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Journal : Journal of Applied Data Sciences

A Dual-Fusion Hybrid Model with Attention for Stunting Prediction among Children under Five Years Hadikurniawati, Wiwien; Hartomo, Kristoko Dwi; Sembiring, Irwan; Arthur, Christian
Journal of Applied Data Sciences Vol 6, No 3: September 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i3.831

Abstract

Malnutrition remains a persistent global health challenge, especially among children under five. Traditional assessment methods often rely on static anthropometric measures, which are limited in capturing complex growth patterns. This study aims to develop a robust classification model for predicting the nutritional status of children under five years old, addressing the critical public health challenge of stunting. The model contributes to the growing need for accurate, data-driven early detection systems in child health monitoring by introducing a hybrid framework that combines deep learning and classical machine learning techniques. The proposed approach integrates automatically extracted features from a One-Dimensional Convolutional Neural Network (1D-CNN) with classical anthropometric indicators. These combined features are processed through an additive attention mechanism, highlighting the most informative attributes. The attention-weighted representation is then classified using an ensemble stacking method that aggregates predictions from multiple base classifiers, including decision trees, nearest neighbor algorithms, support vector machines, etc. Synthetic Minority Over-sampling Technique (SMOTE) is applied to the training dataset to mitigate data imbalance, particularly the underrepresentation of severe and moderate malnutrition cases. The research utilizes a dataset comprising 2,789 records of children under five years old collected from community health posts in Indonesia. Data preprocessing included cleaning, normalization, and gender encoding. The model’s performance was evaluated using 5-fold cross-validation and measured by accuracy, precision, recall, and area under the curve metrics. The results show that the proposed model achieved an average accuracy of 99.70% and an area under the curve of 99.99%. An ablation study further demonstrated the significant contribution of each component, feature extraction, fusion mechanism, and ensemble classifier to the final performance. This approach reveals a robust and scalable solution for early nutritional status prediction in healthcare settings.
Co-Authors Ade Iriani Adyatma Andhika Bagaskara Agus Bambang Nugraha Ahmad Ashifuddin Aqham Alexandra, Andrea Cellista Allu, Roy Armus Andeka Rocky Tanaamah Andreas Arga Rinjani Saputro Andriana, Myra Angelia Destriana Anggara Cahya Putra Anita Sulistiawati Anthony Y.M. Tumimomor April Firman Daru Ariany Mahastanti, Linda Ariel Kristianto Arthur, Christian Aruperes, Viveca Grivenda Aryanata Andipradana Baali, Gabriel Megfaden Kenisa Brilliananta Radix Dewana Chandra Husada Danny Manongga Danny Sebastian Dearmelliani Tarigan Desyandri Desyandri Dewi, Stefani Fransisca Dian Widiyanto Chandra Diky Candra Muria Pratama Djoko Hartanto Dwi Anggono Winarso Suparjo Putra Dwi Hosanna Bangkalang Eko Sediyono Enik Muryanti Estie Grace Melisa Sinulingga Evangs Evi Maria Evi Maria Evi Maria Ezra Julang Prasetyo Faudisyah, Alfendio Alif Gerry Santos Lasatira Gladiola Lavinia Ambayu Gogo Krisatyo Hanna Arini Parhusip Hanna Prillysca Chernovita Hindriyanto Dwi Purnomo Indrajaya, Denny Irwan Sembiring Ismanto, Bambang Ismanto Joanito Agili Lopo Joanito Agili Lopo Johan Jimmy Carter Tambotoh Joshua Rondonuwu Josua Josen Alexander Limbong Karina Bianca Lewerissa Kevin Benedictus Simarmata Kevin Hendra William Kevin Stevian Hermawan Kezia Sharent Kodoati Kuncoro, Wreda Agung Kurniawan, Timothy Arif Linda Ariany Mahastanti Lobo, Murry Albert Agustin Lutfi Rahmawati Magdalena Ariance Ineke Pakereng Martin Setyawan Martin Teddy Sihite Matheus Supriyanto Rumetna Mila Chrismawati Paseleng Mozad Timothy Waluyan Muflihanto, Ezar Juan Muhammad Rizky Ramadhan Muhammad Sholikhan Neilin Nikhlis Nicolas Evander Suhandi Nina Setiyawati Nining Fitriani nuranto, bogo Nurrokhman Nurrokhman Nuzhah Al Waaidhoh Penidas Fodinggo Tanaem Prakoso, Hendri Suryo Pramudhita Tunjung Seta Prasianto, Kornelius Reinand Purnomo, Andreas Wisnu Adi Purwanto Purwanto Raditya Ditto Aryaputra Radius Tanone Radjawane, Samy Rahmat Abadi Suharjo Raymond Elias Mauboy Rizaldi, Alexander Sandy Pratama Septian Silvianugroho Sinulingga, Yedija Sada Ukurta Sri Yulianto Sri Yulianto Joko Prasetyo Sri Yulianto Prasetyo Stevan Hamonangan Hardi Suhandi, Nicolas Evander Suryasatriya Trihandaru Sutarto Wijono T. Arie Setiawan P Takakobi, Michael Richard Teguh Wahyono Theopillus J. H. Wellem Tri Harjani Tri Wahyuningsih Triloka Mahesti Tumbade, Marcho Oknivan Wahab, Nur Haliza Abdul Wibowo, Mars Caroline Winarko, Edi Wiwien Hadikurniawati Yessica Nataliani Yohan Maurits Indey Zenitha Eunike Tridinatha