ALIFAH SURYA GAMIYANTI, NIM. 13651057 (2017) CLUSTERING DATA BAKTERI ACETOBACTERACEAE BERDASARKAN CIRI-CIRI DAN SPESIES MENGGUNAKAN FUZZY C-MEANS. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.
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Text (CLUSTERING DATA BAKTERI ACETOBACTERACEAE BERDASARKAN CIRI-CIRI DAN SPESIES MENGGUNAKAN FUZZY C-MEANS)
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Text (CLUSTERING DATA BAKTERI ACETOBACTERACEAE BERDASARKAN CIRI-CIRI DAN SPESIES MENGGUNAKAN FUZZY C-MEANS)
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Abstract
Bacteria are the most numerous organisms. Bacteria have hundreds of thousands of species that live on land, oceans and extreme places. A large number of bacterial species cause researchers in the field of Biology to have difficulty in classifying bacteria based on similarity or proximity characteristics. One of the bacteria that has many species and characteristics of Acetobacteraceae bacteria. Bacteria Acetobacteraceae is an acidic bacteria that has the ability to oxidize alcohol and sugars, in particular oxidizing ethanol to acetic acid. Bacteria Acetobacteraceae is divided into 15 genera, and each genus is divided into several species or species that have characteristics or characteristics that differ from one type to another. Acetobacteraceae bacteria data were obtained from Bergey's Manual of Systemic volume 2 book. Classification of Acetobacteraceae bacteria data based on the characteristics and species is done by fuzzy c-means clustering method. Fuzzy c-means is a data clustering technique where the existence of each data point in a cluster is determined by the degree of membership. Fuzzy c-means method is used in the process of clustering data with the first step is to change the data characteristics and species into numbers or numerization, then calculate the cluster center of the data already in numerisasi. The next step is to calculate the objective function and the change in the partition matrix. The output of clustering using fuzzy c-means is the cluster pattern of Acetobacteraceae bacteria.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | Dr. Shofwatul ‘Uyun, S.T., M. Kom |
| Uncontrolled Keywords: | bacteri data Acetobacteraceae, clustering, fuzzy c-means |
| Subjects: | Tehnik Informatika |
| Divisions: | Fakultas Sains dan Teknologi > Teknik Informatika (S1) |
| Depositing User: | Miftahul Ulum [IT Staff] |
| Date Deposited: | 23 Nov 2017 09:56 |
| Last Modified: | 23 Nov 2017 09:56 |
| URI: | http://digilib.uin-suka.ac.id/id/eprint/28474 |
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