CLUSTERING DATA PASIEN MENGGUNAKAN FUZZY C-MEANS DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING

ROSALIA SUSILOWATI, NIM. 08650080 (2012) CLUSTERING DATA PASIEN MENGGUNAKAN FUZZY C-MEANS DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING. Skripsi thesis, UIN SUNAN KALIJAGA.

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Abstract

During these days, system development only includes input, view and report in general. From the medical record database at Rumah Sakit Jogja, informations which can be obtained just the percentage of male and female patient, the more specific information which can be retrieved has not been done. With the completeness of informations from the database, so that can used as consideration of decision making by the authorities. These informations can be obtained from analysis and processing available data, one of methods for retrieving information is clustering technique. Domain data of this research is patient data. Before the data clustered, first performed prepocessing which includes naming standardization, changing form or data numerisation and normalization. During the clustering process, the used algorithms are Fuzzy C-Means (FCM) and Agglomerative Hierarchical Clustering(AHC). The purpose of the use of these two algorithms is to determine the most appropriate algorithm and the faster processing time for patient data cases. Processing time required to perform clustering using FCM Algorithm relatively faster than AHC algorithm. For small volume data, FCM algorithm's iteration is more than AHC algorithm, however, the clustering result of FCM algorithm is easier to interpreted than AHC algorithm. If seen from the clustering result visualization, cluster pattern of FCM algorithm is more clustered based on three variables. So, for medical records as domain of this research, the more precise algorithm is the Fuzzy C-Means (FCM) algorithm. Keywords: Agglomerative Hierarchical Clustering, Clustering, Fuzzy C-Means,Patient Data

Item Type: Thesis (Skripsi)
Subjects: Tehnik Informatika
Divisions: Fakultas Sains dan Teknologi > Teknik Informatika (S1)
Depositing User: Miftahul Ulum [IT Staff]
Date Deposited: 17 Jun 2013 15:47
Last Modified: 17 Mar 2016 17:35
URI: http://digilib.uin-suka.ac.id/id/eprint/8193

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