Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Jurnal Gaussian
Andreanto Andreanto
Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro
Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Gaussian

 1 
IMPLEMENTASI R-SHINY UNTUK ANALISIS BIPLOT KOMPONEN UTAMA (Studi Kasus: Penggunaan Alat Kontrasepsi pada Peserta Aktif KB di Provinsi Jawa Tengah Tahun 2019) Andreanto Andreanto; Hasbi Yasin; Agus Rusgiyono
Jurnal Gaussian Vol 10, No 4 (2021): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v10i4.33097

Abstract

The population problem is a fairly complex and complicated problem. Therefore, Indonesia seeks to control the birth rate with the Family Planning program. The implementation of this program can be evaluated through statistical data. The statistical analysis used is biplot principal component analysis to see the relationship between districts/cities in choosing the contraceptive device/method used, the variance of each contraceptive device/method, the correlation between contraceptive devices/methods, and the superiority value of the contraceptive device/method in the population. each district/city. The problem with performing the analysis is the limitations of easy-to-use open source software. As with R, users must understand writing code to perform data analysis. Therefore, to perform a biplot analysis of the principal components, an RShiny application has been created using RStudio. The R-Shiny that has been made has many  advantages,  including  complete  results  which  include  data  display,  data transformation, SVD matrix, to graphs along with plot graph interpretation. The results of the principal component biplot analysis using R-Shiny with α =1 have the advantage of a good principal component biplot, which is 95.63%. This shows that the biplot interpretation of the main components produced can be explained well the relationship between the district/city and the contraceptive methods/devices used. 
Co-Authors Agus Rusgiyono Hasbi Yasin