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All Journal Timuris : Journal of Computational and Information Research
Aisyah Novianti
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Application of Principal Component Analysis (PCA) to Identify the Main Factors Causing Stunting Novica Sintasyah Sinaga; Elisabeth Princess; Aisyah Novianti
Timuris: Journal of Computational and Information Research Vol. 1 No. 1 (2026): Timuris: Journal of Computational and Information Research
Publisher : Kiswah Institute

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Abstract

Stunting is a serious public health problem in Indonesia, including in North Sumatra Province where the prevalence is still above the threshold set by WHO. This study aims to identify the main factors that cause stunting in North Sumatra Province using the Principal Component Analysis (PCA) method. PCA is applied to reduce a number of variables that cause stunting into several main components that are able to explain the diversity of data to the maximum and overcome the problem of multicollinearity between variables. The data used is secondary data from stunting vulnerability indicators in districts/cities throughout North Sumatra Province. The results of the analysis showed that PCA succeeded in reducing the data dimension and identifying the main components with the highest eigenvalues that were the dominant factors causing stunting. These findings are expected to provide a comprehensive overview of the factors that have the most influence on stunting incidence in North Sumatra, so that it can be the basis for more targeted and effective intervention policy recommendations for local governments in an effort to accelerate the reduction of stunting rates.  
Co-Authors Elisabeth Princess Novica Sintasyah Sinaga