Perbandingan Hasil Algoritma Self Organizing Map (SOM) dan Fuzzy C-Means Clustering Untuk Kualifikasi Data Kinerja Dosen

Authors

Keywords:

Cluster, Fuzzy C-means, Kinerja dosen, SOM,

Abstract

Perkembangan yang kompetitif dan mengglobal setiap lembaga, termasuk lembaga pendidikan perguruan tinggi kegiatan penilaian kerja atau unjuk kerja dari setiap pegawai merupakan kegiatan yang umum untuk penataan sumber daya manusia sebagai tenaga pendidik. Melalui proses penilaian kinerja dosen tersebut dilakukan proses kualifikasi agar dapat diketahui cluster-cluster yang terdapat didalamnya. Penelitian ini bertujuan untuk mengelompokkan dosen dengan teknik clustering sehingga diketahui karakteristik data dari hasil clustering. Teknik yang digunakan yaitu algoritma Self Organizing Maps (SOM) dan Algoritma Fuzzy C-means (FCM). Dalam penelitian ini dibagi menjadi 4 cluster dengan learning rate 0.5 pada SOM dan Error yang ditentukan adalah 0.0001. Hasil yang diperoleh nilai centroid awal mempengaruhi banyaknya iterasi dan elemen pada anggota cluster. Penggunaan nilai random rule-base pada nilai centroid awal menghasilkan kualifikasi yang sama. Secara keseluruhan algoritma SOM lebih unggul dibandingkan dengan algoritma FCM dalam konsisten
data terhadap centroid.

References

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Published

2018-09-20

Issue

Vol. 3 No. 2 (2018): Prosiding Seminar Nasional Ilmu Komputer dan Teknologi Informasi (SAKTI)

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Articles

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