Integration k-means clustering method and elbow method for identification of the best customer profile cluster

MA Syakur, BK Khotimah, EMS Rochman… - IOP conference series …, 2018 - iopscience.iop.org
Clustering is a data mining technique used to analyse data that has variations and the
number of lots. Clustering was process of grou** data into a cluster, so they contained …

Effect of distance metrics in determining k-value in k-means clustering using elbow and silhouette method

DM Saputra, D Saputra, LD Oswari - … international conference on …, 2020 - atlantis-press.com
Clustering is one of the main task in datamining. It is useful to group and cluster the data.
There are a few ways to cluster the data such as partitional-based, hierarchical-based and …

A comparative study of software defect binomial classification prediction models based on machine learning

H Tao, X Niu, L Xu, L Fu, Q Cao, H Chen… - Software Quality …, 2024 - Springer
As information technology continues to advance, software applications are becoming
increasingly critical. However, the growing size and complexity of software development can …

Severity detection of COVID-19 infection with machine learning of clinical records and CT images

F Zhu, Z Zhu, Y Zhang, H Zhu, Z Gao… - … and Health Care, 2022 - content.iospress.com
BACKGROUND: Coronavirus disease 2019 (COVID-19) is a deadly viral infection spreading
rapidly around the world since its outbreak in 2019. In the worst case a patient's organ may …

Detection and diagnosis of process fault using unsupervised learning methods and unlabeled data

A Rahoma, S Imtiaz, S Ahmed, F Khan - International Journal of Advances …, 2023 - Springer
Supervised learning methods, commonly used for process monitoring, require labeled
historical datasets for normal condition as well for each faulty condition, which demands …

Pendekatan Initial Centroid Search Untuk Meningkatkan Efisiensi Iterasi Klustering K-Means.

MZ Nasution, MS Hasibuan - Techno. com, 2020 - search.ebscohost.com
Pengelompokan K-Means bertujuan untuk mengumpulkan satu set titik pusat cluster yang
optimal melalui iterasi yang berurutan. Fakta bahwa semakin optimal posisi dari titik pusat …

Perbandingan metode K-Means dengan fuzzy C-Means untuk analisa karakteristik mahasiswa berdasarkan kunjungan ke perpustakaan (Studi kasus Sekolah Tinggi …

NPE Merliana - 2015 - e-journal.uajy.ac.id
Kurangnya minat membaca pada mahasiswa khususnya menjadi perhatian bagi lembaga
pendidikan, karena membaca dapat menambah wawasan, pengetahuan dan informasi …

Importance of initialization in K-means clustering

A Gupta, A Tomer, S Dahiya - 2022 Second International …, 2022 - ieeexplore.ieee.org
Data clustering is a method of visualizing the data in such a way that enables the researcher
to see similar patterns formed in the data and these lead to conclusions that can be helpful …

Penerapan k-means clustering dari log data moodle untuk menentukan perilaku peserta pada pembelajaran daring

E Ikhsan - Sistemasi: Jurnal Sistem Informasi, 2021 - sistemasi.ftik.unisi.ac.id
Pembelajaran berbasis daring atau e-learning mulai semakin banyak digunakan oleh para
pengampu pelajaran melalui Learning Management System (LMS). Moodle sebagai LMS …

Seismotectonic zoning by K-means clustering analysis in the Korean Peninsula

김성균, 전정수, 전명순 - 지질학회지, 2017 - dbpia.co.kr
지진활동이 활발하지 않은 판내부 지역에서는 확률론적 지진재해도 분석에 사용되는 지진원의
설정이 용이하지 않다. 지진원 모델을 설정하고 평가하는 유일무이한 공식적인 방법은 …