BibTex Citation Data :
@article{Medstat8287, author = {Triastuti Wuryandari and Abdul Hoyyi and Dewi Kusumawardani and Dwi Rahmawati}, title = {IDENTIFIKASI AUTOKORELASI SPASIAL PADA JUMLAHPENGANGGURAN DI JAWA TENGAH MENGGUNAKAN INDEKS MORAN}, journal = {MEDIA STATISTIKA}, volume = {7}, number = {1}, year = {2014}, keywords = {}, abstract = { Unemployment is caused by the work force or job seekers are not proportional with the number of existing jobs. Unemployment is often a problem in the interconnected economy due to unemployment, productivity and income will be reduced. The number of unemployed in an are a expected to be affected by unemployment in the surrounding area. This is made possible because of the proximity factor or adjacency between regions, it is estimated that there are linkages to the regional unemployment rate. To determine the relationship between regional linkages used Moran’s Index method. The number of unemployed in Central Java, obtained Moran’s Index value = 0.0614. Moran's Index values in the range 0 < I ≤ 1 indicating the presence of spatial autocorrelation is positive but small correlation can be said because of near zero, orit can be concluded that the similarity between the district does not have a value or indicate that unemployment among districts in Central Java has a small correlation. Keywords : Unemployment, Moran’s Index, Central Java, Autocorrelation, Spatial }, issn = {2477-0647}, pages = {1--10} doi = {10.14710/medstat.7.1.1-10}, url = {https://ejournal.undip.ac.id/index.php/media_statistika/article/view/8287} }
Refworks Citation Data :
Unemployment is caused by the work force or job seekers are not proportional with the number of existing jobs. Unemployment is often a problem in the interconnected economy due to unemployment, productivity and income will be reduced. The number of unemployed in an are a expected to be affected by unemployment in the surrounding area. This is made possible because of the proximity factor or adjacency between regions, it is estimated that there are linkages to the regional unemployment rate. To determine the relationship between regional linkages used Moran’s Index method. The number of unemployed in Central Java, obtained Moran’s Index value = 0.0614. Moran's Index values in the range 0 < I ≤ 1 indicating the presence of spatial autocorrelation is positive but small correlation can be said because of near zero, orit can be concluded that the similarity between the district does not have a value or indicate that unemployment among districts in Central Java has a small correlation.
Keywords: Unemployment, Moran’s Index, Central Java, Autocorrelation, Spatial
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