ommon approaches to stunting prediction, including statistical analysis and machine learning, have poor performance due to shifts in the factors influencing stunting. Causes data cannot be integrated directly when using statistical analysis. At the same time, machine learning causes a decrease in predictive performance down over time. This study proposes a new approach to stunting prediction in infants and toddlers aged 0-5 years using continuous learning methods.

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[1] dicky faisal, allya paramita, "Data_Stunting", IEEE Dataport, 2023. [Online]. Available: http://dx.doi.org/10.21227/7wx2-3c69. Accessed: Feb. 28, 2024.
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doi = {10.21227/7wx2-3c69},
url = {http://dx.doi.org/10.21227/7wx2-3c69},
author = {dicky faisal; allya paramita },
publisher = {IEEE Dataport},
title = {Data_Stunting},
year = {2023} }
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AU - dicky faisal; allya paramita
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dicky faisal, allya paramita. (2023). Data_Stunting. IEEE Dataport. http://dx.doi.org/10.21227/7wx2-3c69
dicky faisal, allya paramita, 2023. Data_Stunting. Available at: http://dx.doi.org/10.21227/7wx2-3c69.
dicky faisal, allya paramita. (2023). "Data_Stunting." Web.
1. dicky faisal, allya paramita. Data_Stunting [Internet]. IEEE Dataport; 2023. Available from : http://dx.doi.org/10.21227/7wx2-3c69
dicky faisal, allya paramita. "Data_Stunting." doi: 10.21227/7wx2-3c69