PENERAPAN ALGORITMA INVASIVE WEED OPTIMIZATION UNTUK PENENTUAN TITIK PUSAT KLASTER PADA K-MEANS
K-means is one of the most popular clustering algorithm. One reason for the popularity of K-means is it is easy and simple when implemented. However, the results of K-means is very sensitive to the selection of initial centroid. The results are often better after several experi...
Main Authors: | , I PUTU ADI PRATAMA, , Drs. Agus Harjoko, M. Sc., Ph. D. |
---|---|
Format: | Thesis |
Published: |
[Yogyakarta] : Universitas Gadjah Mada
2014
|
Subjects: |
Similar Items
-
Penerapan Algoritma Invasive Weed Optimnization untuk Penentuan Titik Pusat Klaster pada K-Means
by: I Putu Adi Pratama, et al.
Published: (2015-01-01) -
Penerapan Algoritma Pillar Untuk Inisialisasi Titik Pusat K-Means Klaster Dinamis
by: Ketut Agus Seputra, et al.
Published: (2020-12-01) -
Optimasi K-Means Dengan Particle Swarm Optimization (PSO) Dalam Penentuan Titik Awal Pusat Klaster Data Telekomunikasi
by: Raden Gesit Prasasti Alam, et al.
Published: (2024-02-01) -
Klastering Sayuran Unggulan Menggunakan Algoritma K-Means
by: Lina Mardiana Harahap, et al.
Published: (2022-12-01) -
ALGORITMA PENENTUAN TITIK PENCEKAMAN HOLE-BASED MODULAR FIXTURE
by: Josef Hernawan Nudu, et al.
Published: (2008-01-01)