“Rwanda”Search All-EnPress Publisher LLC.

Jan 7, 2025

Preliminary approach of oil spill model: A hindcasting with in situ data and numerical model in Balikpapan Bay, Indonesia

Oil spills (OS) in waters can have major consequences for the ecosystem and adjacent natural resources. Therefore, recognizing the OS spread pattern is crucial for supporting decision-making in disaster management. On 31 March 2018, an OS occurred in Balikpapan Bay, Indonesia, due to a ship’s anchor rupturing a seafloor crude oil petroleum pipe. The purpose of this study is to investigate the propagation of crude OS using coupled three-dimensional (3D) model from DHI MIKE software and remote sensing data from Sentinel-1 SAR (Synthetic Aperture Radar). MIKE3 FM predicts and simulates the 3D sea circulation, while MIKE OS models the path of oil’s fate concentration. The OS model could identify the temporal and spatial distribution of OS concentration in subsurface layers. To validate the model, in situ observations were made of oil stranded on the shore. On 1 April 2018, at 21:50 UTC, Sentinel-1 SAR detected an OS on the sea surface covering 203.40 km². The OS model measures 137.52 km². Both methods resulted in a synergistic OS exposure of 314.23 km². Wind dominantly influenced the OS propagation on the sea surface, as detected by the SAR image, while tidal currents primarily affected the oil movement within the subsurface simulated by the OS model. Thus, the two approaches underscored the importance of synergizing the DHI MIKE model with remote sensing data to comprehensively understand OS distribution in semi-enclosed waters like Balikpapan Bay detected by SAR.

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Dec 10, 2024

Named entity recognition in government domain: A systematic literature review

Named Entity Recognition (NER), a core task in Information Extraction (IE) alongside Relation Extraction (RE), identifies and extracts entities like place and person names in various domains. NER has improved business processes in both public and private sectors but remains underutilized in government institutions, especially in developing countries like Indonesia. This study examines which government fields have utilized NER over the past five years, evaluates system performance, identifies common methods, highlights countries with significant adoption, and outlines current challenges. Over 64 international studies from 15 countries were selected using PRISMA 2020 guidelines. The findings are synthesized into a preliminary ontology design for Government NER.

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Sept 2, 2024

Evaluating how and why the Government of Rwanda failed to achieve middle-income status (MICS) in 2020: Lessons for other African countries

In the 1960s, many East Asian Tiger countries, such as Taiwan, Malaysia, China, etc., faced unfavourable socio-economic conditions like those facing many African countries such as Rwanda. For example, in the 1960s, Singapore was classified as an undeveloped country, with its GDP per capita standing at less than $320. However, all these countries managed to reach a development level like that of Western and North American countries (such as the U.S. and Canada), within a space of less than 15 years. Today, Singapore’s GDP per capita has risen to an incredible $84,501, making it the sixth highest GDP per capita in the world. With Vision 2020, President Kagame promised that Rwanda, which he referred to as “the African lion”, would cruise faster to the middle-income country status faster than Singapore and other middle income status countries, most of which are in East-Asia in less than 20 years. Thirteen years after the introduction of Rwanda’s Vision 2020, President Kagame dashed off the Wall Street Journal and other western media which often referred to Rwanda’s economic development as “the economic tiger of Africa” in his 2013 famous statement as follows: “There is a view that development is a marathon, not a sprint. We do not agree. Development is a marathon that must be run at a sprint. In our pursuit of progress, we have, of course, looked to East Asia’s so-called “tiger” economies for inspiration. But Africa’s experience is unique, and we must now define our own destiny. So, while being described as an “African tiger” is a welcome recognition of how far Rwanda has come, perhaps it isn’t quite right. After all, our continent has its own big cat. Step forward, the new lions of Africa.”. To achieve this objective between 2000 and 2020, Rwanda’s GDP per capita needed to increase from 254.94 USD (2000) to $1240 (in 2020), and the GDP growth rate was to grow consistently between 7% and 10% for a period of 20 years (2000–2020). The objective of this article is to critically analyse how the Government of Rwanda failed to achieve its promise of achieving a middle-income status (MICS) between 2000 and 2020. In 2000 the Rwandan president Paul Kagame launched Rwanda’s Vision 2020. This was a long-term framework for Rwanda’s development in 20 (i.e., 2000–2020). The idea behind Rwanda’s leadership was to imitate whatever Singapore did to become a developed country in just 15 years after its independence in 1965. Blatantly stated, President Paul Kagame wanted to turn his country into the Singapore of Africa. The IMF states that “Vision 2020 was the longer-term socio-economic development framework that sought to transform Rwanda into a middle-income country by 2020”. There is no doubt that Rwanda has made some developmental strides through the implementation of Vision 2020 as an instrument for operationalisation for the Singaporean-modelled developmental state over the past 20 years and has succeeded in some areas. However, the Government of Rwanda has failed in many areas and has failed to achieve the prestigious MICS in 2020. Therefore, among the many gaps in the current literature that this research seeks close is to find out what were some of the accomplishments that Rwanda’s Vision 2020 was unable to achieve? Why did the Government of Rwanda fail to achieve middle-income status within 20 years? What insights can other developing countries gain from Rwanda’s Vision 2020 experience? This study is a significant contribution to the current theoretical knowledge as it sheds light on the reasons behind the Government of Rwanda’s failure to achieve middle-income country status in 2020, a topic that has been largely ignored by the Government’s documents and the media. Despite Rwanda’s Vision 2020, there has been no scientific study to date that has attempted to deal with this topic. Therefore, this study, titled “Why the Government of Rwanda failed to achieve middle-income status (MICS) in 2020” is likely the first of its kind. By addressing

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Aug 29, 2024

Development of a data governance framework of MOOC providers in Indonesia

Massive open online courses (MOOCs) are intentionally designed to be easily accessible to many learners, regardless of their academic level or age. MOOCs leverage internet-based technology, allowing anybody with an internet connection to have unrestricted access, regardless of their location or time limitations. MOOCs provide a versatile and easy opportunity for acquiring top-notch education, enabling anyone to learn at their preferred speed, free from limitations of time, cost, or geographical location. Given the advantages they offer, MOOCs are a valuable method for improving the quality and availability of education in Indonesia. Following the outbreak of the COVID-19 pandemic, colleges and institutions have implemented the establishment of digital campuses. One important characteristic of these digital campuses is that they prioritize processes but overlook data and lack standardized standards. The problems and fundamental causes include challenges related to the comprehensive information architecture. The main factor contributing to this challenge is the absence of uniform and well-defined information standards. The existing connectivity and data exchange mechanisms in several schools are poor, leading to substantial data discrepancy among various departments due to the limited content of the fundamental data utilized. Moreover, the absence of clear information about the reliable source of data exacerbates the problem. The main objectives of data governance are to improve data quality, eliminate data inconsistencies, promote extensive data sharing, utilize data aggregation for competitive benefits, supervise data modifications based on data usage patterns, and comply with internal and external regulations and agreed-upon data usage standards. The aim of this project is to create a data governance framework that is customized to the specific conditions in Indonesia, with a specific emphasis on MOOC providers. The researcher chose design science research (DSR) as the research paradigm as it can successfully tackle relevant issues linked to the topic by creating innovative artefacts about the data governance framework for MOOC providers in Indonesia. This research highlights the necessity and significance of implementing a data governance framework for MOOC providers in Indonesia, hence increasing their awareness of this requirement. The researchers incorporated components from the data management body of knowledge (DMBOK) into their data governance framework. This framework includes ten components related to data governance, which are further divided into sub-components within the MOOC providers’ framework.

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Jun 25, 2024

Impact of exchange rates, Inflation, foreign direct investment, government spending, and economic openness on exports, imports, and economic growth in Indonesia

Globalization and economic integration have an impact on increasing trade volume and economic growth in various countries, especially those that are open in their economies. This situation also provides ease of capital mobility between countries, which makes investment not only rely on domestic investment but also on foreign direct investment. Exchange rates and inflation also affect export growth, imports, and economic growth. The purpose of this study is to determine the effect of exchange rate, inflation, foreign direct investment, government expenditure, and economic openness on export and import growth. This study used time series data during the period 1980–2021, sourced from UNCTAD, ASYB, and Indonesian Central Bank (BI). The analysis model used is multiple linear regression with the help of EViews software, which first tests classical assumptions so that the regression results are Best Linier Unbiased Estimator (BLUE). The results show that foreign direct investment and government spending can significantly increase the rate of exports and imports. Meanwhile, the depreciating rupiah against the US dollar cannot encourage an increase in both exports and imports. Furthermore, foreign direct investment, government spending, and economic openness can significantly increase economic growth. The other variables, net exports and inflation, have no effect on Indonesia’s economic growth rate.

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