Rabu, 07 Maret 2018


Retno Tri Vulandari1, Kumaratih Sandradewi2, Bebas Widada3,Sapto Nugroho4

124Department of Informatics, STMIK Sinar Nusantara
3Department of Information System, STMIK Sinar Nusantara

Human development progress in Central Java. It is characterized by a continued rise in the human development index (HDI) of Central Java. HDI is an important indicator for measuring success in the effort to build the quality of human life. HDI explains how residents can access the development results in obtaining a long and healthy life, knowledge, education, decent standard of living and so on. HDI is affected by four factors, namely: life expectancy, expected years of schooling, means years of schooling, and expenditure per capita. Currently the Central Bureau of statistics do grouping HDI, using calculation formula then known how the value HDI each county or city in Central Java. In this research will be made to the classification of county or city in Central Java based on the HDI be high, middle, and under estimate area.
In this research used cluster analysis. Cluster analysis is a multivariate technique which has the main purpose to classify objects based on their characteristics. Cluster analysis classifies the object, so that each object that has properties similar to be clumped into a single cluster (Group). One of the cluster analysis method is K-Means. The result of this research, there are three group, high estimate area, middle estimate area, and under estimate area. The first group or the under estimate area contained 12 members, namely Cilacap, Purbalingga, Purworejo, Wonosobo, Grobogan, Blora, Rembang, Pati, Jepara, Demak, Pekalongan, and Brebes. The second group or the middle estimate area contained 8 members, namely Banjarnegara, Kebumen, Magelang, Temanggung, Wonogiri, Batang, Pemalang, and Tegal. The third group or the high estimate area contained 11 members, namely Banyumas, Kudus, Boyolali, Klaten, Sukoharjo, Karanganyar, Sragen, Semarang, Kendal, Surakarta, and Salatiga.

Keywords: Inverse Distance Weighted, K-Means, The Human Development Index.

Tidak ada komentar:

Posting Komentar