text: import pandas
  from sklearn import tree
  from sklearn.model_selection import cross_val_score
  
  def preparation():
      d = pandas.read_csv('Chapter01/dataset/kuli_ah_daring.csv', sep=",")
      d = d.sample(frac=1)
      print("ini dari fungsi sini gan : " +  str(len(d)))
      
      d_train = d[:35]
      d_test = d[35:]
      
      d_train_att = d_train.drop(['no'], axis=1) #fitur
      d_train_pass = d_train['no'] #label
      
      d_test_att = d_test.drop(['no'], axis=1)
      d_test_pass = d_test['no']
      
      d_att = d.drop(['no'], axis=1)
      d_pass = d['no']
  
      data = [[d_train_att, d_train_pass], [d_test_att, d_test_pass]]
      return data
      
  def training(d_train_att,d_train_pass):
      t = tree.DecisionTreeClassifier(criterion="entropy", max_depth=5)
      t = t.fit(d_train_att, d_train_pass)
      return t
  
  def testing(t,testdataframe):
      return t.predict(testdataframe)