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All Journal TEKNIK Jurnal Pseudocode Journal of Information Systems Engineering and Business Intelligence Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini IT JOURNAL RESEARCH AND DEVELOPMENT JITU : Journal Informatic Technology And Communication TIN: TERAPAN INFORMATIKA NUSANTARA Journal Evaluation in Education (JEE) Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian Harmoni Sosial : Jurnal Pengabdian Dan Solidaritas Masyarakat Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Manfaat: Jurnal Pengabdian Pada Masyarakat Indonesia Ngudi Waluyo Empowerment : Jurnal Pengabdian Kepada Masyarakat
Alifia Revan Prananda
Department Of Information Technology, Faculty Of Engineering, Universitas Tidar
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Journal : Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini

 1 
Using Support Vector Machines for Predicting and Mitigating Stunting in Early Childhood Education in Rural Semarang Novichasari, Suamanda Ika; Prananda, Alifia Revan; Suwidagdho, Dhanang; Fauziah, Syifa; Setya Wijaya, Vania Amelia; Adam, Otmar Shah
Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini Vol. 8 No. 5 (2024)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/obsesi.v8i5.6131

Abstract

In 2030, 70% of Indonesia's population will be of productive age (15-64 years), which is a demographic bonus. However, this potential is threatened by the high rate of stunting in children, which threatens future workforce productivity. Early identification of stunting risk is essential for timely intervention. This study develops a stunting prediction model using machine learning with data from early childhood education institutions in rural Semarang. The model used is a Support Vector Machine (SVM) implemented through the RapidMiner framework. The SVM model achieved an accuracy of 97.56%, a precision of 98.97%, a recall of 97.37%, and an AUC of 0.997. The results of the SVM model highlight the importance of physical motor skills and artistic development.
Using Support Vector Machines for Predicting and Mitigating Stunting in Early Childhood Education in Rural Semarang Novichasari, Suamanda Ika; Prananda, Alifia Revan; Suwidagdho, Dhanang; Fauziah, Syifa; Setya Wijaya, Vania Amelia; Adam, Otmar Shah
Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini Vol. 8 No. 5 (2024)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/obsesi.v8i5.6131

Abstract

In 2030, 70% of Indonesia's population will be of productive age (15-64 years), which is a demographic bonus. However, this potential is threatened by the high rate of stunting in children, which threatens future workforce productivity. Early identification of stunting risk is essential for timely intervention. This study develops a stunting prediction model using machine learning with data from early childhood education institutions in rural Semarang. The model used is a Support Vector Machine (SVM) implemented through the RapidMiner framework. The SVM model achieved an accuracy of 97.56%, a precision of 98.97%, a recall of 97.37%, and an AUC of 0.997. The results of the SVM model highlight the importance of physical motor skills and artistic development.
Co-Authors Abdillah, Muhammad Nurkholis Adam, Otmar Shah Anisa Lestari Annisa Istiqomah, Annisa Bagus Fatkhurrozi Cornelius Rangga Surya Kusuma D Jayus Nor Salim Damar Wicaksono Daniel Gunawan Delfiyan Widiyanto Dhanang Suwidagdho Dinda Kusumaningrum Dwi Wulandari Eka Legya Frannita Galih Slamet Hidayat, Anwar Ibrahim Nawawi Imam Adi Nata Irfandy Thalib Lidia Faridah Majidah, Zharifa Nur Marwanto Marwanto, Marwanto Mashud Syahroni Mohammad Norman Aulia Mufasir Mujtahidah, Tholibah Nabila Fairuzzahra Niken Orisa Putri Novitasari Novitasari Pramitaningrum, Erlita Purwaningsih , Nunik Putri, Naimah Rahmawati, Atiqa Rakhmawati, Restu Rhema Chandrawati Sapto Nisworo Setiawan , Wawan Budi Setya Wijaya, Vania Amelia Suamanda Ika Novichasari Syifa Fauziah Terbit Bagaskara Ahmad Terra Rhebekka Wibowo, Fadhila Syahida Wibowo, Rheza Ari