Implementation of k-means clustering for the job provision in urban village

Unemployment is one of critical issue in society. It may creates snowball effect towards economic development in a country and leads to the economic recessions. Hence, it is important to solve this issue by implementing the clustering to provide groups of people that have chance for job provision. K-Means Clustering is employed in this study by using 378 of data samples. Ages, marital status, amount of land owned, and income are selected as the attributes. The clustering result pointed out that there are 3 clusters that represent the people chances to get job, namely “High”, “Medium”, and “Low”. To evaluate the proposed cluster, Davis-Boulden index is utilized and presents a proper score. The practical implications are presented and discussed, then suggestions for future research are provided.