Factors Affecting Stunting Using Automatic Content Analysis: The Computer Framework Approach

This research aims to analyze the content of articles related to stunting and machine learning as a solution to stunting cases. The result of this research is a framework that will be used for further study. This research uses the Automatic Content Analysis (ACA) method and Leximancer text analysis tool. Reputable articles from journals and proceedings, keywords stunting and machine learning, published 2018-2023, English language, and open access. We then used ACA and Leximancer to organize and group the articles into a structured dataset. This was followed by a more in-depth text analysis process within Leximancer. The analysis with Leximancer resulted in a framework with 6 categories with various concepts related to stunting: risk factors (growth), health impacts(motherhood), interventions, prevention efforts, demographics, and Nutrition. ACA and Leximancer allows data to be viewed visually, to see relationships between concepts, and to understand the complexity of the problem of interconnections between concepts.