Membuat scatterplot

coba = read.csv("C:/Users/user/Pictures/Nilai Mahasiswa.csv")

library(readr)
write_csv(coba,"...Nilai Mahasiswa.csv")

 Nilai_Mahasiswa = read.csv("...Nilai Mahasiswa.csv")
Nilai_Mahasiswa

##      Nama Quiz UTS UAS Tugas.1 Tugas.2 Tugas.3 Tugas.4 Tugas.5 Tugas.6
## 1   Hanin   80  90  80      75      90      75      85      70      90
## 2   Wasik   85  80  85      70      95      75      80      70      90
## 3 Attifah   90  85  90      75      85      75      80      75      90
## 4   Sapta   75  80  75      90      85      75      85      75      90
## 5    Rafi   70  90  70      85      80      75      80      75      90
##   Rata.rata
## 1  81.66667
## 2  81.11111
## 3  82.77778
## 4  81.11111
## 5  79.44444

library(mosaicCalc)

## Loading required package: mosaic

## Registered S3 method overwritten by 'mosaic':
##   method                           from   
##   fortify.SpatialPolygonsDataFrame ggplot2

## 
## The 'mosaic' package masks several functions from core packages in order to add 
## additional features.  The original behavior of these functions should not be affected by this.

## 
## Attaching package: 'mosaic'

## The following objects are masked from 'package:dplyr':
## 
##     count, do, tally

## The following object is masked from 'package:Matrix':
## 
##     mean

## The following object is masked from 'package:ggplot2':
## 
##     stat

## The following objects are masked from 'package:stats':
## 
##     binom.test, cor, cor.test, cov, fivenum, IQR, median, prop.test,
##     quantile, sd, t.test, var

## The following objects are masked from 'package:base':
## 
##     max, mean, min, prod, range, sample, sum

## Loading required package: mosaicCore

## 
## Attaching package: 'mosaicCore'

## The following objects are masked from 'package:dplyr':
## 
##     count, tally

## 
## Attaching package: 'mosaicCalc'

## The following object is masked from 'package:stats':
## 
##     D

gf_point(
  UAS ~ Nama, data = coba )  %>%
  gf_point(
    UTS ~ Nama, data = coba, color = "red") %>%
  gf_point(
    Rata.rata ~ Nama, data = coba, color = "blue")