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All Journal JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Hen Hen Lumana
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Computer Science & IT

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Early Detection of Stunting in Toddlers Based on Ensemble Machine Learning in Purbaratu Tasikmalaya AL Husaini; Irani Hoeronis; Hen Hen Lumana; Luh Desi Puspareni
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 11, No 3 (2023)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v11i3.66465

Abstract

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.
Co-Authors AL Husaini Irani Hoeronis Puspareni, Luh Desi