Connected Scatterplot
library(ggplot2)
library(ggrepel)
data <- data.frame(
time = 2000:2020,
value = cumsum(rnorm(21, 0.5, 1)) # nilai acak kumulatif
)
data <- data[order(data$time), ]
ggplot(data, aes(x = time, y = value)) +
geom_point(color = "blue", size = 3) + # Titik
geom_line(color = "darkorange", size = 1) + # Garis penghubung
geom_text_repel(aes(label = round(value, 1)), size = 3) + # Label angka
labs(
title = "Connected Scatterplot",
x = "Tahun",
y = "Nilai"
) +
theme_minimal()
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
Network graph
library(tidyverse)
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library(igraph)
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library(ggraph)
library(tidygraph)
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library(visNetwork)
set.seed(123)
nodes <- tibble(id = 1:15,
label = paste0("N", id),
group_hint = sample(letters[1:3], 15, replace = TRUE))
edges <- tibble(
from = sample(nodes$id, 30, replace = TRUE),
to = sample(nodes$id, 30, replace = TRUE),
weight = round(runif(30, 0.2, 1.0), 2)
) %>%
filter(from != to) %>% # hindari self-loop
distinct(from, to, .keep_all = TRUE) # hindari duplikat
g <- graph_from_data_frame(edges, directed = FALSE, vertices = nodes)
# Centrality & komunitas
deg <- degree(g, mode = "all")
btw <- betweenness(g, directed = FALSE, normalized = TRUE)
cls <- cluster_louvain(g) # deteksi komunitas Louvain
comm <- membership(cls)
# Gabungkan metrik ke nodes
nodes_metrics <- tibble(
id = as.integer(V(g)$name),
label = V(g)$label,
degree = as.numeric(deg),
betweenness = as.numeric(btw),
community = as.factor(comm)
)
# Skala ukuran node dari degree
nodes_metrics <- nodes_metrics %>%
mutate(size = scales::rescale(degree, to = c(4, 18)))
# Gabungkan bobot edge untuk ketebalan
edges_plot <- as_tibble(get.data.frame(g)) %>%
rename(from = from, to = to) %>%
mutate(width = scales::rescale(weight, to = c(0.3, 2.5)))
## Warning: `get.data.frame()` was deprecated in igraph 2.0.0.
## ℹ Please use `as_data_frame()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
# Konversi ke tidygraph untuk ggraph
tg <- tbl_graph(nodes = nodes_metrics, edges = edges_plot, directed = FALSE)
p <- ggraph(tg, layout = "fr") +
geom_edge_link(aes(width = width), alpha = 0.4, colour = "grey40") +
geom_node_point(aes(size = size, color = community), alpha = 0.9) +
geom_node_text(aes(label = label), repel = TRUE, size = 3) +
scale_edge_width(range = c(0.2, 2.5), guide = "none") +
scale_size_identity() +
labs(title = "Network Graph (Louvain Communities & Degree Size)",
subtitle = "Ukuran node ~ degree | Warna ~ komunitas | Ketebalan edge ~ bobot",
x = NULL, y = NULL) +
theme_graph(base_family = "") +
theme(legend.position = "right")
print(p)
# Siapkan data sesuai format visNetwork
vn_nodes <- nodes_metrics %>%
transmute(id = id,
label = label,
group = community,
value = degree, # kontrol ukuran relatif
title = paste0(
"<b>", label, "</b>",
"<br>Degree: ", degree,
"<br>Betweenness: ", round(betweenness, 3),
"<br>Community: ", community
))
vn_edges <- edges_plot %>%
transmute(from = as.integer(from),
to = as.integer(to),
value = weight,
title = paste0("Weight: ", weight))
vn <- visNetwork(vn_nodes, vn_edges, width = "100%", height = "620px") %>%
visIgraphLayout(layout = "layout_with_fr") %>% # layout gaya igraph
visEdges(smooth = FALSE, color = list(opacity = 0.5)) %>%
visLegend(useGroups = TRUE, position = "right") %>%
visOptions(highlightNearest = list(enabled = TRUE, degree = 1),
nodesIdSelection = TRUE) %>%
visInteraction(hover = TRUE, dragNodes = TRUE, zoomView = TRUE) %>%
visPhysics(stabilization = TRUE)
vn
Radar/Spider chart
library(fmsb) # radar chart dasar
data_single <- data.frame(
Komunikasi = c(10, 0, 8),
Kepemimpinan = c(10, 0, 6),
Analisis = c(10, 0, 9),
Kreativitas = c(10, 0, 7),
Kolaborasi = c(10, 0, 5)
)
rownames(data_single) <- c("Max", "Min", "Profil A")
radarchart(
data_single,
axistype = 1,
pcol = rgb(0.2, 0.5, 0.8, 0.9),
pfcol = rgb(0.2, 0.5, 0.8, 0.35),
plwd = 3,
cglcol = "grey70",
cglty = 1,
cglwd = 0.8,
axislabcol = "black",
caxislabels = seq(0, 10, 2),
vlcex = 0.9,
title = "Radar Chart – Profil A"
)
data_multi <- data.frame(
Komunikasi = c(10, 0, 8, 6, 7),
Kepemimpinan = c(10, 0, 6, 9, 5),
Analisis = c(10, 0, 9, 7, 6),
Kreativitas = c(10, 0, 7, 8, 5),
Kolaborasi = c(10, 0, 5, 7, 8)
)
rownames(data_multi) <- c("Max", "Min", "Orang A", "Orang B", "Orang C")
radarchart(
data_multi,
axistype = 1,
pcol = c("#e41a1c", "#377eb8", "#4daf4a"),
pfcol = c(
rgb(228/255, 26/255, 28/255, 0.3),
rgb(55/255, 126/255, 184/255, 0.3),
rgb(77/255, 175/255, 74/255, 0.3)
),
plwd = 2,
cglcol = "grey70",
cglty = 1,
cglwd = 0.8,
axislabcol = "black",
caxislabels = seq(0, 10, 2),
vlcex = 0.85,
title = "Radar Chart – Perbandingan Tiga Profil"
)
legend("topright",
legend = c("Orang A", "Orang B", "Orang C"),
bty = "n",
pch = 20,
col = c("#e41a1c", "#377eb8", "#4daf4a"),
text.col = "black", cex = 0.9)
