CHAPTER III: RESEARCH METHOD
D. Data Analysis
the score of each aspect was 3 points. It indicated that the test was practical for students. The practicality result can be seen in appendix 10.
2) Speaking test
The speaking test can be said to be practical if students do the test easily without any difficulties, the instructions do not make students confused and time allotment is appropriate for students.
The observation result when students were doing try out were none of students asked about the question. From 10 students, there were three students asked about the instructions. It can be concluded that the instructions and questions did not make students confused and easily to be understood. For time allocation, there were two students who have not finished preparing some points that will be conveyed when speak and there were three students felt nervous doing the test. As the result, the score of each aspect was 3 points. It showed that the test was practical for students. The practicality result can be seen in appendix 11.
1. Descriptive Statistic
In this study, descriptive statistics were employed to interpret scores. The students' data on speaking ability and vocabulary mastery were tested using score interpretation. The maximum, minimum, mean, range, and standard deviation must all be known in advance in order to create a scale or score for each variable.
2. Inferential Statistic
Correlation analysis is the method used to examine the associative hypothesis. The application of correlation analysis allows researchers to determine the direction, and significance of relationships between two or more variables. The steps involved in completing statistical analysis are listed below.
a. Normality Test
The purpose of the normality test is to ascertain whether or not the two variables have a normal distribution. The One-Sample Kolmogorov-Smirnov Test was used in this study as the normality test with the aid of SPSS. The normality test follows the rules that if p >
0.05, the distribution is considered normal, and if p < 0.05, the distribution is considered abnormal. It is possible to conclude that the data are normally distributed if the significance value is greater than 0.05.
b. Linearity Test
The linearity test was used to determine the linearity of the data, namely whether or not two variables have a linear relationship. In this research, the researcher used test of linearity from SPSS. The linearity follows the rules that if the sig. deviation from linearity > 0.05, the data is linear. Meanwhile, if the sig. deviation from linearity < 0.05, the data is not linear.
c. Pearson Product Moment Test
In this research, to analyze the data, the researcher used Pearson Product Moment because this research aimed to find out whether or not there was a significant positive relationship between students' vocabulary and speaking ability of eleventh grade culinary program at SMKN 3 JEMBER.
CHAPTER IV
DATA PRESENTATION AND ANALYSIS A. Data Description
The researcher conducted this research at SMKN 3 JEMBER, where the researcher used eleventh grade culinary students which consists of four classes. The researcher took eight students from culinary class 1, nine students from culinary class 2, eight students from culinary class 3, and eight students from culinary class 4. So, the total sample was 33 students. The researcher conducted the research in 5 meetings. The detail description as follows:
1. Description of the first meeting
The researcher conducted the vocabulary test and speaking test on 9 students of XI culinary 2. This first meeting was held on February, 21 2023 from 7 am. to 9 am. For the speaking test, the researcher used two inter rater namely the English teacher and the researcher. The researcher explained the instructions in detail to the students in order the students would not misunderstand.
2. Description of the second meeting
The researcher conducted the vocabulary test and speaking test on 8 students of XI culinary 1. This meeting was held on February, 23 2023 from 10 am. to 12 am. Before the students did the speaking test, the researcher explained the instructions clearly to the students.
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3. Description of the third meeting
The researcher conducted the vocabulary test and speaking test on 8 students of XI culinary 3 on February, 27 2023. This meeting was held from 10 am. to 11.30 am. For speaking test, the students individually came forward in front of class to speak up explained the procedure based on the topic they chose in 3 minutes.
4. Description of the fourth meeting
The researcher held the vocabulary test on 8 students of XI culinary 4 on March, 02 2023. This meeting took place from 7 am. to 8 am. The time allotment for the vocabulary test was 50 minutes.
5. Description of the fifth meeting
The researcher conducted the speaking test on 8 students of XI culinary 4 on March, 03 2023. This fourth meeting took place from 1.45 pm. to 2.30 pm. The researcher conveyed the clear instructions to the students. The researcher and the English teacher assessed the students’
speaking ability based on 3 aspects namely pronunciation, vocabulary, and fluency.
B. Data Presentation
In this section, the researcher would present the obtained data of eleventh grade culinary students. The presented data consisted of the result of vocabulary test and speaking test.
1. Students’ vocabulary mastery score
In this section, the researcher presented the vocabulary mastery score of 33 students of eleventh grade culinary program that chosen randomly from 4 classes. The students’ vocabulary mastery score as follows:
Table 4.1
The students’ vocabulary mastery score
No. Name Class Score
1. Rifqiya Amalina H. XI Culinary 2 75
2. Mohammad Iqbal M. XI Culinary 2 50
3. Edla Fatin XI Culinary 2 75
4. Yuda Putra Pratama XI Culinary 2 60
5. Nabilla Ayudya P XI Culinary 2 75
6. Dhining Arum Jati XI Culinary 2 95
7. Silmi Eloka Avanur XI Culinary 2 70
8. Alivia Cinta Maharani XI Culinary 2 75
9. Arsyad Ad Damsyiqi XI Culinary 2 60
10. Ganis Aulia Fitrah XI Culinary 1 40
11. Abdul Mukti Prayoga XI Culinary 1 65
12. Danil Setiawan XI Culinary 1 70
13. Adinda Anggun Gracia XI Culinary 1 60
14. Aisyah Miliyana XI Culinary 1 70
15. Aisa Agustin XI Culinary 1 70
16. Happy Margaretha XI Culinary 1 65
17. Aisyah Wardatul Jannah XI Culinary 1 55
18. Anisa Yanuarita XI Culinary 3 65
19. Annisa Adhisty XI Culinary 3 75
20. Rafif Pasha XI Culinary 3 45
21. Annisa Naila Ufa XI Culinary 3 60
22. Fitrah Aulia R. H. XI Culinary 3 70
23. Dinda Ayu Sri W. XI Culinary 3 65
24. Nabila Desti S XI Culinary 3 75
25. Putri Dewi Ambarwati XI Culinary 3 75
26. Aulina Maharani XI Culinary 4 40
27. Femi Amelia Lestari XI Culinary 4 80
28. Auril Zahra Islami Pasha XI Culinary 4 80
29. Aurea Nike Putri Kusuma XI Culinary 4 75
30. Valentina Resi Putri XI Culinary 4 80
31. Rizki Januar XI Culinary 4 75
No. Name Class Score
32. Aulia Izzati Abdillah XI Culinary 4 80
33. Kamila Riskianti XI Culinary 4 80
Average score 68.18
From the students’ vocabulary mastery score above, it is clearly showed that the minimum score is 40, the maximum score is 95, and the average score is 68.18. The result of vocabulary mastery statistic as follows:
Table 4.2
Statistic of Vocabulary Mastery Statistics
Vocabulary mastery
N Valid 33
Missing 0
Mean 68.18
Mode 75
Std. Deviation 12.236
Range 55
Minimum 40
Maximum 95
Sum 2250
From the table 4.2 above, it can be seen that the mean score is 68.18, the standard deviation is 12.236, the range is 55, the minimum score is 40, and the maximum score is 95. To know the amount of class (k), the researcher used Sturges formula:65
k = 1 + 3.3 log n
Where is the number of participants (33). Thus, the amount of class (k) = 1 + 3.3 log 33 = 5,98 (rounded to 6)
65 Sugiyono, Statistika untuk Penelitian, (Bandung: ALFABETA Bandung, 2007), 34.
Next, to know the interval class (i), the range is divided by the amount of class. It can be calculated as follows:
i = 55: 6 = 9.16 (rounded to 10)
The frequency distribution table of vocabulary mastery score can be seen in table 4.3 below:
Table 4.3
The frequency distribution table of vocabulary mastery score Interval class Frequency Cumulative Percent
40 - 49 3 9%
50 – 59 2 6%
60 – 69 8 24.2%
70 – 79 14 42.4%
80 – 89 5 15.1%
90 - 99 1 3%
33 100%
Based on the table 4.3 above, the result showed that there were 3 students (9%) in the interval 40-49. In the interval 50-59 there were 2 students (6%). In the interval 60-69 consisted of 8 students (24.2%). In the interval 70-79 had 24 students (42.4%), and there were 5 students (15.1%) who occupied the interval 80-89. The last, only there was 1 student (3%) filled the interval 90-99.
2. Students’ speaking ability score
In this section, the researcher presented the speaking ability score of 33 students of eleventh grade culinary program that chosen randomly from 4 classes. This speaking test was assessed by two inter rater. The students’ speaking ability score as follows:
Table 4.4
The students’ speaking ability score
No. Name Rater 1 Rater 2 Average Score
1 2 3 4 5
1. Rifqiya Amalina H. 67 67 67
2. Mohammad Iqbal M. 40 40 40
3. Edla Fatin 73 80 77
4. Yuda Putra Pratama 67 53 60
1 2 3 4 5
5. Nabilla Ayudya P 67 60 64
6. Dhining Arum Jati 87 93 90
7. Silmi Eloka Avanur 80 80 80
8. Alivia Cinta Maharani 67 67 67
9. Arsyad Ad Damsyiqi 67 67 67
10. Ganis Aulia Fitrah 40 40 40
11. Abdul Mukti Prayoga 67 67 67
12. Danil Setiawan 73 73 73
13. Adinda Anggun Gracia 73 67 70
14. Aisyah Miliyana 80 67 74
15. Aisa Agustin 60 67 64
16. Happy Margaretha 60 60 60
17. Aisyah Wardatul Jannah 60 53 57
18. Anisa Yanuarita 73 73 73
19. Annisa Adhisty 67 67 67
20. Rafif Pasha 60 53 57
21. Annisa Naila Ufa 67 67 67
22. Fitrah Aulia R. H. 87 73 80
23. Dinda Ayu Sri W. 53 53 53
24. Nabila Desti 40 47 44
25. Putri Dewi Ambarwati 67 67 67
26. Aulia Izzati Abdillah 73 73 73
27. Kamila Riskianti 80 80 80
28. Valentina Resi Putri 60 60 60
29. Rizki Januar 67 73 70
30. Aurea Nike Putri Kusuma 87 87 87
31. Aulina Maharani 40 40 40
32. Auril Zahra Islami Pasha 67 67 67
33. Femi Amelia Lestari 73 67 70
Average total score 65.82
From the students’ speaking ability score above, it is clearly showed that the minimum score is 40, the maximum score is 90, and the average score is 65.82. The result of speaking ability statistic as follows:
Table 4.5
Statistic of Speaking Ability Speaking Ability
N Valid 33
Missing 0
Mean 65.82
Mode 67
Std. Deviation 12.438
Range 50
Minimum 40
Maximum 90
Sum 2172
From the table 4.2 above, it can be seen that the mean score is 65.82, the standard deviation is 12.438, the range is 50, the minimum score is 40, and the maximum score is 90. To know the amount of class (k), the researcher used Sturges formula:
k = 1 + 3.3 log n
Where is the number of participants (33).Thus, the amount of class (k) = 1 + 3.3 log 33 = 5,98 (rounded to 6)
Next, to know the interval class (i), the range is divided by the amount of class. It can be calculated as follows:
i = 50: 6 = 8.3 (rounded to 9)
The frequency distribution table of speaking ability score can be seen in table 4.6 below:
Table 4.6
The frequency distribution table of speaking ability score Interval class Frequency Cumulative Percent
40 - 48 4 12.1%
49 – 57 5 15.1%
Interval class Frequency Cumulative Percent
58 – 66 4 12.1%
67 – 75 14 42.4%
76 – 84 4 12.1%
85 - 93 2 6%
33 100%
Based on the table 4.6 above, the result showed that there were 4
students (12.1%) in the interval 40-48. In the interval 49-57 there were 5 students (15.1%). In the interval 58-66 consisted of 4 students (12.1%).
In the interval 67-75 had 14 students (42.4%), and there were 4 students (12.1%) who filled the interval 76-84. The last, only there were 2 students (6%) occupied the interval 85-93.
C. Analysis and Hypothesis Testing 1. Analysis
In this section, the researcher conducted normality test and linearity test of the data before testing the hypothesis. The result of normality test as follows:
Table 4.7 The Normality Test
One-Sample Kolmogorov-Smirnov Test Unstandardize
d Residual
N 33
Normal Parametersa,b Mean .0000000
Std. Deviation 10.81341362 Most Extreme Differences Absolute .084
Positive .069
Negative -.084
Test Statistic .084
Asymp. Sig. (2-tailed) .200c,d
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
d. This is a lower bound of the true significance.
Based on the result above, it showed that significant value was 0.200 which means that it was greater than 0.05. It can be concluded that the data had normal distribution.
Next, to know the linearity of the data, the researcher used linearity test helped by SPSS 26 version. The result of linearity test as follows:
Table 4.8
The Linearity Test
ANOVA Table Sum of Squares df
Mean
Square F Sig.
Speaking Ability * Vocabular y Mastery
Betwee n Groups
(Combined )
2297.837 9 255.315 2.213 .060
Linearity 1084.190 1 1084.190 9.399 .005 Deviation
from Linearity
1213.647 8 151.706 1.315 .285
Within Groups 2653.072 23 115.351
Total 4950.909 32
Based on the result above, the sig. deviation from linearity was 0.285 which means that it was higher than 0.05. So, it showed that there was a linear correlation between vocabulary mastery and speaking ability.
Next, because the data distribution was normal and linear, means the data can be continued to be tested using parametric statistic. The researcher used Pearson Product Moment by SPSS 26 version to analyze the data in order find out the correlation between vocabulary mastery and speaking ability. The result is presented in the table 4.9 below:
Table 4.9 Correlations
Vocabulary Mastery
Speaking Ability Vocabulary Mastery Pearson Correlation 1 .468**
Sig. (2-tailed) .006
N 33 33
Speaking Ability Pearson Correlation .468** 1
Sig. (2-tailed) .006
N 33 33
**. Correlation is significant at the 0.01 level (2-tailed).
From the table above, the significance (ρ value) was 0.006 < 0.05.
It can be concluded that the correlation between vocabulary mastery and speaking ability was significant.
2. Hypothesis Testing
After analyzed the data by testing the normality, linearity, and Pearson Product Moment, the researcher carried on the hypothesis testing as follows:
a. If significance (ρ value) < 0.05, it means the correlation is significant then Ha is accepted and H0 is rejected.
b. If significance (ρ value) > 0.05, it means the correlation is not significant then H0 is accepted and Ha is rejected
If r value is positive, it indicates students’ vocabulary mastery score is high; the students’ speaking score is also high.
If r value is negative, it indicates students’ vocabulary mastery score is high; the students’ speaking score is low.
From the table 4.9 above, it indicated that ρ value was 0.006 < 0.05 which implies H0 was rejected and Ha was accepted; r value was 0.468
means positive. So, it can be summed up that there was a significant positive correlation between culinary students' vocabulary mastery and their speaking ability of eleventh grade culinary program at SMKN 3 JEMBER.
D. Discussion
The researcher conducted this study in order to know the correlation between culinary students' vocabulary mastery and their speaking ability. The researcher used vocabulary test and speaking test for collecting the data. The sample for this study was 33 students in eleventh grade culinary program. The data collection was analyzed using Pearson Product Moment with SPSS 26 version.
The finding showed that significance (ρ value) = 0.006 which was lower than 0.05, and r value was 0.468, means H0 was rejected and Ha was accepted. Hence, there was a significant positive relationship between culinary students' vocabulary and their speaking ability. This result was still in line with the previous research conducted by Nor Harisha66, in this research, the researcher used multiple choice items for vocabulary test;
presented one of topics that interested students for speaking test, and used questionnaire for self-confidence. The result indicated that the correlation of three variables was significant.
66 Harisa, ―The Correlation among Self-Confidence, Vocabulary Size, and Speaking Performance of EFL Students at IAIN Palangka Raya.‖
The result of this research was also supported by previous research done by the previous research done by Putri Aulia& Refnaldi67, this research used multiple choices items for vocabulary test and used role play for speaking test. The result of this research was there was strong relationship between students’ vocabulary and speaking ability. In addition, the previous research done by Dwhy Dinda Sari68, in this research, the researcher used vocational students from TKJ (Teknik Komputer dan Jaringan) and TKR (Teknik Kendaraan Ringan) program as research subjects. The researcher employed matching words for vocabulary test and for speaking test, and the topic was telling students’ experiences. The finding of this research showed that there was significant correlation between students’ vocabulary achievement and fluency in speaking English.
In the TKJ and TKR programs, the students' vocabulary mastery showed an average score of 78.1, and their average speaking score was 72.75.
From these values, it can be said that their vocabulary mastery and their speaking abilities are good. Meanwhile, in this current research, the culinary students’ mastery of vocabulary shows an average score of 68.18, and their average speaking score is 65.82. From these data, it can be seen that the conditions in the TKJ and TKR programs are not much different from the conditions in the culinary program in this current study.
67 Aulia Putri and Refnaldi, ―The Correlation Between Students’ Vocabulary Mastery and Speaking Ability at Grade 8 of Junior High School,‖ Journal of English Language 9, no.1 (2020)
68 Dwhy Dinda Sari, ―The correlation between Students’ Vocabulary Achievement and Fluency in Speaking English,‖ English Teaching and Linguistics Journal(ETLiJ) 2, no.1 (2021): 107-111
From those previous studies mentioned above, the researcher summed up that although previous studies used general topics in conducting tests and used different kind of tests, meanwhile the current research used culinary- related topics, it turned out that the results of the studies were same. The results showed that vocabulary and speaking had a positive significant relationship.
According to students' vocabulary test result, there were several students gave incorrect answer to the questions about adverbs and synonyms of adjectives. During the test, some of the students asked what the adverb was. Not only in adjectives and adverbs, some students made mistakes in answering questions about kitchen tools. From this, the researcher concluded that culinary students had minimum vocabulary.
As for the students' speaking test results, based on the vocabulary aspect, students with high vocabulary scores tended to use vocabulary that varies, produced long sentences, and rarely repeated the same words. But there were some students who were confused about how to pronounce the words because they did not know those words in English so finally they said those words in Indonesian. This result was in accordance with Richards&
Renandya’s theory that vocabulary is a fundamental part of language competence and plays big role for learners in speaking, writing, reading, and listening69.
69 Richards and Renandya, Methodology in Language Teaching, 255.
Secondly, pronunciation, the students who had high vocabulary mastery scores had good pronunciation, and all students used American accents. Nevertheless, there were a lot of students who mispronounced certain words. Most of the students mispronounced the words: fruit, salad, serve, grape, onion, and sausage.
The third is fluency, which tends to have a lot of hesitation and speed when speaking. The students who had a little vocabulary often paused for a long time while speaking, and also added words such as "umm, eee, anu".
While students who had a lot of vocabulary, they spoke fluently without any long pauses. This showed that vocabulary becomes a fundamental component that helps people communicate and convey their thought fluently 70 . Therefore, to get communicating effectively and delivering ideas fluently, the learners must to know a lot of words in speaking (expressive vocabulary) as well as words in listening (receptive vocabulary)71.
From the explanation above, the researcher concluded that vocabulary is related to speaking skill. Students who have a lot of vocabulary will speak fluently without hesitation and will not pause for a long time. Meanwhile, students who have a little vocabulary, they will think for a long time about how to pronounce those words in English. As Brown argued, vocabulary is one of crucial aspects in speaking, so vocabulary and speaking are related to each other72.
70 Nella, Hera Hartati, and Mita Lianah, ―Students ’ Ability in Vocabulary Mastery at the Second Grade Students ’ of Smpn 10 Merangin Academic Year 2019 / 2020,‖ Selecting: English Education Program Journal 2, no. 2 (2020): 57–67
71 Susan B. Neuman and Julie Dwyer, ―Missing in Action: Vocabulary Instruction in Pre-K,‖ The Reading Teacher 62, no. 5 (2009): 384–392, https://doi.org/10.1598/rt.62.5.2.‖
72 Brown, Language Assessment Principles and Classroom Practices, 157.
CHAPTER V
CONCLUSION AND SUGGESTION A. Conclusion
Based on the exposure finding in the chapter 4 above, the researcher summed up that there was a significant positive correlation between culinary students' vocabulary mastery and their speaking ability. It was proven by the significance value (ρ value) which was 0.006 < 0.05, it indicated that alternative hypothesis was accepted and null hypothesis was rejected.
Meanwhile r value was 0.468 which means positive. Hence, the correlation between culinary students' vocabulary mastery and their speaking ability was positive significantly.
B. Suggestion
Primarily based on the results of the studies that has been carried out, the researcher would really like to provide a few suggestions:
1. For the English Teacher
In order for students to have high self-confidence, be fluent in speaking, and have good pronunciation, it is suggested that the English teacher can increase students’ vocabulary and frequently give speaking practices.
2. For Next Researcher
To improve the quality of the next research, it is suggested that the next researcher can improve the results of this study by adding other language skills such as listening, reading, and writing.
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