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Abstract


ANALISIS OF GENDER IN TURKEY USING DATA MINING CLASSIFICATION MODEL

Statistics on women are very important for achieving gender equality, determining the place of women in society and strengthening the contribution of women in socio-economic development and improving their social and economic status by identifying negative indicators. In this study, using the k-means algorithm and CHAID decision tree algorithms, one of the data mining classification (supervisory learning) models, the gender perspective in 81 provinces within the scope of 2019 population, fertility, health, marriage, family life, education, political life, business life. It is aimed to classify them according to the selected social structure and gender indicators and to determine the rules and variables that are effective in this classification. It is important that measures and improvements aimed at achieving gender equality are addressed with regional differences. The results of this study are also aimed to measure, monitor and compare indicators of gender-based inequality at the regional level and contribute to raising awareness on gender equality at the regional level.



Keywords
Gender, Data mining, CHAID analysis, K-means method



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