No X
Y X
2
Y
2
XY
33 113
91 12769
8281 10283
34 113
91 12769
8281 10283
35 113
85 12769
7225 9605
36 113
93 12769
8649 10509
37 113
90 12769
8100 10170
38 109
95 11881
9025 10355
39 109
94 11881
8836 10246
40 109
88 11881
7744 9592
41 106
91 11236
8281 9646
42 106
97 11236
9409 10282
43 106
85 11236
7225 9010
44 106
90 11236
8100 9540
45 106
58 11236
3364 6148
46 106
58 11236
3364 6148
47 106
82 11236
6724 8692
48 106
94 11236
8836 9964
49 106
90 11236
8100 9540
50 106
75 11236
5625 7950
51 106
72 11236
5184 7632
52 106
74 11236
5476 7844
53 106
66 11236
4356 6996
54 106
84 11236
7056 8904
55 97
84 9409
7056 8148
∑ 6424
4610 756478
392044 539702
To know the significance correlation between variables, the writer use Pearson’s Product Moment to analyze the correlation because the data
scale thatusing in this research is interval. In this part of this chapter the coeficient correlation Pearson and the significancey was calculated. And
the next step is test the hypothesis by comparing between score of r
hitung
from the distribution table of r. So, the result of the problem that formulated is gained here.
B. Analysis Data
After calculating data Variable X and Variable Y, the next calculation is input the data into Pearson Product Moment formula, as followed :
Next the data can be calculated as followed :
55.539702 64244610
2 2
55.756478 6424 55.392044
4610
xy
r
29683610 29614640 41606290 41267776 21562420 21252100
xy
r
68970 338514 310320
xy
x
r
68970
105047664480
68970 324110, 6
xy
r
0, 213
To interpret the data that gained, the writer use the criteria of coefficient correlation as a reference. It can be seen below :
Table 4.4 Interpretation of Product Moment Correlation
Coeficient Interval Degree of
Interpretation
0,00 - 0,199 Very Low
0,20 - 0,399 Low
0,40 - 0,599 Medium
0,60 - 0,799 Strong
. .
2 2
2 2
Y Y
N X
X N
Y X
XY r
xy
0,80 - 1,000 Very Strong
Sugiyono 2013 : 184.
44
C. Interpretation of Data
Based on the reference table and the calculation before it can be seen that the
correlation score between Intelligence Quotient and students‟ achievement is 0,213. Where the correlation score of 0,213 is included in
low coefficient, that is interval 0.20 – 0,399.
The next step is looking for the r score from the table significance. Based on the book of Sugiyono, from the total sample of 55 students the
significance is 5 and in 5 significance the score of r is 0,266.
45
D. The test of Hypothesis
To know the significance correlation between Intelligence Quotient and students‟ learning achievement at first grade year students of SMPIT Nurul
Fikri, so here is the analysis of Pearson correlation with formulation from hypothesis:
H
o
: There is no Significant correlation between intelligence quotient and students‟s learning achievement in English of First grade year students of
SMPIT Nurul Fikri.
44
Sugiyono, Statistika Penelitian, Bandung,2013 p.184
45
Sugiyono, Statistika Penelitian, Bandung,2013 p.333
H
a
:There is a significant correlation between intelligence quotient and students‟ learning achievement in English of first grade year students
SMPIT Nurul Fikri. The degree of error used in this test
α is 5, with the testing criteria rejected Ho if r
o
r
t .
and it will be accepted if r
o
r
t
. From the data proceeded the score of r
o
is 0,231 and the score of r
t
is 0,266. It can be seen that r
o
is 0,231 r
t
0,266 and it means accepted as the criteria from test of hypothesis that Ho is accepted and Ha is rejected, where based on the table
of interpretation product moment the result approximately is low. It can be concluded that there is a low significance correlation between intelligence
quotient and students‟ learning achievement in English of first grade year students at SMPIT Nurul Fikri.
