Data Analysis

posttest compared with the results obtained in the pretest to determine whether there is an increase in student learning outcomes after being given treatment or no.

Then the results of rxy are compared with the price of r Product Moment with a significant level of 5%. If rxy> rtable with = 5% then the item is said to be valid or in other words, if the price is rxy < rtable, then the item is invalid. To make this study easier, the researchers used the SPSS application for Windows 32-bit Version 25.

b. Reliability

Arikunto in Lara Oktavia and Syahrul Ismet (2019: 75) Reliability refers to an understanding that an instrument is reliable enough to be used as a data collection tool because the instrument is good (Oktavia & Ismet, 2019). And according to Wagiran in Iis Ernawati and Totok Sukardiyono (2017: 206) the reliability test on a learning outcome test aims to determine the level of constancy in measuring what should be measured (Ernawati & Sukardiyono, 2017). To find out the reliability of the test with description questions, you can use the Alpha formula as follows (Yusup, 2018):

Where 𝑟_𝑖 = Reliability coefficient of Alfa Cronbach k = Number of item

∑𝑠_𝑖² = Number of variance scores for each item 𝑠_𝑡² = Total variance

Item variance dan total variance formulas:

𝑟

_𝑖

= 𝑘

𝑘 − 1 ቊ1 − ∑ 𝑠

_𝑖²

𝑠

_𝑡²

ቋ

𝑠

_𝑖²

=

^𝐽𝐾𝑖

𝑛

−

^𝐽𝐾𝑠

𝑛²

𝑠

_𝑡²

= ∑𝑥

_𝑡²

𝑛 − ሺ∑𝑥

_𝑡

ሻ

²

𝑛

²

Where 𝑠_𝑖² = Variance each item

JKi = Sum of squares of all item JKs = Sum of squares of the subject n = Number of respondent

𝑥_𝑡² = Total varience 𝑥_𝑡 = Total score

If Cronbach's Alfa reliability coefficient is more than 0.70 (ri > 0.70), so an instrument can be said to be reliable or not more than 0.90 (ri < 0.9) (Yusup, 2018). Furthermore, if Cronbach's Alfa reliability coefficient is less than 0.70 (ri <

0.70), then the instrument must be revise or if it is more than 0.90 (ri < 0.90) then the number of questions must be revise too.

2. Descriptive analysis

The data that has been obtained is then analyzed descriptively with the aim of describing the important things of the object under study. The data description of the research variables would be carried out with sample data that had been obtained in the field. The description in question is the distribution of frequency, mean, median, mode, range, category and percentage of each variable. The general description of the data is obtained from the help of SPSS version 25.0 for windows 23 bit.

3. Inferential statistics

Inferential statistics is a means to assist researchers in analyzing data by testing the research hypotheses proposed by researchers and built from theoretical studies. Before conducting inferential statistical tests, it is necessary to test assumptions first.

a. Assumption test

Assumption test is carried out to determine the type of statistics used.

Parametric statistics require the fulfillment of many assumptions. The first assumption is that the data must be normally distributed, homogeneous, and the next test is to fulfill the assumption of linearity.

1) Normality test

This normality test was carried out by researchers to determine whether the data obtained are normal or not. This is because before testing the hypothesis the sample data must come from a distributed population.

In this study, researchers tested the normality of the data using the Kolmogorov-Smirnov test. As a guide for decision making, if the significance value or probability value is greater than or (Sig. > = 0.05), the research data is normally distributed. Skewness-Kurtosis test, the guideline is data that is normally distributed has a Skewness value close to 0, so it has a slope that tends to be balanced. Researchers will use a computer program SPSS 25.0 for windows in the normality test to make the testing process easier.

2) Homogeneity test

The homogeneity test aims to determine whether the data obtained are homogeneous or not (Usmadi, 2020). This homogeneity test uses the help of a computer program SPSS 25.0 for windows at a significance level of 5%. If the significance value (sig) < 0.05, the data comes from a population that has a non-homogeneous variance. Furthermore, if the significance value (sig) 0.05, the data comes from a population that has a homogeneous variance.

3) Linearity test

The linearity test aims to determine whether two variables have a linear relationship or not. Researchers used SPSS version 25.0 for windows program to make testing easier. The linearity test can be known by looking at the probability value of Sig. on the deviation from linearity at a significant level of 5%. The test criteria are as follows:

a) If the significance value (sig) < 0.05, then there is no linear relationship.

b) If the significance value (sig) 0.05, then there is a linear relationship.

b. Hypothesis testing

The t-test aims to determine whether or not there is a significant effect of the independent variable partially on the dependent variable. With the criteria of (2-tailed) paired sample T-test, if (Sig.>0.05) then H0 is accepted and Hi is rejected, in other words there is no significant difference of the student learning outcomes of reading comprehension after the application of blended learning using the Quizizz application. If (Sig.<0.05) then H0 is rejected and Hi is accepted, in other words, there is a significant difference of the student learning outcomes of reading comprehension after the application of blended learning using the Quizizz application. In this research, researchers used the help of SPSS version 25.0 for 32-bit windows to make testing easier.

4. Classifying the score of the student

After the data is collected through the pretest, posttest and distributing questionnaires, the researcher will classify the scores obtained by students. The classification of scores obtained by students as listed in the table below:

Scoring the result of the students’ test.

a. Classifying the score of the students

Table 3.3 Scoring classification of student learning outcomes in reading

No Classification Score

1 Excellent ≥ 95

2 Very good 80 – 94

3 Good 75 – 79

4 Fairly Good 60-74

5 Poor 50-59

6 Fairly Poor 0-49

Source: Kemendikbud 2017 b. Analyzing the data of the students’ interest by using Likert Scale

Table 3.4 Likert Scale

Positive Statement Negative Statement

Score Category Score

5 Strongly Agree 1

4 Agree 2

3 Undecided 3

2 Disagree 4

1 Strongly Disagree 5

Source: Sugiyono in (Sunarsi, 2018:6) The number of questions that will be used in the questionnaire is 20 questions. To measure the level of students' interest in learning English of the implementation of the Blended Learning method with the Quizizz application.

𝑆𝑐𝑜𝑟𝑒 =𝑆𝑡𝑢𝑑𝑒𝑛𝑡𝑠 𝐶𝑜𝑟𝑟𝑒𝑐𝑡 𝐴𝑛𝑠𝑤𝑒𝑟

𝑇𝑜𝑡𝑎𝑙 𝐼𝑡𝑒𝑚 𝑥10

Which there 10 positive questions and 10 negative questions. So, the highest score is 100 and the lowest score is 20. For the classification of scores as shown in the following table:

Tabel 3.5 The classification score for the questionnaire

Classification Score

69-85 Strongly Interested

56-68 Interested

43-55 Moderate

30-42 Uninterested

17-29 Strongly Uninterested

57 CHAPTER IV

FINDING AND DISCUSSION