K-means and bayesian networks to determine building damage levels

Devni Prima Sari (Gadjah Mada University Negeri Padang University)
Dedi Rosadi (Gadjah Mada University)
Adhitya Ronnie Effendie (Gadjah Mada University)
Danardono Danardono (Gadjah Mada University)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 17, No 2: April 2019

Many troubles in life require decision-making with convoluted processes because they are caused by uncertainty about the process of relationships that appear in the system. This problem leads to the creation of a model called the Bayesian Network. Bayesian Network is a Bayesian supported development supported by computing advancements. The Bayesian network has also been developed in various fields. At this time, information can implement Bayesian Networks in determining the extent of damage to buildings using individual building data. In practice, there is mixed data which is a combination of continuous and discrete variables. Therefore, to simplify the study it is assumed that all variables are discrete in order to solve practical problems in the implementation of theory. Discretization method used is the K-Means clustering because the percentage of validity obtained by this method is greater than the binning method.