Application of Principal Component Analysis (PCA) to Identify the Main Factors Causing Stunting
Keywords:
Stunting, Principal Component Analysis (PCA), North Sumatra, Causal Factors, Dimension Reduction.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.
References
[1] Alam, S., & Nurcahyo, G. W. (2022). Expert system in diagnosing malnutrition in toddlers using the CBR method. Journal of Information Systems and Technology, 4(4), 143–148
[2] Darmin, Rumaf, F., Ningsih, S. R., Mongilong, R., Goma, M. A. D., & Anggaria, A. D. (2023). The importance of complete basic immunization in infants and toddlers. Journal of Community Service MAPALUS, 1(2), 15–21.
[3] Gemilastari, R., Zeffira, L., Malik, R., & Septiana, V., T. (2024). Characteristics of Babies with Low Birth Weight (BBLR). Scientific Journal, 3(1), 16-26.
[4] Harahap, L. J. (2021). The relationship between knowledge and K4 coverage in pregnant women at the Sangkunur Health Center. Pannmed Scientific Journal, 16(3), 899–903.
[5] Hazimah, M., Akbar, S., Pane, A. H., & Diba, F. (2024). Factors that affect the incidence of low birth weight in Bangka Regency. STM Journal of Medicine (Medical Science and Technology), 7(1), 42–52.
[6] Lesnussa, T. P., Kaseside, M., Utubira, E. E. M. (2025). Application of the Principal Component Analysis Method (Case Study: Poverty Rate in the Maluku Islands). Number: Scientific Journal of Mathematics, Earth and Space, 3(2), 152-160.
[7] Rambe, N. L., Sebayang, W. B. R., & Irsani, N. (2022). Health counseling on the importance of complete basic immunization in the work area of the Terjun Health Center. Scientific Journal of Community Service (Ji-SOMBA), 1(2), 48–52.
[8] Sari, R. K., & Susilowati, E. (2023). Scoping review: Factors that cause malnutrition in toddlers. Journal of Scientific Nutrition, 10(3), 1–9.
[9] Surbakti, E. S. B., Damayanty, Purba, A. M., Azzahra, I. A., Purba, R. R., Santika, & Hasibuan, S. D. (2026). Analysis of factors affecting the incidence of low birth weight babies at Regina Maris Hospital, Medan Maimun District, Medan City, North Sumatra Province in 2025. Scientific Forum and Student Discussion (FORISMA), 7, 799–806.
[10] Suwanti, Ramadhani, S.G., Yuliana, D., Safruddin, N., & Budiman, A. (2026). A systematic review of the application of K-Means clusters and elbow methods for stunting data analysis. Journal of Informatics Engineering Students, 10(2), 3469-3479.
. [11] Ula, M., Ulva, A., F. & Mauliza. (2021). Implementation of Machine Learning with Case Based Reasoning Model in Managing Malnutrition in Children. Journal of Informatics Kaputama(Jik), 5(2),333-339.
[12] Ulfah, S., & Fitrah, N. (2025). Determinants of Complete Basic Immunization Coverage as Part of Stunting Prevention Efforts in Medan City: A Literature Study. Journal of Public Health Clusters, 3(4), 1-10.
