Comparative study of predicting domestic violence cases in Malaysia using Logistic, Hyperbolic and Gompertz Growth Models / Nurul Haida Fadhil, Nur Khaliqah Maarof and Wan Nur Nabila Wan Ab Razak

• Main Authors: Fadhil, Nurul Haida, Maarof, Nur Khaliqah, Wan Ab Razak, Wan Nur Nabila
• Format: Student Project
• Language: English
• Published: 2019
• Subjects: Mathematical statistics. Probabilities; Analytical methods used in the solution of physical problems
• Online Access: http://ir.uitm.edu.my/id/eprint/39476/1/39476.pdf; http://ir.uitm.edu.my/id/eprint/39476/

Domestic violence is a violation of human rights and came to be a global problem. Many growth models that can be used to predict domestic violence cases however if not rigorously studied, may lead to incorrect conclusions and its characteristics can easily mislead even experienced researchers. There are three mathematical models which arc the Logistic growth model, the Hyperbolic growth model and the Gompertz grow1h model that can be used to predict domestic violence grow1h in Malaysia. The error analysis of the models was calculated and compared to find the preferable model for predicting domestic violence cases in Malaysia from the year 2020 until 2030. The result shows that the I lyperbolic grow1h model gives better prediction since its mean absolute error is smaller compared to the Logistic and Gomper1z growth model. Therefore, the Hyperbolic growth model is used to predict domestic violence from the year 2020 until 2030. From the result obtained, it shows that domestic violence cases increase throughout the year. Further research on domestic violence prediction needs to be done to better predict the future. There are many other grow1h models that also predict cases of domestic violence such as the Coalition model and the regression model.