  This paper discusses the design of the system used for providing a solution
for the problem given at SemEval-2020 Task 9 where sentiment analysis of
code-mixed language Hindi and English needed to be performed. This system uses
Weka as a tool for providing the classifier for the classification of tweets
and python is used for loading the data from the files provided and cleaning
it. Only part of the training data was provided to the system for classifying
the tweets in the test data set on which evaluation of the system was done. The
system performance was assessed using the official competition evaluation
metric F1-score. Classifier was trained on two sets of training data which
resulted in F1 scores of 0.4972 and 0.5316.
