Abstract

Poverty is social gap problem for some people with below average income level but in Pringsewu district the poverty rate is significantly decreased so it is expected to increase the potential of Pringsewu region to be better, in increasing the potential of the region it needs a system that is expected to assist in determination of poverty level in sub district in Pringsewu by data clustering and ranking from every subdistrict in Pringsewu Regency using SAW method. Therefore, we are interested to build an application of Poverty Grouping in Pringsewu region in the form of Poverty Index of the last few years, existing data is expected to be a reference to increase the potential of the area by reducing the poverty rate every year. It is expected that the data obtained can be a reference of the government in reducing poverty level in subdistrics in Pringsewu District.

Keywords:
Poverty Ranking (information retrieval) Poverty rate Index (typography) Government (linguistics) Cluster analysis Geography Socioeconomics Statistics Economics Economic growth Computer science Mathematics

Metrics

31
Cited By
8.48
FWCI (Field Weighted Citation Impact)
46
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Data Mining and Machine Learning Applications
Physical Sciences →  Computer Science →  Information Systems

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