Leveraging big data for economic stability: a dashboard for ASEAN's future growth / Ibrahim Norfiza ... [et al.]

• Main Authors: Ibrahim, Norfiza, Aziz, Nurul Athirah, Abu Seman, Azmi, Abdul Wahab, Nadia, Osman, Aznoora, Md Ilyas, Siti Sarah
• Format: Article
• Language: English
• Published: UiTM Cawangan Perlis 2024
• Subjects: Electronic data processing. Information technology. Knowledge economy. Including artificial intelligence and knowledge management
• Online Access: https://ir.uitm.edu.my/id/eprint/103722/1/103722.pdf; https://ir.uitm.edu.my/id/eprint/103722/; https://jcrinn.com/index.php/jcrinn
• Institution: Universiti Teknologi Mara

The economy is expected to decline. All countries aspire for economic stability because it can enhance a country's gross domestic product(GDP). Nations must thoroughly examine their economic realities in order to adopt strategic economic policies that foster growth and attract investment. The present dashboard only displays the inflation rate and excludes other essential economic indicators such as total economic output, current GDP rate, currency rates, and unemployment rate. The indicators were presented graphically on a separate platform without a detailed explanation, which could lead to misinterpretation. Investors may make an incorrect evaluation, leading to a financial loss. The major purpose of this project is to create a dashboard that appropriately assesses Southeast Asian states' economic stability. The primary goals of this research are to determine the techniques and requirements of an economic stability indicator dashboard for ASEAN countries, to create a console utilizing Big Data methods and to assess the usefulness of this system. This study employs the Rapid Application Development paradigm, which was chosen for its ability to efficiently build a system within a small time frame. The objectives are met successfully within the specified stages through Technology Acceptance Model. T here are four dimensions were evaluated namely Perceived Ease of Use, Perceived Usefulness, Attitude and Intention to Use. The participants comprised both salaried Malaysians from various industries and self-employed people. The system's average score for all dimensions is 4.76 shows that the dashboard can help consumers make better decisions. This study is suggested to has prediction and machine learning to be used as a prediction model for future implementation.