Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/3749
Title: Data mining to analyse recurrent crime in South Africa
Authors: Monyeki, Phirime 
Issue Date: 2-Nov-2021
Abstract: 
When South Africa is compared to other countries, it has a notably high rate of crime. The
country has seen a concomitantly high occurrence of murder, residential burglary, drug-related
crime and carjacking (hijacking) crime. The government is desperately seeking solutions that
can be implemented to reduce recurrent crime. Several reasons to explicate high crime trends
in different areas include alcohol or drug abuse, low standards of education, poor parenting
skills and a lack of social and vocational skills. This study aimed to gain better insight into
crime trends in South Africa using data mining techniques. Decision-making linked to the data
could help the government implement a coherent crime strategy to mitigate crime. The crime
dataset chosen for this study was publicly available at kaggle.com. The dataset was prepared
using Python programming code. The research design was utilised as an overall strategy to
compile all different components of this study with an intention of answering the research
questions and attaining the research objectives. To identify the significant changes, ChangePoint Analysis (CPA) was performed to pinpoint the abrupt change in the South African crime
dataset. Two methods called Cumulative Sum (CUSUM) and Bootstrap were implemented in
this study of CPA. To analyse the trend of data, CUSUM and Bootstrap were performed to
measure the occurrence of change points based on the confidence levels. The CPA outcome
depicted multiple significant changes and abrupt shifts in several provinces of South Africa.
Linear regression (LR) was utilised to predict the future trends of crime in South Africa from
2016 – 2022 based on the erstwhile 2005 – 2015 crime statistics. The results showed that crime
has been on the increase in South Africa with certain provinces such as Western Cape, Gauteng
and KwaZulu-Natal being identified as crime hotspots. Future studies on crime should focus
only on one province to gain insight into the dominating crimes and hotspots within that
particular province, with a view to developing highly specific crime-reduction interventions.
Description: 
A dissertation submitted in fulfilment of the requirement for the degree of Master of Information and Communications Technology, Department of Information Technology, Faculty of Accounting and Informatics, Durban University of Technology, 2021.
URI: https://hdl.handle.net/10321/3749
DOI: https://doi.org/10.51415/10321/3749
Appears in Collections:Theses and dissertations (Accounting and Informatics)

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