Hypotheses The Effectiveness Of Student Teams-Achievement Divisions (Stad) Technique On Students’ Reading Comprehension (A Quasi Experimental Study At Second Grade Students Of Smp Islam Ruhama Ciputat)

D. The Technique of Data Collecting One important thing in the research is the technique of data collecting that can determine the results of the research. The techniques of collecting data which are used in this research are pre-test and post test: a. Pre-test The pre-test was given by the writer in the beginning of attending class VIII to know the students’ knowledge of the material that will be taught. b. Post-test The writer gave the students post-test for the class after lesson finished. The test was consisted of 30 questions, they are multiple choice. Before the writer giving the pre-test to the classes, she did the validity the test to other object. The validity of a test is the extent to which it measures what it is supposed to measure. The test must aim to provide a true measure of the particular skill which it is intended to measure, to the extent that it measures external knowledge and other skills at the same time. To analyze the validity, the writer has to give the test to the tester to take the score. After getting the score, the writer has to make the ranking from the highest up to the lowest score and make the group of upper, middle, lower. The respondent that would be analyzed is the upper and lower with 27 respondent of both. After getting the respondent, the writer would use instrument of validity as follows: 1. Item Discriminating Power Discriminating power used to differentiate between intelligent and unintelligent students. The good item question is item which is answered truly by the upper students and false by the lower students. The more upper students answer truly, the more lower answer falsely, the better the item will be. The formulation to know the discriminating is: D = Discriminating power Correct U = Correct answer of upper group Correct L = Correct answer of lower group N = Sum of upper and lower group There are some criteria on discriminating power: Table 3.1 Criteria of Discriminating Power DP Quality Recommendation 1.0 - 0.40 Excellent Retain 0.30 - 0.39 Good Possibilities for improvement 0.20 - 0.29 Mediocre Need to checkreview 0.00 - 0.19 Poor DiscardReview in Depth -0.01 Worst Definitely Discard 2. The Difficulty Level Difficulty level used to know how difficult or easy the item for students. The more students answer the questions truly, the easier the item will be. The formulation to know the difficulty level is: DL = Difficulty Level Correct U = Correct answer of upper group Correct L = Correct answer of lower group N = Sum of upper and lower group There are some criteria of difficulty level, as follows: Table 3.2 Criteria of Difficulty Level The writer did the validity of pre-test at SMP YMJ Ciputat with 25 students. Therefore, the writer took 27 of 25 students that are 7 students for upper and lower. The result shows that from 30 questions of multiple choices, the item that is not valid is number 14, 16, 21, 23, 24, 25, 29. Therefore, the writer revised the item before testing the pre-test to the sample. After giving the pre-test, the writer applied the cooperative learning with STAD technique in teaching reading to the experiment class. Meanwhile in the controlled class, the writer applied the presentation technique as teacher usually used. Finally before giving the post test, the writer did the validity of post test to the other class, except controlled and experiment class at SMP Islam Ruhama. Post test has the different item with pre test, but it also consist of 30 multiple items. The validity of post test showed that there is no item that is worse and poor, but it should only to be reviewed. After doing the validity of post test, the writer gave the post test and took the scores. 3. Normality The writer also did the normality test to the data of pre-test and post- test. Inductive statistic needs a distribution model to measure the population parameter. Therefore, before doing hypothesis test, it is important to test the Difficulty Level 0.00 - 0.30 Very Difficult 0.31 - 0.50 Moderately Difficult 0.51 - 0.70 Medium Difficult 0.71 - 0.80 Moderately Easy 0. 80 Very Easy distribution normality which is used as sample from the population. The writer used normality test of Lillyfors. E. The Technique of Data Analysis Analyzing the data is the last step in the procedure of experiment, in this case processing the data. Data processing is the step to know the result of both the experiment class and control class and also their differences. The writer used t-test formula to analyze the difference score of students’ achievement in reading comprehension with cooperative learning and without it. According to Sudijono, the formulation of t o is as follow 1 : M 1 : Mean of Variable X experiment class M 2 : Mean of Variable Y controlled class : Standard Error of Different Mean of Variable X and Y Before using t-test formula, the researcher has to seek some formula below: a. Determining Mean of Variable X Variable I, with formula: ∑ b. Determining Mean of Variable Y Variable II, with formula: ∑ 1 Anas Sudijono, Pengantar Statistik Pendidikan, Jakarta: PT Raja Grafindo Persada, 2010, p. 347. c. Determining Standard Deviation of Variable I, with formula: √ ∑ ∑ d. Determining Standard Deviation of Variable II, with formula: √ ∑ ∑ e. Determining Standard Error Mean Variable I, with formulation: √ f. Determining Standard Error Mean Variable II, with formulation: √ g. Determining Standard Error of Different Mean of Variable X and Variable Y, with formulation: √ F. The Testing of Hypothesis Before deciding the result of hypothesis, the writer followed the assumptions as the statistic hypothesis. As Budi Susetyo stated: 2 If T o t t : The null hypothesis H o is rejected; on the contrary the alternative hypothesis H a is accepted. It means that between variable x and y is significance. 2 Budi Susetyo, Statistika untuk Analisis Data Penelitian, Bandung: PT. Refika Aditama, 2010, p. 144. If T o t t : The null hypothesis H o is accepted; on the contrary the alternative hypothesis H a is rejected. It means that between variable x and y is not significance. 42 CHAPTER IV RESEARCH FINDINGS

A. The Description of Data

After conducting the research, the writer obtained two kinds of data, the scores of pre-test and post-test. The score of pre-test and post test of the experimental class can be seen at appendix 14, page 161. Based on the table at appendix 14, page 161, the highest students’ score in the experimental class was 93 obtained by two students. Meanwhile, the lowest students’ score in the experimental class was 46 obtained by one student. From the differences score obtained between the highest students’ score was 93 and the lowest students’ score was 46, it can be concluded that there was an affect of reading through STAD technique. The score of pre-test and post test of the controlled class can be seen at appendix 15, page 162. Based on the table at appendix 15, page 162, it shows that the highest students’ score in the controlled class was 90 obtained by two students. Meanw hile the lowest students’ score in this class was 40 obtained by one student. Those differences showed that there was a positive effect of STAD that is used in the experimental class.

B. Analysis of Data

Before analyzing the data, the writer did the normality test of data by using Lillyfors model distribution normality. The writer used the degree of significance 0.05 with N was 31. So that the T table was 0.16. She tested the normality to the pre-test and post-test of experimental class and controlled class. The hypothesis of normality was: H o : Population X has normal distribution probability H 1 : Population X has no normal distribution probability The criteria of test was: H o is accepted if T 0.16 H o is rejected if T 0.16 The result is as follows: a. Normality of pre-test experimental class The normality of pre-test in the experimental class showed that T value was 0.1144, see appendix 16, page 163. It means that T 0.16 and H o is accepted. The data of pre-test in experimental class has normal distribution probability, see appendix 12. b. Normality of post-test experimental class The normality of post-test in the experimental class showed that T value was 0.066, see appendix 17, page 164. It means that T 0.16 and H o is accepted. The data of post-test in the experimental class has normal distribution probability, see appendix 13. c. Normality of pre-test controlled class The normality of pre-test in the controlled class showed that T value was 0.1336, see appendix 18, page 165. It means that T 0.16 and H o is accepted. The data of pre-test in the controlled class has normal distribution probability, see appendix 14. d. Normality of post-test controlled class The normality of post-test in the controlled class showed that T value was 0.0936 see appendix 19, page 166. It means that T 0.16 and H o is accepted. The data of pre-test in the controlled class has normal distribution probability, see appendix 15. Before the writer calculating the t value of the observation, the writer would like to calculate some formula: a. Determining Mean, Standard Deviation and Standard Error of Mean Variable I: Table 4.1 The Score of Mean, Standard Deviation and Standard Error of Mean Variable I Skor F X x’ fx’ fx’ 2 86 – 93 3 89.5 +3 +6 27 78 – 85 10 81.5 +2 +20 40 70 – 77 11 73.5 +1 +11 11 62 – 69 3 65.5 54 – 61 2 57.5 -1 -2 2 46 – 53 2 49.5 -2 -4 8 N = 31 ∑ = 34 ∑ = 88 1. Determining Mean of Variable X Variable I, with formula: ∑ 2. Determining Standard Deviation of Variable I, with formula: √ ∑ ∑ √ √ √ 3. Determining Standard Error Mean Variable I, with formulation: √