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Image of PENGGUNAAN K-NEAREST NEIGHBOR DENGAN ALGORITMA GENETIKA UNTUK MENGIDENTIFIKASI GANGGUAN GIZI STUNTING BERDASARKAN PENGUKURAN ANTROPOMETRI

Text

PENGGUNAAN K-NEAREST NEIGHBOR DENGAN ALGORITMA GENETIKA UNTUK MENGIDENTIFIKASI GANGGUAN GIZI STUNTING BERDASARKAN PENGUKURAN ANTROPOMETRI

Cahyadi, Salsabila Virginia - Personal Name;

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Penilaian anda saat ini :  

Stunting nutrition disorders are a big problem with nutritional disorders in toddlers, where Indonesia has stunting prevention of 29.6%. Stunting nutrition can result in inhibited intelligence development in children and growth is not optimal, and can trigger obesity or degenerative diseases and potentially increase the rate of pain and death. Therefore, solutions are needed for the identification of stunting nutritional disorders in toddlers to find out and detect whether the toddler is identified as stunting or not. This research was developed to produce software with the K-nearest Neighbor method but the weakness of K-nearest Neighbor is that weighting on K-nearest Neighbor has complex k value and computational problems. So that the method that can be used to perfect the K-nearest Neighbor method is a genetic algorithm, in order to provide optimal results. In the identification of stunting nutritional disorders in this study using anthropometric measurements, namely parameters in the form of height, weight, and age. It obtained quite good accuracy results using a confusion matrix of 80%. Keywords: stunting nutrition, K-Nearest Neighbor, Genetic Algorithm, confusion matrix.


Availability
Inventory Code Barcode Call Number Location Status
2207002284T74961T749612022Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T749612022
Publisher
Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022
Collation
xii, 85 hlm.: ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
004.07
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Pengolahan Data
Jurusan Teknik Informatika
Specific Detail Info
-
Statement of Responsibility
SEPTA
Other version/related

No other version available

File Attachment
  • PENGGUNAAN K-NEAREST NEIGHBOR DENGAN ALGORITMA GENETIKA UNTUK MENGIDENTIFIKASI GANGGUAN GIZI STUNTING BERDASARKAN PENGUKURAN ANTROPOMETRI
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