Hilmi Taufiqurohman, - (2022) ANALISIS KLASTER DENGAN METODE ALGORITMA ENSEMBLE BASED FUZZY GUSTAFSON KESSEL. S1 thesis, Universitas Pendidikan Indonesia.
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Abstract
Cluster analysis is a technique for grouping several objects into groups according to certain characteristics. Cluster analysis will allocate a group of individuals to independent groups so that individuals in the group are similar to one another, while differing in characteristics from those outside the group. Fuzzy Clustering is a method of cluster analysis by considering the level of membership which includes fuzzy sets as a weighting basis for grouping. This method is a development of the data clustering method with fuzzy weighting. Fuzzy Gustafson-Kessel grouping is the development of Fuzzy C-Means (FCM). The matrix forming value in this grouping method is called the adaptive distance norm which is updated in each iteration. Thus, this grouping is able to better adjust the geometric shape of the right membership function for a data set. The purpose of this study was to classify districts and cities in West Java using the Gustafson Kessel fuzzy ensemble method. By using investment realization data, it is found that the fuzzy Gustafson Kessel method with the number of clusters 3 is the most optimal.
| Item Type: | Thesis (S1) |
|---|---|
| Additional Information: | ID SINTA Donsen Pembimbing: Dewi Rachmatin : 5975775 Fitriani Agustina : 5981275 |
| Uncontrolled Keywords: | Analisis Klaster Fuzzy, Fuzzy Gustafson Kessel, Realisasi Investasi |
| Subjects: | L Education > L Education (General) Q Science > QA Mathematics |
| Divisions: | Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Jurusan Pendidikan Matematika > Program Studi Matematika (non kependidikan) |
| Depositing User: | Hilmi Taufiqurohman |
| Date Deposited: | 23 Sep 2022 07:56 |
| Last Modified: | 23 Sep 2022 07:56 |
| URI: | http://repository.upi.edu/id/eprint/80961 |
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