Sajidah, Annisa (2016) Pengelompokan Provinsi di Indonesia Berdasarkan Indikator Kesejahteraan Rakyat dengan Metode cmeans dan fuzzy c-means clustering. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Permasalahan sosial yang terjadi di Indonesia memberikan
dampak yang cukup serius kepada kesejahteraan rakyat di suatu
daerah. Kesejahteraan rakyat berkaitan dengan tujuan
pembangunan nasional namun permasalahan yang ada adalah
tidak mampunya pemerintah dalam memilah permasalahan di
setiap daerah sehingga pembangunan yang dilakukan dapat
merata. Penelitian ini bertujuan memberikan informasi kepada
pihak terkait dalam pembangunan nasional agar memberikan
penanganan yang sesuai kepada provinsi yang dianggap kurang
sejahtera berdasarkan tingkat homogenitasnya dengan metode
pengelompokan c-means dan fuzzy c-means. Pengelompokan
tersebut memberikan hasil bahwa dengan c-means memberikan
hasil lebih baik dibandingkan dengan fuzzy c-means clustering
berdasarkan nilai icd rate terendah nya dimana cluster optimum
yang terbentuk ada sebanyak 2 cluster yang dilihat dari nilai
pseudo f-statistics tertinggi. Hasil c-means memberikan hasil
karakteristik provinsi papua membutuhkan perhatian lebih
dibandingkan provinsi lainnya dari segala dimensi. Sedangkan
dengan fuzzy c-means kedua kelompok mampu meberikan
karakteristik tersendiri sesuai dengan komponen utama yang
membentuknya.
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Social problems that occur in Indonesia provide a fairly serious
impact to the welfare of people in that area. Welfare indicators
concerned with national development goals but the problem is the
inability of the government for sorting out the problems in each
area so that development can be done evenly. This study aims to
provide information to stakeholders in national development in
order to provide appropriate treatment to provinces that are
considered less prosperous based on the level of homogenity by
the method of grouping c-means and fuzzy c-means. Grouping by
fuzzy c-means providing better results than with c-means
clustering based on the value icd-rate cause it is the lowest rate in
which the optimum cluster is formed there were two clusters are
seen from the pseudo highest f-statistics. The result by c-means
provide the characteristics of Papua province needs more
attention compared the other provinces from all dimensions.
While the fuzzy c-means two groups that gave the distinct
characteristics in accordance with the principal components of
dimensions that make it up.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 519.53 Saj p |
| Uncontrolled Keywords: | C-Means Clustering, Fuzzy C-Means Clusering, Icd rate, Indikator Kesejahteraan Rakyat. Pseudo F-Statistics |
| Subjects: | Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics) |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Tondo Indra Nyata |
| Date Deposited: | 23 Feb 2018 04:11 |
| Last Modified: | 27 Dec 2018 07:31 |
| URI: | http://repository.its.ac.id/id/eprint/51350 |
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