This research is my undergraduate thesis focusing on the effect of fuel subsidy cut using Machine Learning in Big Data. The background came which fuel subsidy cut is an major effect in Indonesia and i wonder i can capture people behaviour (changing) of using transportation to work. The idea is i implementing SVM and Naive Bayes algorithm to classifiy people using public transportation and private vehicle. This work is collaborate with United Nations Global Pulse - Pulse Lab Jakarta to provides me tweets data. Due to the procedure that UN had, i cannot shared the data. Most of the scripts is written in python using IPython Notebook. And the dataset that i want to analyse is differentiate into two parts : before the event (fuel subsidy cut) and after the event. Will people changing their transportation to work considering about fuel price that rising? After that, i applicate regression analysis to have conclusion or brief understanding between the amount of public transportation user and private vehicle user. At the end, i visualize all of the result from the system by using D3JS Visualization.   For further discussion and information, please contact me at :  satya.nugraha@mail.ugm.ac.id , graha234@gmail.com   This work is still in progress, i hope that you can give me feedback or suggestion through the process of the project.