Herawati, Dea (2020) PENERAPAN METODE K-NEAREST NEIGHBOR UNTUK MENENTUKAN STATUS GIZI BALITA (Studi Kasus Posyandu Padukuhan Trini). Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
Nutrition problems can occur in every phase of life, starting in the womb until old age. Malnutrition in infants can lead to mental health disorders, low IQ levels, infectious diseases, and children do not grow optimally. Accuracy in determining the nutritional status of children under five accurately takes a long time so it takes an algorithm, especially in the classification that is easily represented and implemented in a decision support system. In making it easier and accurate in giving nutritional status decisions to toddlers, a classification system for toddler nutritional status is made. The classification will use the KNN (K-Nearest Neighbor) method to calculate a healthy and unhealthy assessment of a toddler in terms of four conditions, namely age, height, weight and head circumference. So that with the research and making this website able to provide information on the nutritional status of infants to posyandu officers and parents quickly and accurately. Keywords: Classification, KNN (K-Nearest Neighbor), Decision Support
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 27 Mar 2020 04:19 |
| Last Modified: | 27 Mar 2020 04:19 |
| URI: | http://eprints.uty.ac.id/id/eprint/4910 |
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