Socio-Economic Household Data Analysis Of Vientiane Capital,Laos PDR Using The Clustering And Association Technique For Data Mining

With the rapid development of technology and increasing rate of data gives us new terminology for data analysis and data clustering.With a view toward analysis of sources of data,we consider the challenging task of developing exploratory analytical techniques to explore clustering techniques analysis there have been many clustering algorithms.K-Means is one of the most popular clustering algorithms because it is easy and simple when implemented.This research is the studies and analyses the data from the Household Socio-Economic Survey 2018 of Vientiane capital,Laos PDR.for cluster the expenditure of population by use K-means algorithm and find right cluster of data by using DB Index and SD Validity Index.we found that the appropriate number of clusters is three clusters.Then we use association rule technique to determine the relationship between variables.The results show that the association rule is similar among clusters.For example,the average monthly household income is related to the average monthly household cost.Besides,household size is related to number of earners per household.Furthermore,the monthly tobacco cost for a household is associated with a number who are entitled to reimbursement for medical expenses.