Data analysis on domestic violence against the woman
DOI:
https://doi.org/10.33448/rsd-v12i1.39561Keywords:
Data analysis; Domestic violence; Predictive analytics; Discovery of knowledge in databases.Abstract
Femicide is the worst outcome of a police occurrence in cases of domestic violence, as the woman dies after suffering violence one or more times. The databases on domestic violence and femicide in the state of Paraná are made up of many attributes and valuing them for further analysis is a problem that, without the aid of a flow or method, can be a time-consuming and ineffective task. The objective of this study was to build predictive analysis flows that support research with public safety data. This is a research with a quantitative approach, inductive method, at an exploratory level. The analysis of the violence against women databases for the years 2018, 2019 and 2020 was carried out using descriptive statistics combined with the Fayyad model for knowledge discovery through data mining that employed four attribute selection techniques with filter approach and rules induction algorithms PRISM and CN2. The average age is 37 years and the most frequent occupation is linked to domestic service for the victims of both databases, 63% of the women killed by femicide have a history of domestic violence, being more likely that the victim and the perpetrator cohabit and 19% of the victims registered more than one occurrences. The rules generated by the CN2 algorithm with the CFS and Info Gain attribute selection techniques were validated by specialists in criminal analysis.
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