Lembaga : Universitas Islam Negeri Maulana Malik Ibrahim Malang
Fakultas : Sains dan Teknologi
Program Studi : Teknik Informatika
Mata Kuliah : Linear Algebra (C)
Relasional data set merupakan kumpulan item data yang memiliki perpaduan atau hubungan yang telah ditentukan sebelumnya. Berbagai item ini diatur sebagai satu set tabel menggunakan kolom dan baris. Tabel digunakan untuk menyimpan informasi tentang objek yang ditampilkan dalam database. Tiap kolom dalam tabel memuat tipe data ekskusif , dan bidang tersebut menyimpan nilai aktual atribut. Baris dalam tabel mempresentasikan perpaduan nilai terkait berdasarkan satu objek atau entitas. Tiap baris pada tabel dapat ditandai dengan pengidentifikasi unik yang disebut kunci utama (keyword), dan baris di antara beberapa tabel dapat dibuat saling terkait menggunakan kunci asing. Berikut tahapan dalam menerapkan relasional data set pada RStudio menggunakan bahasa pemrograman R.
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.1.3
## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.6 v dplyr 1.0.8
## v tidyr 1.2.0 v stringr 1.4.0
## v readr 2.1.2 v forcats 0.5.1
## Warning: package 'ggplot2' was built under R version 4.1.3
## Warning: package 'tibble' was built under R version 4.1.3
## Warning: package 'tidyr' was built under R version 4.1.3
## Warning: package 'readr' was built under R version 4.1.3
## Warning: package 'purrr' was built under R version 4.1.3
## Warning: package 'dplyr' was built under R version 4.1.3
## Warning: package 'forcats' was built under R version 4.1.3
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
data_mahasiswa <- data.frame(
NIM = c(210605110045, 210104110151, 210503110075, 210104110030, 210104110016, 210104110070, 210606110024, 210301110045, 210201110156, 210202110144, 210201110002, 21030111015, 210401110025, 210203110082, 210201110201, 210104110153, 210301110002, 210701110007, 210301110178, 210602110083,
210602110080
),
Nama = c("Aisya Gusti savila","Maulida Musyarofah","Moira Calila Naifa","Rahma Alfariza","Jenar Meisa Ayu","Elfina Sabilia Rajabi","Farah Fadillah","Puspa dewi","Mutiara Zafirah","zakiatuz Zahro","Alivia lailatur","Siti Rosyidatul Abidah","Fitria Susanti","Kania Tri Andayani","Hajratul aswad","Vidyalies Rakasawi","Muhammad Rizky","Zidan Ramadhan","Ahmad Maulana","Sitti Umamah","Muhammad yusuf"
),
stringsAsFactors = FALSE)
data_mahasiswa
data_Prodi <- data.frame(
NIM = c(210605110031, 210104110151, 210503110075, 210104110030, 210104110016, 210104110070, 210606110024, 210301110045, 210201110156, 210202110144, 210201110002, 21030111015, 210401110025, 210203110082, 210201110201, 210104110153, 210301110002, 210701110007, 210301110178, 210602110083, 210602110080
),
Nama = c("Teknik Informatika", "Ilmu Tafsir Al-Quran", "Pendidikan Dokter", "Ilmu Perpustakaan Dan Informasi", "Manajemen pendidikan islam", "Pendidikan Bahasa Arab", "Hukum Ekonomi Syariah", "Hukum Ekonomi Syariah", "Psikologi", "Sastra Inggris", "Pendidikan Agama Islam", "Manajemen Pendidikan Islam", "Teknik Informatika", "Akuntansi", "Teknik Informatika", "Biologi", "Teknik Arsitektur", "Pendidikan Dokter", "Bahasa Sastra Arab", "Psikologi", "Biologi"
),
stringsAsFactors = FALSE)
data_Prodi
library(dplyr)
Nama14 <- merge(
x = data_mahasiswa,
y = data_Prodi,
by = 'NIM',
all = TRUE
)
Nama14
Alamat1 <- data.frame(
NIM = c(210605110045, 210104110151, 210503110075, 210104110030, 210104110016, 210104110070, 210606110024, 210301110045, 210201110156, 210202110144, 210201110002, 21030111015, 210401110025, 210203110082, 210201110201, 210104110153, 210301110002, 210701110007, 210301110178, 210602110083, 210602110080
),
Alamat = c("Duren sawit", "Muara Angke", "Kemang", "Payaraman", "Bima", "Sungai Lilin Muba", "Cawang", "Pasar baru", "Priok", "Kelekar Muara Enim", "Meranjat Ogan Ilir", "Merjosari", "Kemang", "Rawamangun", "Banyuasin", "Lubuk Linggau", "Cakung", "Muara Kelingi", "Rambutan", "jatinegara", "Baturaja OKU"
),
stringsAsFactors = FALSE)
Alamat1
library(dplyr)
Namaa14 <- merge(
x = Nama14,
y = Alamat1,
by = 'NIM',
all = TRUE
)
Namaa14
innerJoin <- data_mahasiswa %>%
inner_join(data_Prodi, by = "NIM")
innerJoin
1.Aleft Join
leftjoin <- left_join(data_mahasiswa,data_Prodi)
## Joining, by = c("NIM", "Nama")
leftjoin
rightjoin <- right_join(data_mahasiswa
,data_Prodi)
## Joining, by = c("NIM", "Nama")
rightjoin
fulljoin <- full_join(data_mahasiswa,data_Prodi)
## Joining, by = c("NIM", "Nama")
fulljoin