Perancangan Aplikasi Clustering Sebagai Sumber Informasi Penentu Kelas Konsentrasi Bagi Mahasiswa Informatika UMS Dengan Algoritma K-Means

Setiawan, Dian (2015) Perancangan Aplikasi Clustering Sebagai Sumber Informasi Penentu Kelas Konsentrasi Bagi Mahasiswa Informatika UMS Dengan Algoritma K-Means. Skripsi thesis, Universitas Muhammadiyah Surakarta.

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Abstract

Department of Informatics in UMS has three concentrations. Due to these three concentrations, the students are required to choose one of these three concentrations at the end of the fourth semester. Currently, students determine the concentration based on the students’ own wishes without a system which gives the students consideration in selecting their concentration. By designing clustering k-means application, the researcher expects it can provide the students source of information to determine their class concentration. The variables used are the value of the dominant subjects of each concentration ranging from semester 1 to 4, the variables of information system and enterprise (Basic Web Programming, Algorithms and Programming, Introduction to Information System, Data Base System) concentrations. Computer network and multimedia (Data Communication, Computer Network, Practicum Computer Network, Operation System). Software engineering and animation (linear algebra and matrix, Algorithms and Data Structures, Discrete Structure 2, Digital system). The result is that the students of 2011 academic year data are distributed into 3 cluster, cluster 1 with centroid point (3,333 ; 3,548 ; 3,098) and cluster 2 with centroid point (0,915 ; 1,110 ; 0,773), also cluster 3 with centroid point (2,682 ; 3,221 ; 1,880). The members of cluster 1 are recommended to take the Computer Network and Multimedia concentration, the members of cluster 2 are recommended to take the Software engineering and animation concentration then the members of cluster 3 are recommended to take the Information System and Enterprise concentration.

Item Type: Karya ilmiah (Skripsi)
Uncontrolled Keywords: Class Concentration, Clustering Method, Data Mining, K-Means Algorithms, Majoring.
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komunikasi dan Informatika > Teknik Informatika
Depositing User: Dian Setiawan
Date Deposited: 04 Aug 2015 06:25
Last Modified: 04 Aug 2015 06:25
URI: http://eprints.ums.ac.id/id/eprint/35905

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