add citation of Julia (#63)

Due to the JOSS submission: 

openjournals/joss-reviews#5786

paper/paper.bib

@@ -1,3 +1,17 @@
+@article{julia,
+  doi       = {10.1137/141000671},
+  url       = {https://doi.org/10.1137%2F141000671},
+  year      = 2017,
+  month     = {jan},
+  publisher = {Society for Industrial {\&} Applied Mathematics ({SIAM})},
+  volume    = {59},
+  number    = {1},
+  pages     = {65--98},
+  author    = {Jeff Bezanson and Alan Edelman and Stefan Karpinski and Viral B. Shah},
+  title     = {Julia: A Fresh Approach to Numerical Computing},
+  journal   = {{SIAM} Review}
+}
+
 @article{ashari2013performance,
   title={Performance comparison between Na{\"\i}ve Bayes, decision tree and k-nearest neighbor in searching alternative design in an energy simulation tool},
   author={Ashari, Ahmad and Paryudi, Iman and Tjoa, A Min},

paper/paper.md

@@ -22,7 +22,7 @@ bibliography: paper.bib
 
 # Summary
 
-SIRUS.jl[^1] is an implementation of the original Stable and Interpretable RUle Sets (SIRUS) algorithm in the Julia programming language.
+SIRUS.jl[^1] is an implementation of the original Stable and Interpretable RUle Sets (SIRUS) algorithm in the Julia programming language [@julia].
 The SIRUS algorithm is a fully interpretable version of random forests, that is, it reduces thousands of trees in the forest to a much lower number of interpretable rules (e.g., 10 or 20).
 With our Julia implementation, we aimed to reproduce the original C++ and R implementation in a high-level language to verify the algorithm as well as making the code easier to read.
 We show that the model performs well on classification tasks while retaining interpretability and stability.