Difference between revisions of "R"

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R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, data mining surveys and studies of scholarly literature databases, show substantial increases in popularity in recent years. As of August 2018, R ranks 18th in the TIOBE index, a measure of popularity of programming languages.
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R adalah bahasa pemrograman dan lingkungan perangkat lunak bebas untuk komputasi statistik dan grafik yang didukung oleh R Foundation for Statistical Computing. Bahasa R banyak digunakan di kalangan ahli statistik dan data miner untuk mengembangkan perangkat lunak statistik dan analisis data. Jajak pendapat, survei penambangan data dan studi basis data literatur ilmiah, menunjukkan peningkatan popularitas yang cukup besar dalam beberapa tahun terakhir. Pada Agustus 2018, R peringkat ke-18 dalam indeks TIOBE, ukuran popularitas bahasa pemrograman.
  
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A GNU package, source code for the R software environment is written primarily in C, Fortran and R itself and is freely available under the GNU General Public License. Pre-compiled binary versions are provided for various operating systems. Although R has a command line interface, there are several graphical user interfaces, such as RStudio, an Integrated development environment.
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Paket GNU, source code untuk lingkungan perangkat lunak R ditulis terutama di C, Fortran dan R sendiri dan tersedia secara gratis di bawah GNU General Public License. Versi biner pre-compiled disediakan untuk berbagai sistem operasi. Meskipun R hanya menggunakan command line interface, ada beberapa antarmuka pengguna grafis, seperti RStudio, lingkungan pengembangan terintegrasi.
  
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==Referensi==
  
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* https://r.analyticflow.com/en/ -- '''R Rasa Orange'''
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* http://www.rexamples.com/
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* http://www.sthda.com/english/articles/32-r-graphics-essentials/
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* https://www.tidytextmining.com/
  
 
==Pranala Menarik==
 
==Pranala Menarik==
  
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* [[R: Install di Ubuntu 18.04]]
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* [[R: Install di Ubuntu 20.04]]
 
* [[R: Install di Ubuntu]]
 
* [[R: Install di Ubuntu]]
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* [[R: Install java]]
 
* [[R: Menggunakan library CRAN]]
 
* [[R: Menggunakan library CRAN]]
 
* [[R: Matematika Dasar]]
 
* [[R: Matematika Dasar]]
 
* [[R: Tipe Data - Numeric Character Logical]]
 
* [[R: Tipe Data - Numeric Character Logical]]
 
* [[R: ls dan ls.str untuk melihat daftar variable dan isinya]]
 
* [[R: ls dan ls.str untuk melihat daftar variable dan isinya]]
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* [[R: garbage cleanup]]
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* [[R: sort]]
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===Data===
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* [[R: Dataset]]
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* [[R: data]]
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* [[R: Melihat Informasi dari data set]]
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* [[R: Import]]
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* [[R: Export]]
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===R Studio===
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* https://gist.github.com/ElToro1966/999f1c8ca51a75648dd587a3170e4335
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* http://web.cs.ucla.edu/~gulzar/rstudio/basic-tutorial.html
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* [[RStudio: Install]]
  
 
===File Processing===
 
===File Processing===
  
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* [[R: operasi file]]
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* [[R: readtext]]
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* [[R: read PDF]]
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* [[R: read CSV]]
 
* [[R: Read File]]
 
* [[R: Read File]]
 
* [[R: multiread file]]
 
* [[R: multiread file]]
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* [[R: save dan load data]]
  
 
===Text Processing===
 
===Text Processing===
  
 
* [[R: Package Pendukung Text Processing]]
 
* [[R: Package Pendukung Text Processing]]
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* [[R: twitter persiapan]]
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* [[R: stopwords]]
 
* [[R: Text Vector]]
 
* [[R: Text Vector]]
 
* [[R: tidy text dataset - tibble]]
 
* [[R: tidy text dataset - tibble]]
 
* [[R: contoh DataframeSource]]
 
* [[R: contoh DataframeSource]]
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* [[R: wordcloud]]
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* [[R: wordcloud dari dua sumber]]
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* [[R: evaluasi twit]]
 
* [[R: bigram]]
 
* [[R: bigram]]
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* [[R: bigram 2]]
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* [[R: trigram]]
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* [[R: ngram dan frekuensi-nya]]
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* [[R: term frequency tf dan inverse document frequency idf]]
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* [[R: ngram word clouds]]
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* [[R: spam classification]]
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====Referensi====
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* https://tm4ss.github.io/docs/Tutorial_2_Read_data_Zipf.html
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===TidyText Processing===
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Ref: https://github.com/dgrtwo/tidy-text-mining
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tidy data has a specific structure:
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* Each variable is a column
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* Each observation is a row
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* Each type of observational unit is a table
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* [[R: read multi PDF ke tidytext]]
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* [[R: tidytext data frame]]
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* [[R: tidytext Jane Austen Book]]
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* [[R: sentiments analysis]]
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* [[R: tidytext RPJP BAPPENAS]]
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* [[R: tidytext NASA data]]
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* [[R: tidytext analisa twitter]]
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* [[R: tidytext: tidytext]]
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* [[R: tidytext: tidytext hgwells]]
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* [[R: tidytext: bronte]]
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* [[R: tidytext: compare text]]
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* [[R: tidytext: tweet trump]]
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* [[R: tidytext: sentiment analysis basic]]
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* [[R: tidytext: sentiment comparing the three sentiment dictionaries]]
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* [[R: tidytext: sentiment Most common positive and negative words]]
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* [[R: tidytext: sentiment wordcloud]]
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* [[R: tidytext: tf-idf Jane Austen novels]]
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* [[R: tidytext: tf-idf corpus of physics texts]]
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* [[R: tidytext: word-combinations Tokenizing by n-gram]]
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* [[R: tidytext: document-term-matrices-mining financial articles]]
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* [[R: tidytext: topic-modelling]]
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===Bayesian===
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* http://www.bnlearn.com/
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* https://www.r-bloggers.com/text-message-classification/
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* https://www.r-bloggers.com/bayesian-network-in-r-introduction/
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* https://cran.r-project.org/web/packages/BayesianNetwork/vignettes/BayesianNetwork.html
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* http://www.di.fc.ul.pt/~jpn/r/bayesnets/bayesnets.html
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===Time Series===
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* https://a-little-book-of-r-for-time-series.readthedocs.io
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* https://www.statmethods.net/advstats/timeseries.html
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* https://a-little-book-of-r-for-biomedical-statistics.readthedocs.io
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* [[R: time series]]
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* [[R: Rserve]]
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* [[R: ARDUINO dengan RServe]]
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* [[R: Stock Prices Prediction Using Machine Learning and Deep Learning Techniques with Python codes]]
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===Regression Analysis===
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* [[R Regression: Dataset]]
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* [[R Regression: Simple Linear Regression]]
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* [[R Regression: Linear Regression]]
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* [[R Regression:  Categorical Variables]]
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* [[R Regression: multicollinearity essentials and vif]]
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* [[R Regression: stepwise regression essentials]]
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* [[R Regression: penalized regression essentials ridge lasso elastic.net]]
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* [https://www.youtube.com/watch?v=66z_MRwtFJM YOUTUBE: Simple Linear Regression in R]
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===Machine Learning===
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* [[R ML: Load Dataset]]
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* [[R Regression: Logistic Regression]]
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* [https://www.youtube.com/watch?v=C4N3_XJJ-jU YOUTUBE: Logistic Regression in R]
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* [https://www.youtube.com/watch?v=SeyghJ5cdm4 YOUTUBE: Machine Learning with R]
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===Graphics===
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* [[R Plot: Basics]]
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* [[R Plot: multiple time series data]]
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* [[R Plot: ggplot2 extensions for ts objects]]
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* [https://www.youtube.com/watch?v=SjcUlHh3UJg YOUTUBE: Introduction to Plotting in R]
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* [https://www.youtube.com/watch?v=Z3V4Pbxeahg YOUTUBE: How to plot multiple graphs in R]

Latest revision as of 12:50, 10 May 2020

R adalah bahasa pemrograman dan lingkungan perangkat lunak bebas untuk komputasi statistik dan grafik yang didukung oleh R Foundation for Statistical Computing. Bahasa R banyak digunakan di kalangan ahli statistik dan data miner untuk mengembangkan perangkat lunak statistik dan analisis data. Jajak pendapat, survei penambangan data dan studi basis data literatur ilmiah, menunjukkan peningkatan popularitas yang cukup besar dalam beberapa tahun terakhir. Pada Agustus 2018, R peringkat ke-18 dalam indeks TIOBE, ukuran popularitas bahasa pemrograman.

Paket GNU, source code untuk lingkungan perangkat lunak R ditulis terutama di C, Fortran dan R sendiri dan tersedia secara gratis di bawah GNU General Public License. Versi biner pre-compiled disediakan untuk berbagai sistem operasi. Meskipun R hanya menggunakan command line interface, ada beberapa antarmuka pengguna grafis, seperti RStudio, lingkungan pengembangan terintegrasi.

Referensi

Pranala Menarik

Data

R Studio

File Processing

Text Processing

Referensi

TidyText Processing

Ref: https://github.com/dgrtwo/tidy-text-mining

tidy data has a specific structure:

  • Each variable is a column
  • Each observation is a row
  • Each type of observational unit is a table

Bayesian

Time Series


Regression Analysis

Machine Learning

Graphics

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