Title
Indonesian Gender Equality Survey Analysis Using Feature Selection Based Clustering
Abstract
This paper presents an analysis of an Indonesian gender equality survey: in 2019, we conducted a survey of attitudes about gender roles in Indonesia and obtained data from 122 individuals. The obtained data were analyzed using our original clustering method (UFVS, Unsupervised Feature Value Selection) to form clusters. The extracted features characterized the clusters and helped to analyze the attitudes of Indonesians towards gender equality. This method allowed the respondents to be grouped by features and each group characteristics could be easily identified. It facilitated the understanding of the survey data.
Year
DOI
Venue
2020
10.1109/iCAST51195.2020.9319480
2020 11th International Conference on Awareness Science and Technology (iCAST)
Keywords
DocType
ISSN
gender equality survey,Indonesia,unsupervised feature value selection,UFVS,clustering
Conference
2325-5986
ISBN
Citations 
PageRank 
978-1-7281-9120-1
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Takako Hashimoto15018.47
Shin, K.21310.86
David Lawrence Shepard322.79
Tetsuji Kuboyama400.34