Pengelompokan Bidang Keilmuan Di Teknologi Informasi Dengan Metode K-Means Dan Optimasi Simple Additive Weighting (Saw) Dalam Penentuan Kesesuain Terhadapa Keilmuan
Keywords:
POLNES, JURTI, Bidang Keilmuan, K-Means, MAPE, SAW.Abstract
POLNES JURTI terdiri dari tiga prodi, terdapat 9 Bidang kompetensi keilmuan yaitu, Mobile Computing, Computer Controlled Infrastructure, Computer Vision, Robotic & Artificial Intelligent, Advanced Applied Computer, Human Computer Interaction, Intelligent Computing, Cloud Computing, Multimedia. Pada masing-masing prodi memiliki area kompetensi. Tujuan penelitian mengarahkan ke bidang kompetensi keilmuan yang lebih sesuai, algortima K-means merupakan sebuah algoritma yang mengkelompokan data berdasarkan jarak terdekat dari suatu cluster, MAPE digunakan sebagai perhitungan error pada masing-masing cluster dari perhitungan, SAW adalah metode penjumlahan terbobot, SAW pada penelitian ini dilakukan untuk menentukan responden yang paling sesuai dengan hasil cluster pada K-means. hasil perhitungan K-means tidak bisa menentukan cluster sesuai dengan masing-masing prodi. Karna K-means sendiri menghitung berdasarkan hasil dari nilai Res, dan membandingkan nilai tersebut pada masing-masing cluster, hasil perhitungan error dengan menggunakan MAPE, perhitungan error menunjukkan bahwa cluster pada K-means sangat akurat amat akurat dalam pembagian cluster berdasarakan hasil perhitungan dari kuisioner, Hasil dari perhitungan SAW menujukan bahwa ada nilai yang sama pada salah satu responden mengakibatkan rangking pada suatu cluster menjadi sama, seperti pada cluster CCI. Pada rangking 3 dan 7 masingmasing mempunya dua responden, Hal tersebut membuat perhitungan SAW pada cluster menjadi kurang optimal, karna dalam satu rangking terdapat dua responden.References
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