Classification of divorce causes during the COVID-19 pandemic using convolutional neural networks

Abstract

The COVID-19 pandemic has affected day-to-day activities. Some families experienced a positive impact, such as an increase of bonding between family members. However, there are families that experienced a negative effect, such as the emergence of various conflicts that lead to a divorce. Based on the literature, it can be stated that the COVID-19 pandemic contributed to the increasing number of divorce rates. This paper proposes a convolutional neural network (CNN) classification algorithm in determining the dominant causes of the increase in divorce rate during the COVID-19 pandemic. CNN is considered suitable for classifying large amounts of data. The data used as research materials are available on the official website of the Indonesian Supreme Court. This research utilizes Supreme Court divorce decisions from March 2020 to July 2021, which constitutes 15,997 datasets. The proposed number of layers implemented during the classification is four. The results indicate that the classification using CNN is able to provide an accuracy value of 96% at the 100th epoch. To provide a baseline comparison, the classical support vector machine (SVM) method was performed. The result confirms that CNN outweighs SVM. It is expected that the results will help any parties to provide a suitable anticipation based on the classified dominant causes of the divorce during the COVID-19 pandemic.

Impact of COVID-19 pandemic on marriage, divorce, birth, and death in Kerman province, the ninth most populous province of Iran

“…The implementation of social distancing rules to curb the spread of the disease made it challenging to hold extravagant wedding ceremonies. Uncertainty surrounding the duration of the crisis prompted some couples to expedite their marriage registration in order to save on expenses 43 . This factor could explain the observed increase in the marriage rate.…”

“…The pandemic has brought about changes in employment status and has escalated conflicts and domestic violence within families 10 . Consequently, stress, disputes, conflicts, and ultimately divorces have seen a rise due to the negative consequences of the pandemic 8 , 9 , 43 . However, it should be noted that economic factors are the most common cause of divorce 43 .…”

“…Consequently, stress, disputes, conflicts, and ultimately divorces have seen a rise due to the negative consequences of the pandemic 8 , 9 , 43 . However, it should be noted that economic factors are the most common cause of divorce 43 .…”

“…Iran has experienced a significant surge in divorce rates over the past decade, with economic factors remaining the most common cause of divorce 43 . The rise in housing costs due to a shortage of available housing and limited access to affordable financing, high unemployment rates, and inflation have played a role in driving up divorce rates, particularly among young couples 28 .…”

Machine learning survival analysis on couple time-to-divorce data

“…Another criterion to determine the goodness of the survival model is the hazard ratio. The higher the hazard ratio, the better the survival model (Bramantoro & Virdyna, 2022).…”