Cluster analysis is a descriptive task that seek to identify homogenous group of object and it
is also one of the main analytical method in data mining. K-mean is the most popular …

The recent wave of digitalization is characterized by the widespread deployment of sensors
in many different environments, eg, multi-sensor systems represent a critical enabling …

Clustering techniques are used to group the data based on the structure or through
classification to reduce the mathematical complexity of large datasets. The hierarchical and …

Data mining is the process of finding structure of data from large data sets. With this process,
the decision makers can make a particular decision for further development of the real-world …

Cloud computing harmonizes and delivers the ability of resource sharing over different
geographical sites. Cloud resource scheduling is a tedious task due to the problem of …

Cache-enabled UAVs are widely used as edge servers to provide on-demand content
services for ground users. Most of prior works deploy UAVs based on user locations and …

Provisioning of appropriate resources to cloud workloads depends on the Quality of Service
(QoS) requirements of cloud workloads. Based on application requirements of cloud users …

Intisari–Persaingan yang ketat di bidang bisnis memotivasi sebuah usaha kecil dan
menengah (UKM) untuk mengelola pelayanan terhadap konsumen tetap (pelanggan) …

K-means is a widely used partitional clustering method. While there are considerable
research efforts to characterize the key features of K-means clustering, further investigation …

In data mining, Clustering is the most popular, powerful and commonly used unsupervised
learning technique. It is a way of locating similar data objects into clusters based on some …