UNIVERSITAS AIRLANGGA



Detail Article

Jurnal Biometrika dan Kependudukan

ISSN 2302707X

Vol. 3 / No. 1 / Published : 2014-07

Order : 6, and page :43 - 49

Related with : Scholar   Yahoo!   Bing

Original Article :

Penerapan clustering bootstrap dengan metode k-means

Author :

  1. Hendro Prasetyo*1
  2. Kuntoro*2
  3. Soenarnatalina*3
  4. Merry Adriani*4
  5. Bambang Wijanarko*5
  1. Prodi Kebidanan Jember Politeknik Kesehatan Kemenkes Malang
  2. Dosen Fakultas Kesehatan Masyarakat
  3. Dosen Fakultas Kesehatan Masyarakat
  4. Dosen Fakultas Kesehatan Masyarakat
  5. Dosen Fakultas Kesehatan Masyarakat

Abstract :

Cluster analysis was a process for grouping a set of objects based on data that have similarcertain characteristic. K-Means was a method of cluster analysis which begins by determining the number of clusters desired. Bootstrap was a sampling technique with replacement from the original sample. Bootstrap was used to estimate the parameters based on minimal data using a computer. This methode was useful to maximize relative diffrence and variation in the clusters. Malnutrition was a major problem in Indonesia and is still a concern in children under five. Infants with malnutrition would have a higher mortality rate. The purpose of this study wasto assess the accuracy of K-Means and Bootstrap K-Means method to clustering nutritional status of children undersfive which was crosstabulated with the nutritional status of children based on the WHO-2005 in the Ajung Public Health Center, Jember. The variable in this study was nutritional status based on WHO criteria 2005 as standard benchmarks, presentage and weight. This was non-reactive research, using secondary data in Ajung Public Health Center, without any direct interaction with the subject. This study concluded that the total accuracy rate (TAR) and Total Error Rate (TER) to determine nutritional status of  K-Means method was TAR=0.9 and,  TER=0.1; Bootstrap K-Means methode (B=25) TAR=0,925 and TER=0.075; Bootsstrap K-Means methode (B=50) TAR=0.9417, TER=0.0583;and Bootstrap K-Means Bootstrap (B=75) TAR=0.9583 and TER=0.0417 after crosstabulated with nutritional status based on WHO-2005 (weight for age). In conclusion general, the K-Means method and Bootstrap K-Means method and crosstabulated with nutritional status based on WHO-2005 has shown very good accuracy to determine the nutritional status of children. The best method was Bootstrap K-Means (B=75). K-Means Bootstrap methods can be used as an alternative way to determine the nutritional status of children. 

Keyword :

cluster analysis with K-Means method, bootstrap, nutritional status,


References :

Gudono,(2011) Analisis Multivariat, Edisi Pertama Yogyakarta : BPFE

Halim, S., Mallian, H,(2006) Penggunaan Bootstrap Data Dependen untuk Membangun Selang Kepercayaan Pada Parameter Model Peramalan Data Stationer Surabaya : Jurnal Teknik Industri, Vol. 8, No. 1

Han K,(2007) Data Mining Concepts and Techniques Second Edition San Fransisco : Elsevier Inc

Jelena, P,(2009) Clustering & Bootstrapping Groningen : University of Groningen

Kuntoro,(2011) MetodeStatistik, Edisi Revisi Surabaya : Pustaka Melati

Sjahid, M., A., Adatul, M., Lalita P,(2010) Bagging Regresi Logistik Ordinal Pada Status Gizi Balita Semarang : Media Statistika, Vol. 3, No.2

Menteri Kesehatan RI ,(2010) Standar Antropometri Penilaian Status Gizi Anak Jakarta : Dirjen Bina Gizi dan KIA

Supranto J,(2010) AnalisisMultivariat, Arti&Interpretasi Jakarta : Rineka Cipta

Zhu, W., Nancy, Z., Ning W,(2010) Sensitivity, Specificity, Accuracy, Associated Confidence Intervaland ROC



Archive Article

Cover Media Content

Volume : 3 / No. : 1 / Pub. : 2014-07
  1. Faktor Pada Ibu Yang Berhubungan Dengan Kejadian Komplikasi Kebidanan
  2. Peran Faktor Keluarga Dan Karakteristik Remaja Terhadap Perilaku Seksual Pranikah
  3. Hubungan Persepsi Nilai Anak Dengan Jumlah Dan Jenis Kelamin Anak Yang Diinginkan Pada Wanita Usia Subur Pranikah Di Perdesaan
  4. Analisis Faktor Risiko Berat Badan Lahir Pada Kematian Perinatal Menggunakan Meta Analysis
  5. Pemodelan Bayesian Model Averaging (bma) Pada Kasus Pneumonia Balita
  6. Penerapan Clustering Bootstrap Dengan Metode K-means
  7. Faktor Yang Mempengaruhi Perkawinan Muda Perempuan
  8. Pengaruh Faktor Risiko Ibu Dan Janin Terhadap Persalinan Caesarean Section
  9. Rendahnya Keikutsertaan Pengguna Metode Kontrasepsi Jangka Panjang Pada Pasangan Usia Subur
  10. Hubungan Status Kesehatan Neonatal Dengan Kematian Bayi
  11. Efektivitas Pemberian Wedang Jahe (zingiber Officinale Var. Rubrum) Terhadap Penurunan Emesis Gravidarum Pada Trimester Pertama
  12. Kondisi Sosioekonomi Dan Demografi Keluarga Pra Sejahtera Dan Sejahtera I

Information index.php/JIPK/JBK