Data Collection Technique Data Analysis Technique

digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id Note: r xy = Correlation coefficient of variable X and Y N = Number of cases x = Independent variable students’ MI score y = Dependent variable students’ proposal writing score xy = The sum of the product of paired score multiplication of x and y scores for each student x = The sum of x students’ MI score y = The sum of y students’ proposal writing score x 2 = The sum of square of students’ MI scores y 2 = The sum of square of students’ writing propoal scores x 2 = The square of the sum of students’ MI scores y 2 = The square of the sum of students’ proposal writing scores After collecting the data, the researcher looks for x and y, the data included to table of correlation. The output can be included to digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id r table to know the output of coefficient correlation is significant or not can be generalization. In t table, the researcher uses the standard of significance of 0, 05 or 5 the reliability is 95. The output of that can be conclusion with looking at that, when arithmetic r is more than r table means Ho is pushed way and Ha is accepted and the conclusion is “there is correlation and vice versa” and could be written: Ho : p = 0 Ha : p ≠ 0 12 The coefficient correlation which got from that formula is interpreted based on the guidance Sugiyono’s book. It shows the interval of coefficient and the level of relationship between the two variables below 13 . Table 3.1, Coefficient Correlation Interval of Coefficient Relationship Level 0,00 - 0,199 Very weak 0,20 - 0,399 Weak 12 Anas Sudjono, “Pengantar Statistik Pendidikan...................... 218 13 Sugiono, “Statistik Untuk Penelitian” Bandung: Alfabeta, 2007, 231. digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id 0,40 - 0,599 Enough 0,60 - 0,799 Strong 0,80 - 1,000 Very strong The correlation coefficient has some important properties. Mark Belnaves and Peter Caputi explain that the magnitude of the correlation coefficient indicates the strength of the relationship between the variables. The values of the correlation coefficient can range from -1 to +1. A coefficient close to +1 or to -1 indicates a strong relationship between two variables. Scores closes to zero indicated the absence of a relationship between the two variables. The variables are positively related, if the coefficient has positive sign 14 . The researcher also uses SPSS 16 as the application for this research in order to make the calculation easier and more valid. The level of significance 0,05 is used and the value of sig from output of SPSS. The value of sig is higher than the level of significance, it means that the null hypothesis is rejected and the alternative hyphothesis is accepted there is significant correlation. If the value of sig is lower than the level of significance, it means that the null hypothesis is accepted and the alternative hypothesis is rejected 14 Mark Balnaves and Peter Caputri, Introduction to Quantitative Research Methods an Investigative Approach. London: SAGE Publication Ltd, 2001, 155. digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id there is no significant correlation. The table of data collection and analysis step more detail shows as follow: Figure 3.2, The step of data collection and analysis From the table above, the researcher divides into three steps for analysing the data. The first step is gather the respondent which is in this research is the sixth semester students. The second is the researcher collects the data of students’ multiple intelligence score from multiple intelligence test and for proposal writing score is from final score of proposal writing. The Correlation MI and Proposal writing obtained 3 Score analyzed and correlated using SPSS 16 Multiple Intelligences Score Proposal writing Score 2 Score collected Multiple Intelligences Test Final Score of Proposal writing 1 Respondent gathered The sixth semester students digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id And the third step is analysing tha data. For analysing the data, the researcher uses SPSS 16. The score of multiple intelligences and proposal writing are put into data view. Then, choose analyze  correlate-bivariate. Bivariate correlation is chosen, since that function is to know the correlation between two variables and also can be used to find variable that has more than one sub variable as multiple intelligence. Then, automatically the result of correlation between multiple intelligences and proposal writing are presented. digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id 45

CHAPTER IV RESEARCH FINDING

Concerning with the statement of the problems, in this chapter the researcher describes and analyzes the findings during the research process conducted at English Teacher Education Department at UIN Sunan Ampel Surabaya. It is intended to answer the problem of the study. In finding, the researcher describes the process of calculating and presenting result of the data. Furthermore, in the discussion the researcher integrates and explains more about the finding of the research.

A. Findings

The researcher does the research and gets the complete data from all the research instruments including MI Test and Study Document. To gain the objectives of the research, the researcher analyzes the data systematically and accurately. Then, the data analyzes in order to draw conclusion about the objective of the study. The purpose of findings are to answer research question in chapter one. Researcher describes the findings in this chapter into three parts. They are described as follows: 1. The Students’ Multiple Intelligences Score After distributing MI Test, the researcher gets the result of the test. It is found that all types of intelligences are possessed by the sixth semester students of English Teacher Education Department at UIN Sunan Ampel digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id Surabaya who took proposal writing class in the previous semester. From 83 students who are included in the population, 4 students are absent when the research conducted. Thus, there are 79 students who join the MI Test. The MI test is conducted on 4 th and 8 th of May 2015. The result of the research is analyzed by the researcher on the 8 th and 9 th of June 2015. The table of all the result scores detail students’ multiple intelligence and proposal writing score can be seen in Appendix 1. The result of the students’ multiple intelligence analysis is summarized in the following table. Chart 4.1, The Whole Result of Students’ Multiple Intelligence 5 10 15 20 25 30 Students digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id From the table above, the researcher finds that there are 5 students have high score in Linguistic Intelligence 5,3 . 6 students have high score in Logical-Mathematical Intelligence 6,3 . 28 students have high score in Musical Intelligence 29,5 . 6 students have high score in Bodily- Kinesthetic Intelligence 6,3 . 7 students have high score in Spatial-Visual Intelligence 7,4 . 14 students have high score in Interpersonal Intelligence 14,7 and 29 students have high score in Intrapersonal Intelligence 30,5 . From MI Test, total respondents of MI Test become 95 students from 79 students, since there are some students who have more than one intelligence. Hence, there are 16 respondents who come from several students. The data is matched with theory that stated by Gardner if each individual person possibly has a combination of two or more intelligences 1 . Their score range from 10-40. The data shows that the most predominant of students is in intrapersonal intelligence, 30,5 students have tendencies in intrapersonal intelligence. The preeminent of students for each intelligence show in table above. For mo re detail about the score of students’ preeminent in each intelligences is shown in the following table. 1 Howard Gardner, The Unschooled Mind; How Children Think............. 14 digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id digilib.uinsby.ac.id Chart 4.2, The Students’ Range Score of Linguistic Intelligence Chart 4.3, The Students’ Range Score of Logical-Mathematical Intelligence 10 20 30 40 50 60 70 10,0-20,0 21,0-30,0 31,0-40,0 Linguistic Linguistic 10 20 30 40 50 60 70 10,0-20,0 21,0-30,0 31,0-40,0 Logical-Mathematical Logical-Mathematical