library(readxl)
data_iklim = read_excel("D:/analitika data/data_iklim_kabtegal.xlsx")
View(data_iklim)
suhu_udara = data_iklim$suhu.udara
kecepatang_angin = data_iklim$kecepatan.angin
tekanan_udara = data_iklim$tekanan.udara
curah_hujan = data_iklim$curah.hujan
kelembaban_udara = data_iklim$kelembaban.udara
hari_penelitian = data_iklim$hari.penelitian
model_reg_curah_hujan <- lm(curah_hujan ~ suhu_udara + kecepatang_angin + tekanan_udara + kelembaban_udara , data = data_iklim)
par(mfrow = c(2,2))
plot(model_reg_curah_hujan)
library(car)
## Loading required package: carData
vif(model_reg_curah_hujan)
## suhu_udara kecepatang_angin tekanan_udara kelembaban_udara
## 1.176385 1.012437 1.713343 1.514745
par(mfrow = c(2,2))
plot(model_reg_curah_hujan)
library(lmtest)
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
dwtest(model_reg_curah_hujan)
##
## Durbin-Watson test
##
## data: model_reg_curah_hujan
## DW = 1.0556, p-value = 0.0006618
## alternative hypothesis: true autocorrelation is greater than 0
library(conf)
crPlots(model_reg_curah_hujan)
summary(model_reg_curah_hujan)
##
## Call:
## lm(formula = curah_hujan ~ suhu_udara + kecepatang_angin + tekanan_udara +
## kelembaban_udara, data = data_iklim)
##
## Residuals:
## Min 1Q Median 3Q Max
## -221.34 -64.42 -12.25 59.18 239.97
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -21795.566 18984.924 -1.148 0.260
## suhu_udara -19.112 23.473 -0.814 0.422
## kecepatang_angin 16.047 19.856 0.808 0.425
## tekanan_udara 19.791 18.349 1.079 0.289
## kelembaban_udara 29.052 3.893 7.463 2.08e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 102.3 on 31 degrees of freedom
## Multiple R-squared: 0.7017, Adjusted R-squared: 0.6632
## F-statistic: 18.23 on 4 and 31 DF, p-value: 8.532e-08
predict(model_reg_curah_hujan);
## 1 2 3 4 5 6 7
## 417.493179 396.658284 293.899301 226.230737 191.536523 273.065898 114.833337
## 8 9 10 11 12 13 14
## 24.294416 36.846009 66.172683 179.326410 263.236504 215.592208 511.642773
## 15 16 17 18 19 20 21
## 270.485309 217.839061 121.481014 121.894335 31.667379 -8.315127 -51.081237
## 22 23 24 25 26 27 28
## -86.053655 49.927671 98.269663 374.393709 326.022298 306.593660 225.891166
## 29 30 31 32 33 34 35
## 103.778867 106.235149 78.151448 13.422780 20.179932 -77.781162 -9.625999
## 36
## 187.380478
prediksi_data = data.frame(suhu_udara,kecepatang_angin,tekanan_udara,kelembaban_udara,curah_hujan,prediksi_curah_hujan=predict(model_reg_curah_hujan));
library(dplyr)
##
## Attaching package: 'dplyr'
## The following object is masked from 'package:car':
##
## recode
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
prediksi_data = prediksi_data%>% mutate(selisih=abs(curah_hujan-predict(model_reg_curah_hujan)));head(prediksi_data)
## suhu_udara kecepatang_angin tekanan_udara kelembaban_udara curah_hujan
## 1 28.3 4 1009.23 93.5 403.152
## 2 27.8 3 1010.12 92.4 437.673
## 3 27.3 2 1010.10 89.1 165.945
## 4 29.3 4 1010.22 86.9 119.991
## 5 28.5 3 1010.12 85.8 95.571
## 6 28.3 5 1010.81 86.9 51.726
## prediksi_curah_hujan selisih
## 1 417.4932 14.34118
## 2 396.6583 41.01472
## 3 293.8993 127.95430
## 4 226.2307 106.23974
## 5 191.5365 95.96552
## 6 273.0659 221.33990
library(DT)
data_iklim <- readxl::read_excel("D:/analitika data/data_iklim_kabtegal.xlsx")
datatable(data_iklim, options = list(pageLength = 10))
library(plotly)
## Loading required package: ggplot2
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
plot_ly(data_iklim, x = ~hari_penelitian, y = ~curah_hujan, type = "scatter", mode = "lines+markers") %>%
layout(title = "Curah Hujan di Kabupaten Tegal")