z-logo
open-access-imgOpen Access
Monitoring Program Keluarga Harapan Berbasis Mobile GIS Menggunakan K-Means Clustering
Author(s) -
Ahmad Muhariya,
Bebas Widada,
Sri Siswanti
Publication year - 2021
Publication title -
techno.com
Language(s) - English
Resource type - Journals
eISSN - 2356-2579
pISSN - 1412-2693
DOI - 10.33633/tc.v20i4.4463
Subject(s) - poverty , cluster analysis , government (linguistics) , business , psychology , economic growth , environmental health , computer science , medicine , economics , machine learning , linguistics , philosophy
Poverty is a condition that is below the line of minimum requirement standard values, both for food and non-food. The Government of Indonesia has various programs to overcome poverty-based assistance social, including the family hope program. This family hope program is the provision of conditional cash assistance to very poor households in which there are pregnant women, toddlers, elementary, junior high, high school, elderly, and severe disabilities. The amount of assistance obtained based on the level of family poverty with poverty level parameters is seen from the many categories of very poor households concerned along with the obligation of participants to carry out important commitments in the field of Health and Education. The purpose of this research is the development of a mobile-based poor family monitoring application using the k-means clustering method. Validity test results using sample data 21, it can be concluded that the system can group poor families into 7 clusters with a thoroughness rate of 90.4%.  Based on these results, K-Means Clustering can be said to have a high accuracy value for clustering poor families.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here