This research investigates the relationship between the variables of public service reform (PSR) and bureaucratic revitalization and the relationship between digital leadership (DL) and bureaucratic revitalization. The research method used in this research is quantitative survey research which aims to determine the relationship between two or more variables. The research method for this research is quantitative associative, the population of this study is senior immigration officers. The data analysis method uses structural equation modeling (SEM) partial least squares (PLS), the respondents for this study were 634 senior immigration office employees who were determined using the simple random sampling method—non probability sampling, the questionnaire was designed to contain statement items using a 7 point Likert scale. A closed questionnaire is a list of questions or statements that are equipped with multiple answer choices expressed in scale form. The Likert scale used in this research is (1) strongly disagree, (2) disagree, (3) quite disagree, (4) neutral, (5) quite agree, (6) agree, (7) strongly agree. Data processing in this research used SmartPLS software. The independent variables of this research are digital leadership and public service reform and the dependent variable is bureaucratic revitalization. The stages of data analysis in this research are the outer model test which includes convergent validity, discriminant validity and composite reliability as well as inner model analysis, namely hypothesis testing. The results of this research show that public service reform has a positive and significant relationship to bureaucratic revitalization and digital leadership has a positive and significant relationship to bureaucratic revitalization. This research implies that leaders focus on engaging, using, and handling the uncertainty of emerging technologies, digital tools, and data, leaders to support bureaucratic revitalization, the immigration department must implement digital leadership, immigration leaders should encourage the use of digital platforms in their organizations, support and facilitate digital transformation. The immigration department should increase the revitalization of the bureaucracy, the immigration department should carry out public service reforms. Public services are to be good if they fulfill several principles of public interest, legal certainty, equal rights, balance of rights and obligations, professionalism, participativeness, equality of treatment/non-discrimination, openness, accountability, facilities and special treatment for vulnerable groups, timeliness, speed, convenience and affordability.

The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required the same memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data is used to verify the performance of the proposed RMA.

The aim of this research is to determine the incidence of socioeconomic variables in migration flows from the main countries of origin that form part of the international South-North migration corridor, such as Mexico, China, India, and the Philippines, during the 1990–2022 period. The independent variables considered are GDP per capita, unemployment, poverty, higher education, and public health, while the dependent variable is migration flows. An econometric panel data model is implemented. The tests conducted indicate that all variables have an integration order of I (1) and exhibit long-term equilibrium. The econometric models used, Dynamic Ordinary Least Squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS), reveal that unemployment and poverty had the strongest influence on migration flows. In both models, within this international migration corridor, GDP per capita, higher education, and health follow in order of importance.

Tourism is one of the important sectors that support Indonesia’s economic growth. The tourism sector itself plays a strategic role in increasing the country’s foreign exchange. However, during the Covid-19 pandemic, tourism became one of the most affected sectors. Electronic visa on arrival (e-VOA) is a form of digital transformation in immigration services offered by the Indonesian government to increase the number of tourist arrivals during the recovery of the national economy, especially in the tourism sector, after the Covid-19 pandemic. This study provides an in-depth insight into how e-VOA functions as a digital transformation tool in the immigration and tourism sectors. By exploring the impact of e-VOA implementation, this article contributes to the understanding of how digitalisation can improve the efficiency of administrative processes and support the recovery of the tourism sector in post-pandemic Bali. This study uses qualitative approaches and methods with descriptive analysis techniques to create an objective description of a situation through numbers or statistical data. The results of this study show that e-VOA services effectively contribute to an increase in the number of foreign tourists in Bali. It also has a positive impact on the economic growth of tourism-related businesses in Bali.