Objective: As the scale and importance of official development assistance (ODA) continue to grow, the need to enhance the effectiveness of ODA policies has become more critical than ever before. In this context, it is essential to systematically classify recipient countries and establish tailored ODA policies based on these classifications. The objective of this study is to identify an appropriate methodology for categorizing developing countries using specific criteria, and to apply it to actual data, providing valuable insights for donor countries in formulating future ODA policies. Design/Methodology/Approach: The data used in this study are the basic statistics on the Sustainable Development Goals (SDGs) published annually in the SDGs Report. The analytical method employed is decision tree analysis. Results: The results indicate that the 167 countries analyzed were classified into 10 distinct nodes. The study further limited the scope to the five nodes representing the most disadvantaged developing countries and suggested future directions for aid policies for each of these nodes.

The purpose of this research is to deeply examine the factors that support and hinder green economic growth in South Papua, with a specific focus on increasing awareness and capacity among local communities, developing sustainable infrastructure, and adopting clean technologies. This research utilizes a case study approach to uncover the dynamics and elements supporting the development of green economy in South Papua, particularly in Merauke Regency. Through surveys, in-depth interviews, and document analysis, data were gathered from various stakeholders, including government, communities, and the private sector. Sampling was done using purposive sampling method, ensuring the inclusion of respondents relevant to the research topic to provide a holistic understanding of the factors influencing green economy in the region. The research reveals that in Merauke Regency, the understanding of the concept of green economy among the community is still limited, highlighting the need for broader education and socialization. Factors such as government support, infrastructure availability, and community participation play a key role in driving green economic growth. However, challenges such as resource limitations and differences in perceptions among stakeholders highlight the complexity in implementing green economy. Therefore, holistic and collaborative policy recommendations need to be considered to strengthen support and effectiveness of sustainable development efforts in this region.

The research aims to examine East Nusa Tenggara (NTT) bank service digitalization innovations and examine several implications of bank service digitalization innovations. This research uses a qualitative approach with data collection techniques: in-depth interviews, documentation, and focused discussions. The key informants in this research were the board of commissioners, directors, division heads, and NTT bank employees. The findings of this research are, first, the existence of an existing/generic model in the operational, supporting, and monitoring fields of NTT banks. Second, there is an innovation model for digitizing services and efforts to popularize the digitization of NTT bank services to the government-private sector, including micro, small, and medium enterprises (MSMEs), religious institutions, educational institutions, students and students as well as the broader community to provide easy access to sources of financing for the community, Eliminate regional tax leakage, encourage the development of micro, small, and medium enterprises (MSMEs) and assisted village farmers/breeders, provide entrepreneurial opportunities for the community, namely as a digital agent for NTT bank, minimize fraudulent behavior (shirking) in credit distribution. Third, service digitalization innovation uses a contextual sociolinguistic approach because it incorporates local and global vocabulary such as Bpung Mobile, Bpung Farmer, Lopo Dia Bisa, and Bpinjam. Fourth, service digitalization innovation refers to OJK regulations regarding banking digital transformation contained in RP 21 and PBI number 23/26/2021. Fifth, conventional services (hybrid approach) still accompany the digitalization innovation model. Sixth, Bank NTT is in quadrant III, namely growth. Bank NTT continuously optimizes existing resources by taking advantage of opportunities to increase business growth and continues to mitigate threats into opportunities and strengths. The implications of the innovation in digitizing NTT bank services include updating standard operating procedures (SOP), changing corporate culture from Flobamora to Bintang, and accelerating the increase in human capital capacity. The implications of research on bank management refer to the innovation of procurement of new IT systems. Banks can increase their attention to service quality and maintain customer trust to maintain the quality of digital banks among customers. Moreover, with post-COVID-19 conditions that require people to make digital transactions. With the changes in the financial industry towards digitalization, it is necessary to strengthen risk management in financial service institutions. The implications of the research results for policymakers need to be considered in the transformation towards digital banking related to equitable internet access in Indonesia, cybersecurity, and employment. Recommendations for future research are the importance of studying the determinants of digital service innovation in bank services, such as transformational leadership style, good corporate governance, and organizational commitment.

COVID was initially detected in Wuhan City, Hubei Province, People's Republic of China, in late 2019, as reported by researchers. Subsequently, it rapidly disseminated to numerous nations at the beginning of 2020, ultimately manifested as a pandemic with worldwide prevalence. Regarded as one of the most severe pandemics in documented human history, this outbreak resulted in deaths and infection over a quite millions of individuals globally. Due to its airborne nature, the coronavirus can be transmitted through actions such as coughing, sneezing, talking, and similar activities. Enclosed spaces lacking sufficient airflow are more likely to facilitate the spread of air borne diseases. Wearing a face mask that can provide protection against airborne pollutants, considered as Standard Operation Procedures (SOPS) for COVID-19. It is crucial to monitor the implementation of preventive measures both within and outside the building or workplace in order to prevent the transmission of COVID-19. The main objective of this project is to develop a face mask and social distance detector. You Only Learn One Representation (YOLOR) was implemented as a most advanced end-to-end target identification approach to develop the proposed system. An online available facemask dataset was utilized. The developed system can track individuals wearing masks in real time and can also identify and highlight persons with a rectangular box if their social distance is violated. This proposed interactive framework enables constant monitoring both internally and externally, thereby enhancing the capacity to identify offenders and ensure the safety of all individuals involved.

One functional class is described in terms of one-sided modulus of continuity and the modulus of positive (negative) variation on which there
is a uniform convergence of the truncated cardinal Whittaker functions.