MENGELOMPOKKAN REMAJA BERDASARKAN NILAI IMT (INDEX MASA TUBUH) MENGGUNAKAN ALGORITMA K - MEANS

According to the Indonesian Minister of Health in 2010, the age limit for adolescents is between 10 to 19 years old and unmarried. Meanwhile, according to BKKBN, the age limit for adolescents is 10 – 21 years old (Ministry of Health, 2010). [1]. The purpose of the study is to produce a grouping of BMI values in adolescent posyandu in the UPTD Pengaringan Health Center and adolescent posyandu in the UPTD Pengaringan Health Center. Based on observations to the research places of the UPTD Pengaringan Inpatient Health Center and the Youth Posyandu in the area of the UPTD Pengaringan Inpatient Health Center. Where to determine BMI is still calculated by excel and the data has not been neatly arranged. So that it is not possible to accurately measure the grouping of body mass status in adolescents, to group the BMI (Body Mass Index) of adolescents still have to search and recalculate the data according to needs, this takes a long time and risks inaccuracy. This research uses the K-means algorithm, the classification method using data mining and for testing using ...Keywoard: IMT, K – means, Data mining, Rafid minner, Google colab

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Publication Details

Journal
Format Jurnal Ilmiah Teknik Informatika
Published
2024-11-07
DOI
https://doi.org/10.22441/format.2024.v13.i1.003
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

MENGELOMPOKKAN REMAJA BERDASARKAN NILAI IMT (INDEX MASA TUBUH) MENGGUNAKAN ALGORITMA K - MEANS

Elsa Pratiwi
Format Jurnal Ilmiah Teknik Informatika
Data Mining and Machine Learning Applications
article

MENGELOMPOKKAN REMAJA BERDASARKAN NILAI IMT (INDEX MASA TUBUH) MENGGUNAKAN ALGORITMA K - MEANS

Elsa Pratiwi
article en

Abstract

According to the Indonesian Minister of Health in 2010, the age limit for adolescents is between 10 to 19 years old and unmarried. Meanwhile, according to BKKBN, the age limit for adolescents is 10 – 21 years old (Ministry of Health, 2010). [1]. The purpose of the study is to produce a grouping of BMI values in adolescent posyandu in the UPTD Pengaringan Health Center and adolescent posyandu in the UPTD Pengaringan Health Center. Based on observations to the research places of the UPTD Pengaringan Inpatient Health Center and the Youth Posyandu in the area of the UPTD Pengaringan Inpatient Health Center. Where to determine BMI is still calculated by excel and the data has not been neatly arranged. So that it is not possible to accurately measure the grouping of body mass status in adolescents, to group the BMI (Body Mass Index) of adolescents still have to search and recalculate the data according to needs, this takes a long time and risks inaccuracy. This research uses the K-means algorithm, the classification method using data mining and for testing using ...Keywoard: IMT, K – means, Data mining, Rafid minner, Google colab

Format Jurnal Ilmiah Teknik InformatikaVol. 13(1)
Openalex Percentile: Top 51%
Data Mining and Machine Learning Applications
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