Open AccessVillage Grouping In Southwest Maluku District Based On Poverty Characteristics Using Self Organizing Maps (SOM) Methods
Author(s) -
Monalisa E. Rijoly,
F. L. Lumalessil,
Berny Pebo Tomasouw
Publication year - 2020
Publication title -
zeta - math journal/zeta-math journal
Language(s) - English
Resource type - Journals
eISSN - 2579-5864
pISSN - 2459-9948
DOI - 10.31102/zeta.2020.5.1.16-20
Subject(s) - poverty , self organizing map , government (linguistics) , cluster (spacecraft) , value (mathematics) , geography , computer science , statistics , artificial intelligence , economic growth , mathematics , artificial neural network , economics , linguistics , philosophy , programming language
Poverty is one of the fundamental problems that has become the center of attention of the Maluku Provincial government, especially Southwest Maluku Regency. This study aims to provide information to the government about village grouping based on poverty characteristics in Southwest Maluku Regency using the Self Organizing Map network method. In this network, a layer containing neurons will arrange itself based on the input of a certain value in a group known as a cluster. In the grouping process, 3 results were obtained with the best grouping II results because they had the smallest standard deviation ratio value.