Papua, one of the provinces in Indonesia, is recognized for its limited infrastructure and high poverty rates. This limitation undoubtedly emphasizes the government’s special attention toward augmenting foreign and domestic investments by expanding industrial sectors to absorb more labor, thereby aiming to enhance the region’s economic performance. The focus of the study seeks to assess the extent to which foreign and domestic investments, industrial employment, and the proliferation of industries in Papua contribute to increasing the Gross Development Product (GDP) and reducing poverty. By employing secondary data from 2016 to 2022 and utilizing the Regression Data Panel method, it encompasses 29 districts. The findings reveal that domestic investment, employment in the industrial sector, and the number of industries significantly influence poverty rates. However, as conclusion, foreign investment, surprisingly, demonstrates no substantial impact on economic performance. This unexpected result might be attributed to issues linked with the inadequate quality of financial performance, which doesn’t align with the available investment funds. Utilizing the analytical network process (ANP), the study outlines two primary strategies. The first involves prioritizing investment expansion by focusing on both domestic and foreign investments. The second strategy emphasizes industrial revitalization through augmenting the number of industries and enhancing labor participation in the industrial sector.
This study aims to evaluate the influence of population dependency ratio on the economic growth of Bangladesh, India, and Pakistan, the three members of the South Asian Association for Regional Cooperation (SAARC). The study covers the time from 1960 to 2021. It also analyses in detail how population aging and the youth dependency ratio affects the development of certain sectors, including industry, services and agriculture. This study uses panel data to determine the influence of population dependency ratios on economic growth. To estimate this effect, we use the Pooled Mean Group/Autoregressive Distributed Lag (PMG/ARDL) technique. Based on the results obtained from the ARDL analysis indicate the presence of a long-term relationship among these variables. These discoveries align with prior empirical research conducted by Lee and Shin, Mamun et al., and Rostiana and Rodesbi. Furthermore, the findings suggest that an increase in the old age population dependency ratio positively influences economic growth within these nations. The long-term relationship findings pertaining to the old and young dependency ratio and economic growth corroborate the conclusions of Bawazir et al., who proposed that the old population dependency ratio exerts a favorable impact, while the young population has an adverse effect on economic growth. Originality: This research focused on the population dependency ratio, a pivotal demographic metric that gauges the proportion of individuals relying on support (including children and the elderly) compared to those of working age. This investigation particularly explores the interconnection between the population dependency ratio and sectoral development, an essential aspect given that various sectors make distinct contributions to economic advancement. Examining how population dynamics affect sectoral development yields valuable insights into the overall economic performance of Pakistan, India, and Bangladesh.
Improving the practical skills of Science, Technology, Engineering and Mathematics (STEM) students at a historically black college and university (HBCU) was done by implementing a transformative teaching model. The model was implemented on undergraduate students of different educational levels in the Electrical Engineering (EE) Department at HBCU. The model was also extended to carefully chosen high and middle schools. These middle and high school students serve as a pipeline to the university, with a particular emphasis on fostering growth within the EE Department. The model aligns well with the core mission of the EE Department, aiming to enhance the theoretical knowledge and practical skills of students, ensuring that they are qualified to work in industry or to pursue graduate studies. The implemented model prepares students for outstanding STEM careers. It also increases enrolment, student retention, and the number of underrepresented minority graduates in a technology-based workforce.
This research was conducted using a survey research method to investigate the influence of Artificial Intelligence (AI) on Nigerian students' academic performances in tertiary institutions. Nigerian tertiary institutions have an estimated population of about 2.5 million students across the universities, polytechnics, monotechnics, and colleges of education. A sample size of 509 was used. The researchers adopted an online questionnaire (Google Form) to administer questions to respondents across Nigeria to elicit responses from the respondents bordering on their awareness and the use of AI and its attendant impacts on their academic performance. Five research objectives were raised for the proper investigation of this study. From the findings of the study, the researchers found that the majority of Nigerian students use AI and that AI has positive impacts on the educational performance of Nigerian students. It was also found that Nigerian students have training on the use of AI for educational purposes and that they are more familiar with Snapchat AI and ChatGPT. Conclusively, AI is useful to students in the sense that it enhances their knowledge of their courses, improves their learning and speaking skills, and helps them to have a quick understanding of their course by way of simplifying technical aspects of their courses. The researchers therefore recommend as follows: Nigerian tertiary institutions should formally train students as well as teachers on the use of AI for academic purposes so that they can understand the ethical implications of the use of AI. Using AI for writing could be interpreted to mean examination malpractice, and this should not be condoned in the educational sector; however, at the moment, a small number of students used AI for examinations. Albeit, the appropriate use of AI should be fully integrated into Nigerian tertiary institutions' curricula.
This article aims to elucidate governance primarily from the perspective of collaboration and leadership in managing disasters. This article studies the case of Indonesia, a country with frequent and complex nature of disasters, located on the Pacific Ring of Fire to analyze its disaster management system and draw out implications from its experience. The method used is a qualitative comprehensive and systematic review from national and international earthquake occurrences. The finding is that Indonesia is simultaneously carrying out disaster management which is not contradictory but complementary. The importance of collaboration is imposed and recommendations are offered on rectifying collaborative activities’ value. Modern leadership strategies suggest that acquire their power from effective strategies and transformational power rather than standard operating procedures. This paper provides lessons on how to organize earthquake management through aspects of collaboration and leadership effectively. The author suggests optimizing the potential of the community by providing special assistance to increase disaster management efforts.
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