspectives.

Air pollution in Jakarta has become a severe concern in the last four months. IQAir, in August 2023, revealed that the level of air pollution had reached 161 points on the Air Pollution Standard Index (APSI). The negative impact on society has placed air pollution as a concern for environmental safety and survival in danger. This condition will encourage the development of a national policy agenda to integrate environmental welfare through various energy efficiency channels. This research analyzes the relationship between air pollutant elements that can reduce air quality. The analysis includes pollutant intensity measured by APSI per unit of pollutant as a measure of efficiency. The aim is to observe energy use, which causes an increase in pollutant levels. This research utilizes dynamic system modeling to produce relationships between parameters to produce factors that cause pollution. The parameters used are motorized vehicles, waste burning in landfills, industry, and power plants. The results of historical behavioral tests and statistical suitability tests show that the behavior is suitable for the short and long term. The simulation results show that the pollution level will worsen by the end of 2027, a hazardous condition for society. The optimistic scenario simulation model proposes immediate counter-measures to reduce pollution to 45.01, the ideal condition. To accelerate improvements in air quality, the Government can plan policies to reduce the use of coal by power plants and industry, as well as the use of electric motorized vehicles, resulting in an ideal reduction in pollution by 2024. In conclusion, pollution can be reduced effectively if the Government firmly implements policies to maintain that air quality remains stable below 50 points.

While there has been much discussion about the large infrastructure needs in Asia and the Pacific, less attention has been paid to public expenditure efficiency in infrastructure services delivery. New constructions are not the only solution, especially when governments have limited capital to invest. Globally, new infrastructure projects face delays and cost overruns, leading to an inefficient use of public resources. The root causes include the lack of transparency in project selection, the lack of project preparation, the silo approach by public entities in assessing feasibility studies, and the lack of public sector capacity to fully develop a bankable pipeline of projects. To tackle these issues, governments need a smarter investment approach and to do so, enhancing public service efficiency is very crucial. The paper suggests a “whole life cycle” (WLC) approach as the main strategic solution for the discussed issues and challenges. We expand the definition of WLC to include the entire life cycle of the infrastructure asset from need identification to its disposal. The stages comprise planning, preparation, procurement, design, construction, operation and maintenance, and disposal. This is because we believe any efficient or inefficient decision throughout such a wide life cycle influences the quality of public services. Hence, in this holistic approach, infrastructure life cycle consists of four phases: planning, preparation, procurement, and implementation. Governments could enhance public efficiency and thus improve access to finance throughout the WLC by several solutions. These are (i) preparing infrastructure master plan and pipelines and long-term budgeting during the planning phase; (ii) establishing framework and guidelines and improving governance during preparation phase; (iii) promoting standardization, transparency, open government, and contractual consistency during the procurement phase; and finally (iv) continued role of government and total asset management during the implementation phase. In addition to these phase-specific means, key WLC solutions include proper use of technology, capacity building, and private participation in general and public-private partnership (PPP) in particular.

In immigration services, it is essential to provide good service to the public, in line with the principles of public service. However, in reality, many people still feel that they have not received optimal public service. This study addresses the issue of whether there is a direct and indirect influence of employee competence on citizen satisfaction, with the indirect influence using service quality as a mediating variable. This research employs a quantitative associative method with a population of applicants at the Surakarta Class I Checkpoint Immigration Office over one month, totaling 6236 individuals. A sample of 259 people was obtained using the Isaac and Michael table. Data collection was conducted using a questionnaire distributed via Google Forms to the applicants. The results were then analyzed using descriptive analysis, hypothesis testing with SPSS version 26, path analysis, and finally, the Sobel test. The results of the study indicate that employee competence directly affects service quality with a t-value (18.119) exceeding the t-table (1.969), but does not directly affect citizen satisfaction with a t-value (0.831) less than the t-table (1.969). Meanwhile, service quality directly affects citizen satisfaction with a t-value (10.156) greater than the t-table (1.969). Path analysis and the Sobel test also show that employee competence indirectly affects citizen satisfaction through service quality, with a Sobel test t-value of (8.87) greater than the t-table (1.969). Based on these results, it is concluded that there is no direct influence of employee competence on citizen satisfaction, but there is an indirect influence of employee competence on citizen satisfaction through service quality.