Google Trends Data About Mental Health During COVID-19 Pandemic Using Time Series Regression

Along with the increasing number of COVID-19 sufferers during the Pandemic period, there was also an increase in searches related to mental health. Researchers have used a lot of Google Trends (GT) data to predict disease. However, researchers dissatisfied with the normalized index of GT began turning to Google Extended Trends for Health (GETH). Permissions and coding skills are needed to be able to access data from GETH. We have made one of the more friendly user interfaces for users without qualified coding skills. Using Google application programming interface (API), the data needed can quickly be taken according to the date parameter and the keywords required. We used 13 keywords using Indonesian to get search data on Google, as well as the number of positive COVID-19 sufferers in Indonesia released by the government. The regression analysis results show that the influence of the thirteen variables related to mental health on the positive cases of COVID-19 is 68.1%. In comparison, the most significant variables of the regression coefficient are cemas (anxiety), bunuh diri (suicide), and insomnia. The most partial variable is insomnia.