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All Journal International Journal of Electrical and Computer Engineering JOIV : International Journal on Informatics Visualization JOURNAL OF APPLIED INFORMATICS AND COMPUTING MONSU'ANI TANO Jurnal Pengabdian Masyarakat Jurnal Pengabdian UNDIKMA Jurnal Teknik Informatika (JUTIF) Brilliance: Research of Artificial Intelligence Jurnal Pengabdian Masyarakat Bangsa
Eka Qadri Nuranti
Institut Teknologi Bacharuddin Jusuf Habibie
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Comparative Evaluation of Ensemble Learning Models for Prenatal Stunting Risk Assessment Based on Maternal Health Data Nur Inaya Bahar; Eka Qadri Nuranti; Intan Sari Areni
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13208

Abstract

Stunting remains a significant public health challenge, where interventions are often delayed as they occur postnatally. This research aims to shift the detection focus to the prenatal phase by comparing the performance of four Ensemble Learning algorithms: Random Forest, XGBoost, CatBoost, and Light Gradient Boosting Machine (LGBM). Using a maternal dataset from DPPKB Parepare City consisting of 871 respondents, the models were developed through a Stratified 5-Fold Group Cross Validation scheme to predict stunting risk based on clinical features of pregnant women. Experimental results show that LGBM is the most optimal algorithm, where the hyperparameter tuning process increased model performance to an F1-Score of 94.34% and an accuracy of 94.50%. Ablation analysis identified maternal age, height, and the age of the last child as the most dominant predictors. The best model was integrated into a web-based decision support system using cloud-based microservices architecture, featuring geospatial mapping. This study proves that the application of LGBM on prenatal maternal data can provide accurate early detection to support targeted nutritional interventions for Family Assistance Teams (TPK) in Parepare City, although its generalizability remains limited to local administrative characteristics and warrants further prospective external validation before broader deployment.
Co-Authors Abdurrohman, Jafar Agus, Muh. Al Ghozy, Osama Iyad Al-Fauzi S., Muhammad Faruq Areni, Intan Sari Bahar, Nur Inaya Bhary, Naradhipa Dwitilas, Fariz Wahyuzan Elisabeth Tri Juliana Kandakon Evi Yulianti Gunadin, Indar Chaerah Husin, Husna Sarirah Indar Chaerah Gunadin Intan Sari Areni Iskandar, M. Fauzan Jefri, Muhammad Rivaldi Khaera Tunnisa, Khaera Lukman Hakim M. Fauzan Iskandar Maharani, Putri Ayu Maratuttahirah Mardhiyyah Rafrin Mardhiyyah Rafrin, S.T., M.Sc. Muh. Abubakar Tunru Muh. Agus Muh. Ikhsan Amar, S.Kom., M.Kom. Muhammad Aldi Alfatih Muhammad Alfian Muhammad Anugrah Muhammad Anugrah Muhammad Fadel Hasyim Muhammad Faruq Al-Fauzi S. Muhammad Irsyad Erlangga Muhammad Rivaldi Jefri Naili Suri Intizhami Naili Suri Intizhami, S.Kom., M.Kom. Nur Inaya Bahar Osama Iyad Al Ghozy Primadina Hasanah Prof. Dr. Ir. Indar Chaerah Gunadin, ST.,MT.,IPM Putri Ayu Maharani Putri Ayu Maharani, S.T., M.Sc. Rafdah Pritama Saputri Rafrin, Mardhiyyah Rahmat Eka Putra R Palaloi Risnawati Sitti Rahma Yunus Sri Sukma Tahir Tassakka, Muhammad Irpan Sejati Tunru, Muh. Abubakar Yunus, Sitti Rahma