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All Journal Techno.Com: Jurnal Teknologi Informasi CESS (Journal of Computer Engineering, System and Science) Jurnal ULTIMATICS IKRA-ITH ABDIMAS Jurnal Abdi Masyarakat (JAM) Djtechno: Jurnal Teknologi Informasi Mejuajua MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA SAINSTECH: Jurnal Penelitian dan Pengkajian Sains dan Teknologi Jurnal Masyarakat Madani Indonesia Madani : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Jurnal Ilmu Komputer dan Sistem Informasi Jurnal Pengabdian Masyarakat Journal Collabits
Kurnia Gusti Ayu
Universitas Mercu Buana
Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Public Health Social Sciences Other

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ANALISIS REGRESI LOGISTIK DENGAN SELEKSI FITUR DAN VALIDASI SILANG DALAM MENENTUKAN MODEL PREDIKSI STATUS GIZI ANAK Dwi Wulandari Sari; Kurnia Gusti Ayu; Hariesa Budi Prabowo
Djtechno: Jurnal Teknologi Informasi Vol 6, No 2 (2025): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i2.6925

Abstract

The impact of the economic crisis after the COVID-19 pandemic and the Russia-Ukraine conflict has affected Indonesia's food stability, including the nutritional intake of school children. To respond to this, this study developed a multivariate logistic regression-based predictive model to identify children's nutritional status (normal, malnourished or obese) based on questionnaire data of parents with children aged 6-15 years. The variables analyzed included eating patterns, physical activity, snacking habits, and consumption of fast food and sweet drinks. The results of the Pearson correlation analysis showed that children with a balanced diet (rich in vegetables, fruits, and protein) tend to have normal nutritional status, while the consumption of fast food andsugary drinks is negatively correlated with nutritional health. Breakfast and physical activity were also shown to have a positive effect. However, the prediction model built has limited accuracy with high specificity for normal cases at 0.92, but low sensitivity at 0.38 in detecting poor nutrition/obesity. This means that the model is not yet reliable enough for critical medical applications, but it remains useful as an initial scoring tool. These findings leadto three practical recommendations: (1) an early detection system for nutrition problems based onsimple scores, (2) personalized nutrition interventions (such as reducing fastfood and increasing physical activity), and (3) refining the Free Nutritious Meal program so that it is well-targeted. Although still in the proof of concept stage (TKT 3), this research provides a scientific foundation for data-driven nutrition policy at the primary healthcare level, especially in the midst of global economic challenges that affect family food security. With this approach, efforts to prevent malnutrition in school children are expected to be more targeted, efficient and adaptive to changing socio-economic dynamics.
Co-Authors Abdi Wahab Afiyati, Afiyati Ana Maria Ildiberta Da Costa Martins Ardy Triwibowo Bagus Budi Darmawan Dana Riksa Buana Dina Syakina Djoko Harsono Dwi Wulandari Sari Edyana, Fajar Fadila, Rasyif Subhan Faith Mikhael Riry Hanna Yunita Hariesa Budi Prabowo Hariesa Budi Prabowo Junaedi Junaedi Medina Fibriyanti Akmal Muhammad Arya Hafsah Nurfiant Muhammad Irvan Prabowo, Hariesa Budi Putra, Wisnu Buana Rahma, Intan Dwi Roza, Yuni Sakhrassalam, Haytsam Saruni Dwiasnati Suzan Bernadetha Syafiq, Nur Muhammad Zihni Syakur Khoiri Zein, Adam