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|Title:||Ranking and Hotspot Detection Methods on Infant Health for Districts in Java, Indonesia: E-Governance Micro Tools|
Myers, Wayne L.
Infant Health Indicators
Upper Level Set Scan Statistics
|Abstract:||As the Academia stakeholder, this paper shares the method and theory which extend the understanding of Electronic Governance. The purpose of this research is to obtain the ranking of infant health in Java based on five indicators and three indicators. These indicators or variables are number of infant deaths (infd), number of people in poverty (pov), number of infants with low birth weight (lbw), number of deliveries in absence of health personnel (abhp), and average education shortfall of women (avedsf). All variables are district level aggregates. Besides ranking, hotspots based on those indicators are also detected by ULS hotspot detection method, while rankings are computed based on ORDIT, implemented in R software. Rankings of the districts based on 5 (all) indicators and 3 indicators (infd, pov, lbw) are obtained. Also, ranking is obtained based on salient scaling of 5 indicators and salient scaling of 3 indicators. According to those results, the most severe districts are districts 87 and 90, while the least severe districts are districts 73, 31, and 35. There are many districts in the hotspot area as the results of the ULS hotspot detection. Districts 87, 90, 47, 58, 83, 44, and 45 are the worst areas of infant health. This result is important information for the government, especially the Health Department to make decisions for the improvement of health programs. The methods can be used as a micro tool to extend the function and understanding of egovernance.|
|Appears in Collections:||Proceedings Collection|
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