Utilising Big Data Analytics in the E-Government Health Sector
| Autor: | U. Nwogu, C. A. N. Nwachukwu, A. Cassia, U. E. Omenka, P. U. Sunday, R.U. Iheruo |
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| Rok vydání: | 2022 |
| Zdroj: | Science View Journal. 3:206-214 |
| ISSN: | 2734-2638 2734-2646 |
| DOI: | 10.55989/hzdc4338 |
| Popis: | The world has witnessed massive technological improvements in the Information Technology (IT) sector, giving rise to unprecedented IT penetration into every facet of life and daily living. It has affected the way we live and interact, the way businesses are conducted, and most especially how the government makes decisions that affect its citizenry. Presently, government officials deploy IT techniques in their decision-making process to reach the ever-growing needs of their populace. The traditional approach to large data processing is proving difficult. Hence, the dawn of Big Data Analytics, a phenomenon that describes the processing of large volumes of datasets, being generated at a very high velocity, coming in various forms, and are largely unstructured. This paper examines literatures on Big Data Analytics and its application in e-government. A prototype framework which is divided into two will be proposed for its application. The first section will have the Hadoop infrastructure deployed for distributed storage in clusters, while the second section used a machine learning software – Waikato Environment for Knowledge Analysis (WEKA) for data mining. Finally, the different data mining algorithms provided by WEKA was explored and used in analyzing medical records obtained from the UCI online repository to demonstrate the data analysis of the proposed prototype. From the results of the analysis, J48 algorithm was used to build prediction trees, to ascertain patterns that determine the likelihood of citizens having breast cancer, and to generate predictions rules that will help in curbing or detecting breast cancer early among the populace. |
| Databáze: | OpenAIRE |
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