The Grouping of Regions are Based on the Unemployment Rate in the Attacking Districts with the K-Means Method
- DOI
- 10.2991/assehr.k.200303.043How to use a DOI?
- Keywords
- idleness, clustering, k-means method, data mining
- Abstract
Each region experiences the number of idleness faced by the government. Currently, the Government through the Central Bureau of Statistics conducts a National Labor Force Survey to determine the number of unemployed from each region. Banten Province experienced a decline in the Labor Force Participation Rate (LFPR) of 1.60 percent. Currently, the open idleness grouping conducted in Serang District still uses group strata sourced from the office of the Provincial Central Bureau of Statistics. Based on the data already in the group BPS only displays idleness data based on certain criteria and does not show which region is the highest idleness rate. Therefore, it is necessary to classify the region to know which areas have a high and low idleness rate. In this case, the researcher collects data by looking at data already collected by BPS, by interviewing and viewing literature on idleness data in Banten Province. After viewing and collecting idleness data the idleness grouping of open idleness can still be done in another way, namely to see the proximity of the data point distance between one indicator with other indicators, one of them using clustering approach by using k-means method. K-means method is a non-hierarchical clustering method that seeks to partition existing data into one or more forms. By using the method k-means aim in facilitating the grouping of a region by looking at the number of low idleness rates or high level which results is a pie chart that describes the number of areas that have been grouped based on calculations by the k-means method. From the results of the image can be easily seen in the area where the highest and lowest idleness.
- Copyright
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Rudianto AU - Ramdani Budiman PY - 2020 DA - 2020/03/06 TI - The Grouping of Regions are Based on the Unemployment Rate in the Attacking Districts with the K-Means Method BT - Proceedings of the 1st International Multidisciplinary Conference on Education, Technology, and Engineering (IMCETE 2019) PB - Atlantis Press SP - 177 EP - 185 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.200303.043 DO - 10.2991/assehr.k.200303.043 ID - 2020 ER -