![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgUbbS4M9CVThR_25FSR9VjrxlpYAsdwm86Ihl78k10wWisdz3gyCT8DEd5XxOgiDi-xmZgVBTxulTOc3oNY9qjb3FUTW2GXch9fGoO44aqipgFGj-b_B7V_HjrRMd60MJCrI2exmi7SaRG6GQBq7zKJqPRHq-GgJ1pl2R8KCidO-R_OXkVQk8RSa8zrQ/w640-h480/a11.png) |
Qudrant Analysis of Klassen Typology
|
Halo teman-teman, setelah sebelumnya kita telah membahas mengenai analisis Tipologi Klassen dengan menggunakan visualisasi spasial atau visualisasi peta, kali ini kita akan mencoba memvisualisasikan Tipologi Klassen dengan menggunakan grafik kuadran (Quadrant Chart) menggunakan R.
Sejauh ini, saya sendiri masih dalam pencarian mengenai cara praktik dan mudah dalam melakukan sekaligus memvisualkan analisis Tipologi Klassen ini. Namun, seiring waktu dan terus menyusuri beragam sumber, akhirnya saya bisa meracik ulang bagaimana kita menganalisis sekaligus memvisualisasikan Tipologi Klassen ini dengan grafik kuadran. Adapun penjelasan singkat mengenai apa itu Tipologi Klassen dapat teman-teman baca pada tautan berikut.
Tipologi Klassen sendiri umumnya memang tidak divisualkan dalam bentuk peta spasial, tetapi lebih sederhana dengan grafik kuadran. Tetapi, dalam melakukan visualisasi grafik kuadran, setidaknya pemahaman kita tidak hanya kulit. Dalam pembahasan kali ini, kita akan belajar bersama step by step bagaimana cara membangun grafik kuadran sehingga kita semua memahami setiap code yang ada. Package yang kita gunakan dalam membuat grafik kuadran kali ini meliputi package ggplot2 dan grid yang dapat teman-teman instal dan aktivasi terlebih dahulu kemudian menyiapkan data yang akan kita praktikkan pada tautan berikut.
Setelah datanya diunduh, berikut beberapa code untuk membuat visualisasi grafik kuadran sebagai bekal analisis Tipologi Klassen dengan Quadrant Chart:
library(ggplot2)
library(grid)
library(readxl)
lqku <- read_excel("C:/Users/Joko Ade/Downloads/lqku.xlsx")
lqku
## # A tibble: 38 x 3
## Wilayah LQ_Penmamin PE_Penmamin
## <chr> <dbl> <dbl>
## 1 Pacitan 0.110 4.62
## 2 Ponorogo 0.142 2.51
## 3 Trenggalek 0.0871 2.37
## 4 Tulungagung 0.205 2.09
## 5 Blitar 0.00557 4.78
## 6 Kediri 0.104 4.18
## 7 Malang 0.135 3.32
## 8 Lumajang 0.201 3.61
## 9 Jember 0.881 2.89
## 10 Banyuwangi 1.23 3.82
## # ... with 28 more rows
#mengattach Data
attach(lqku)
## The following objects are masked from lqku (pos = 4):
##
## LQ_Penmamin, PE_Penmamin, Wilayah
## The following objects are masked from lqku (pos = 5):
##
## LQ_Penmamin, PE_Penmamin, Wilayah
#Template Dasar
p <- ggplot(lqku, aes(LQ_Penmamin, PE_Penmamin))
p
![plot of chunk unnamed-chunk-20](data:image/png;base64,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) |
Visualisasi 1
|
#Mengatur Skala sumbu X
p <- p + scale_x_continuous(expand = c(0, 0), limits = c(-4, 13)) #cek nilai xmin xmax data
p
![plot of chunk unnamed-chunk-21](data:image/png;base64,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) |
Visualisasi 2
|
#Mengatur Skala Sumbu Y
p <- p + scale_y_continuous(expand = c(0, 0), limits = c(-1.05, 7)) #cek nilai ymin ymax data
p
![plot of chunk unnamed-chunk-22](data:image/png;base64,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) |
Visualisasi 3
|
#Memberi Label Sumbu X dan Y
p <- p + labs(x="Location Quotient (LQ)",y="Pertumbuhan Ekonomi (persen)")
p
![plot of chunk unnamed-chunk-23](data:image/png;base64,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) |
Visualisasi 4
|
#Mengatur Label Sumbu X pada sumbu koordinat dan warna Darkgrey
p <- p + theme(axis.title.x = element_text(hjust = 0, vjust=4, colour="darkgrey",size=10,face="bold"))
p
![plot of chunk unnamed-chunk-24](data:image/png;base64,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) |
Visualisasi 5
|
#Mengatur Label Sumbu Y pada sumbu koordinat dan warna Darkgrey
p <- p + theme(axis.title.y = element_text(hjust = 0, vjust=0, colour="darkgrey",size=10,face="bold"))
p
![plot of chunk unnamed-chunk-25](data:image/png;base64,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) |
Visualisasi 6
|
#Membuat Penomoran Grid Transparan
p <- p + theme(axis.ticks.x=element_blank(), axis.text.x=element_blank(),
axis.ticks.y=element_blank(), axis.text.y=element_blank()
)
p
![plot of chunk unnamed-chunk-26](data:image/png;base64,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) |
Visualisasi 7
|
#Memberi Judul Template
p <- p+ggtitle("Tipologi Klassen Lapangan Usaha Penyediaan Makan Minum")
p
![plot of chunk unnamed-chunk-27](data:image/png;base64,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) |
Visualisasi 8
|
#Memberi Border pada pinggir Template
p <- p + theme(panel.border = element_rect(colour = "lightgrey", fill=NA, size=4))
p
![plot of chunk unnamed-chunk-28](data:image/png;base64,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) |
Visualisasi 9
|
#Memberi Garis referensi Sumbu Y
p <- p + geom_hline(yintercept=3.081962, color = "lightgrey", size=1)
p
![plot of chunk unnamed-chunk-29](data:image/png;base64,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) |
Visualisasi 10
|
#Memberi Garis referensi Sumbu X
p <- p + geom_vline(xintercept=1, color = "lightgrey", size=1)
p
![plot of chunk unnamed-chunk-30](data:image/png;base64,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) |
Visualisasi 11
|
#Memberi Label dengan Padding Kotak, posisi cek koordinat
p <- p + geom_label(aes(x = -2, y = 6.9, label = "Kuadran II"),
label.padding = unit(2, "mm"), fill = "lightgrey", color="white")
p <- p + geom_label(aes(x = 6.5, y = 6.9, label = "Kuadran I"),
label.padding = unit(2, "mm"), fill = "lightgrey", color="white")
p <- p + geom_label(aes(x = -2, y = -0.9, label = "Kuadran III"),
label.padding = unit(2, "mm"), fill = "lightgrey", color="white")
p <- p + geom_label(aes(x = 6.5, y = -0.9, label = "Kuadran IV"),
label.padding = unit(2, "mm"), fill = "lightgrey", color="white")
#Mengcustome warna dengan Fungsi colfunc()
colfunc=colorRampPalette(c("#90afc5", "#336b87", "#2a3132", "#763626"))
warna <- colfunc(38)
#Plot Data dengan Dot Plot serta warna dan ukuran Dot 3
p <- p + geom_point(colour = warna, size = 3)
p
![plot of chunk unnamed-chunk-33](data:image/png;base64,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) |
Visualisasi 12
|
#Memberi Label setiap Dot dengan label nama WIlayah
p <- p + geom_text(aes(label=Wilayah),colour= warna, hjust=-0.25, vjust=0.25, size=3)
p
![plot of chunk unnamed-chunk-34](data:image/png;base64,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) |
Visualisasi 12
|