Sentiment Analysis of Public Opinion on Handling Stunting in Indonesia using Random Forest

Abstract

The issue of stunting is important to address, as it has the potential to affect the human resource potential and is related to health levels, and even child mortality. The Indonesian government targets to reduce the stunting rate to 14 percent by 2024 through an accelerated stunting reduction program as an effort to improve the nutritional status of the society and also reduce the prevalence of stunting or stunted children. Understanding public sentiment towards the stunting initiative is crucial for policymakers and stakeholders to design effective interventions and allocate resources efficiently. This study aims to analyze public sentiment related to stunting in Indonesia, which impacts children's growth and development. Through the use of sentiment analysis techniques, this study aims to understand public perceptions and attitudes towards the issue of stunting, evaluating whether the general sentiment is positive, negative or neutral. The results of this analysis are expected to provide useful insights for policymakers and health practitioners in designing and implementing more effective strategies to address the issue of stunting.  This study conducted sentiment analysis from crawled Twitter data, showing positive and negative sentiments of the public regarding stunting handling in Indonesia. Furthermore, classification analysis using random forest was conducted and resulted in an accuracy score of 97.5%. The model is good enough but, we suggest trying other algorithms in further research.