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All Journal JITEK (Jurnal Ilmiah Teknosains) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jusikom : Jurnal Sistem Komputer Musirawas Jurnal Informatika Universitas Pamulang Jurnal Teknologi Informasi MURA EDUMATIC: Jurnal Pendidikan Informatika JUSIM (Jurnal Sistem Informasi Musirawas) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pengabdian Dharma Wacana Jurnal Abdimas Bina Bangsa JUSTIN (Jurnal Sistem dan Teknologi Informasi) Ngabdimas : Pengabdian Pada Masyarakat Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Alfis Arif
Sekolah Tinggi Teknologi Pagar Alam
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Social Sciences Veterinary Other

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Journal : EDUMATIC: Jurnal Pendidikan Informatika

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Sistem Cerdas Deteksi Status Gizi Anak melalui Eksplorasi Algoritma C.45 dan Forward Feature Selection Arif, Alfis; Gusmaliza, Debi
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 2 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i2.28014

Abstract

The problem of high rates of child malnutrition remains in Pagar Alam City. The lack of understanding of nutritional interventions and the limited ability of Posyandu cadres to conduct accurate nutritional assessments are the main factors. This situation makes it difficult for the community to monitor the nutritional status of children and provide appropriate nutritional intake. This research aims to create an intelligent system for detecting children's nutritional status through the exploration of C.45 algorithm and Forward Feature Selection in Pagar Alam City. This system is designed to detect children's nutritional status and provide recommendations for appropriate nutritional intake based on detection results with variables of children's weight and height. The data used amounted to 7519 data obtained from the Pagar Alam City Health Office. The model we use to build this system is waterfall with stages of planning, analysis, design, development, testing and implementation. Then the method we apply to this system is CRISP-DM and the C.45 algorithm and Forward Feature Selection technique. Our results are in the form of an intelligent system for detecting children's nutritional status, with the results of system testing using test data and training data showing 100% accuracy. In addition, black box testing also proves that the system works well as expected.
Co-Authors Debi Gusmaliza Desi Puspita Elpita Aisyah Febriansyah Febriansyah Ferry Putrawansyah Fitria Rahmadayanti Gusmaliza, Debi Inda Anggraini Masdalipa, Risnaini Ningrum, Ichda Utami Nurmaleni Okta Lesva Pitaloka Anggriani, Yesi Sasmita Sasmita Yogi Mukti