Early Detection of Stunting in Toddlers Based on Ensemble Machine Learning in Purbaratu Tasikmalaya

AL Husaini (Siliwangi University)
Irani Hoeronis
Hen Hen Lumana
Luh Desi Puspareni

JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Vol 11, No 3 (2023)

This research utilizes combines several algorithm model that improve the accuracy of early detection of stunting in toddlers in Purbaratu Tasikmalaya.  The ensemble method used a voting classifier to combine the prediction results of models. The data used in this research were anthropometric data from 195 toddlers in Purbaratu Tasikmalaya. Results of the testing have identified that the use of the ensemble model machine learning method produces high accuracy for 3 categories of anthropometric data categories tested, that combined accuracy value 97,43 %, 92,30%, and 94,87% for all ensemble model and category.