Classification of Low Birth Weight Baby Under Anthropometry uses Algorithms K-Means Clustering on Maternity Hospital

Classification of Low Birth Weight Baby Under Anthropometry uses Algorithms K-Means Clustering on Maternity Hospital

LBW infants with birth weight less than 2500 grams regardless gestation period. Low birth weight is the weight of a baby who weighed within 1 hour after birth. World Health Organization (WHO) since 1961 states that all newborns are underweight or equal to 2,500 g called low birth weight infant (low...

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Main Authors: Irfan Santiko, Deni Kurniawan
Format: Article
Language:English
Published: Bright Publisher 2020-03-01
Series:IJIIS: International Journal of Informatics and Information Systems
Subjects:
lbw
clustering
k-means
Online Access:http://ijiis.org/index.php/IJIIS/article/view/5
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spelling doaj-f181b0d8378c46a6a02cfea7ca32787f2021-07-03T00:32:10ZengBright PublisherIJIIS: International Journal of Informatics and Information Systems2579-70692020-03-0131293510.47738/ijiis.v3i1.54Classification of Low Birth Weight Baby Under Anthropometry uses Algorithms K-Means Clustering on Maternity HospitalIrfan Santiko0Deni Kurniawan1Amikom University Purwokerto, IndonesiaAmikom University Purwokerto, IndonesiaLBW infants with birth weight less than 2500 grams regardless gestation period. Low birth weight is the weight of a baby who weighed within 1 hour after birth. World Health Organization (WHO) since 1961 states that all newborns are underweight or equal to 2,500 g called low birth weight infant (low birth weight). According to WHO. Statistically, morbidity and mortality in neonates in developing countries is high, with the main causes is associated with LBW. To facilitate medical personnel in determining the risk of LBW. From the testing that has been done by the author, the k-means clustering algorithm has accuracy in classifying LBW babies by spacing the proximity between variables and the similarities in the test data,http://ijiis.org/index.php/IJIIS/article/view/5lbwclusteringk-means
collection DOAJ
language English
format Article
sources DOAJ
author Irfan Santiko
Deni Kurniawan
spellingShingle Irfan Santiko
Deni Kurniawan
Classification of Low Birth Weight Baby Under Anthropometry uses Algorithms K-Means Clustering on Maternity Hospital
IJIIS: International Journal of Informatics and Information Systems
lbw
clustering
k-means
author_facet Irfan Santiko
Deni Kurniawan
author_sort Irfan Santiko
title Classification of Low Birth Weight Baby Under Anthropometry uses Algorithms K-Means Clustering on Maternity Hospital
title_short Classification of Low Birth Weight Baby Under Anthropometry uses Algorithms K-Means Clustering on Maternity Hospital
title_full Classification of Low Birth Weight Baby Under Anthropometry uses Algorithms K-Means Clustering on Maternity Hospital
title_fullStr Classification of Low Birth Weight Baby Under Anthropometry uses Algorithms K-Means Clustering on Maternity Hospital
title_full_unstemmed Classification of Low Birth Weight Baby Under Anthropometry uses Algorithms K-Means Clustering on Maternity Hospital
title_sort classification of low birth weight baby under anthropometry uses algorithms k-means clustering on maternity hospital
publisher Bright Publisher
series IJIIS: International Journal of Informatics and Information Systems
issn 2579-7069
publishDate 2020-03-01
description LBW infants with birth weight less than 2500 grams regardless gestation period. Low birth weight is the weight of a baby who weighed within 1 hour after birth. World Health Organization (WHO) since 1961 states that all newborns are underweight or equal to 2,500 g called low birth weight infant (low birth weight). According to WHO. Statistically, morbidity and mortality in neonates in developing countries is high, with the main causes is associated with LBW. To facilitate medical personnel in determining the risk of LBW. From the testing that has been done by the author, the k-means clustering algorithm has accuracy in classifying LBW babies by spacing the proximity between variables and the similarities in the test data,
topic lbw
clustering
k-means
url http://ijiis.org/index.php/IJIIS/article/view/5
work_keys_str_mv AT irfansantiko classificationoflowbirthweightbabyunderanthropometryusesalgorithmskmeansclusteringonmaternityhospital
AT denikurniawan classificationoflowbirthweightbabyunderanthropometryusesalgorithmskmeansclusteringonmaternityhospital
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