The Role of ICT-Based Metacognition Against the Capabilities of Student Statistics in the Industrial Age 4.0

The ability of statistics is the knowledge base of statistical reasoning and statistical thinking. The ability of Statistics can be improved by increasing the role of student metacognition. In the industrial era 4.0, one way to optimize students’ metacognition skills is to get used to solving complex problems with ICT-based. Optimal statistical ability will contribute to the habit of self to work systematically and scientifically. So that this attitude is a capital for students facing the Industrial era 4.0. The method used is a qualitative method. In the Intervention applying statistics learning by developing ICT-based statistics module to increase the role of metacognition in improving the statistical abilities of students of Medan Potensi Utama University. Samples, taken as many as two classes, namely the control class and randomized experiment. Based on the results of the first trial in the field, the results show that the ability of metacognition has a significant effect on the ability of student statistics. student statistics. Students also show a positive response to ICT-based learning in the classroom.


Introduction
According to Nugraha [6] the skills needed in dealing with industry 4.0 include: 1) Information media and technology skills, 2) Life and Career Skills, 3) Learning and Innovative Skills, 4) Effective Communication Skills. As an educator we can prepare human resources from learning and innovating skills with information-based media and technology skills to face the industrial era 4.0.
But in reality Indonesian human resources are still below the standard in terms of learning and innovation skills and information media and technical skills. This is evident from the results of the World's Most Literate Nations [9] that Indonesia is ranked 60th in Final Rank with criteria: for computers 60, Education System Input 54, Library 36.5, Newspaper, 55, Education-test scores 45. Furthermore, based on interviews and observation of researchers to students at Medan Potensi Utama University that they have difficulty solving complex problems in material statistics, out of 38 students given the problem to analyze the relationship between the cost of advertising with sales volume by systematically completing according to the concept of statistics, only 3 students who answered correctly the rest did not understand what they have to write, while we have taught them how to solve problems aided by SPSS software. Based on the things mentioned above, it is indicated that the metacognition power of students to understand what they have to think and design what to do is still low. They used to 2 solve problems partially, so when presented complex problems (complex problem solving) they were confused which first had to be done.
Based on the above-mentioned efforts that can be done is to optimize one's ability to think and one's ability to use their awareness to regulate their thought processes (metacognition abilities). Metacognition is often called thinking about thinking [1]. The metacognitive component is divided into two, namely metacognitive skills and metacognitive knowledge. Metacognitive skills refer to the three essential skills that are very possible to do, namely: planning skills, monitoring skills and evaluation skills. For metacognitive knowledge is the ability of a person to use his consciousness to regulate his thought processes (self-regulation of cognition). The two components of metacognition are interdependent. Based on the above definition, it is very important to increase the role of metacognition in students, especially in statistical learning One way to motivate students and enhance the role of student metacognition is to get used to solving complex problems with ICT-based so that students' statistical abilities become better. Statistical ability is an ability about the theory and method of analyzing quantitative data obtained from observations in order to study or compare the source of variance of a phenomenon, to help make a decision whether the researcher accepts or rejects the hypothesis of the relationship between phenomena and helps in making reliable conclusions. from empirical observations [7]. Furthermore, according to [6] the ability of statistics is the ability to do something about statistics. So based on the definition above, it can be concluded that the ability of statistics is a capability or can be both theoretical and practical in analyzing quantitative data obtained from observations in the field so that it can be used as a comparison in drawing conclusions. Based on some of the opinions above, it is very necessary to improve or develop student statistics skills.
The ability of statistics is the knowledge base of statistical reasoning (statistical reasoning) and statistical thinking. While statistical citizenship is used by researchers to analyze quantitative data in order to produce decisions that are in accordance with existing information. The basis of statistical ability (statistical competence) as stated above includes: 1) reasoning for data, 2) Reasoning for the basic concepts of statistics and terms used in statistics, 3) Reasoning for collecting and processing data in descriptive statistics, 4) Basic skills in translating data, and 5) Basic abilities in communicating data and research results.
Based on the foregoing, the researcher made the research title "The Role of ICT-Based Metacognition Against Statistics Capabilities in the Industrial Era 4.0. The point here is that researchers want to find out how much the role of metacognition is optimized when learning ICT-based statistics in the form of SPSS software and the Process of Complex Problem Solving. Optimal statistical ability will contribute to the habit of self to work systematically and scientifically. So that such an attitude is a capital for students to face the era of industry 4.0, where needed quality human resources (reliable) with complex and skilled problems using appropriate technological advances, this is in line with researchs are [4,2,5].

Methodology
The method that will be used is a qualitative method according to Davison et.al, in 2004 [2] as a cycle, which in the Intervention (Action Taking) stage the researcher applies learning statistics where by developing statistics module modules on multiple linear regression 4 variables based on ICT and complex problem solving processes with questions that will stimulate the increasing role of student metacognition and the complex problems presented are problems that exist around the student environment in the Industrial 4.0 era. The design concept of this study is presented in Figure 1  2. Action Planning: To overcome the cause, the researcher plans to apply the ICT-Based Complex Problem Solving learning method (SPSS Software) to create and compile student learning modules for material statistics and to develop modules with metacognition questions aimed at increasing the role of student metacognition and will later influence the ability student statistics. Taking): Implementation of the Process of Complex Problem Solving by using ICT that is SPSS software in class (a trial I). In this first trial, the writer used the Thing Pair and Share method where students sat in pairs, working together to solve problems and discuss.

Intervention (Action
4. Evaluation: Provide Tests (complex and realistic problems of students directed to Analysis of multiple linear regression data of 4. variables) Conduct observations during learning and provide questionnaires for students' responses to the learning methods applied and observation of student activities.
5. Reflection: Overall evaluation results both test results, observations and questionnaires that students 'Metacognition plays an important role and the results of students' statistical ability tests also increase then the research cycle is considered complete (EXIT), if the role of metacognition has not been optimal or increased and the student's statistical ability results have not increased then the cycle is repeated again to get the desired results. In trial I the results of the posttest were improved compared to the results of the pretest 6. Exit: Exit the research cycle if the application is deemed appropriate according to the rules.

Results and Discussion
Based on the above research design for the second stage, namely in the Action Planing the authors compiled a learning module which before testing it in the field is done first validation on the opinions of 3 experts in mathematics education. Based on the opinion of the experts obtained an average value of the total aspects. The summary of the results of the validation of learning tools and research instruments are presented in Table 1 below. Furthermore, after the revision conducted an instrument trial with the subject of students of the University of Muhammadiyah North Sumatra, namely in two classes on statistical material. The results of the test of the validity of statistical ability instruments with reference to the role of student metacognition are valid, high reliability coefficient (0.751). After the validation results are declared valid and meet the requirements to be used as a measurement tool then used in trial I in learning in class.
Based on the research design for the third stage, namely Intervention (Action Talking) doing learning in class which is a Think Pair And Share method, here students exchange ideas to design problem solving. The problem is given in Figure 2 below.

Figure 2. Problems presented at the time of learning
The problem presented is solved by ICT-based and manual with questions that refer to optimizing the role of student metacognition when solving problems. The metacognition questions are as follows, When you develop a problem solving plan, ask yourself: a. What initial knowledge will help you in solving the problems above? b. What did you first do after reading the questions? c. How long will you complete this problem in full? why is that? When you are carrying out problem solving, ask yourself: a. What do you need to do if after reading the problem, but don't understand the problem given? b. How do you solve the problem above? c. Why are you sure that the answer process you made is correct? After you have solved the problem, ask yourself: a. Why did you use this method in solving the problem above? b. How do you check the correctness of your answers above? c. What did you learn after solving the problem above? The problem that must be solved is to see how much influence the competence, remuneration, and leadership style on the performance of employees. The data that must be analyzed based on field surveys are as follows, 5. Calculate the partial correlation coefficient and test its significance.

Give conclusions from the results of the analysis that has been obtained
The ICT is used as a complex problem solving process using Excel and SPSS. Based on the results of the first tryout in class data obtained that the average value of the metacognition ability of students is 78.56 and the average ability of student statistics is 83.85. linear regression test was performed. The results of the linear regression test are presented in the following table.   Table 4, it can be seen that the coefficient of the regression equation with an F value of 22.487, which means with a value of sig.0.00, which means the coefficient of the regression equation is significant. Furthermore, for the linearity regression test results are as follows. Based on Table 5 it can be seen that the Linearity form deviation obtained an F of 0.706 with sig. 0.667 > from 0.05, which means linear regression line Table 6. Correlaton Test After implementing learning in class the students fill in the questionnaire of students' responses to learning and the modules used. The results of the questionnaire responses of students are calculated based on the criteria for interpretation of the questionnaire answers in Table 7 below, Based on the results of the calculation of student questionnaire answers and based on the criteria of questionnaire answers in Table 7 the results of the trial data of student questionnaire answers can be seen in Table 8 below.
Based on Table 6 it can be seen that Pearson Correlation X with Y is 0.648 with sig. 0.00 which means that the correlation between X and Y is significant. Based on Table 8, it can be seen that for the control class almost half of the students responded positively to learning that is equal to 49% and for the experimental class students responded to learning by 90% (Almost all) students responded positively and were happy with ICT-based learning, meaning that learning was based ICT gets a better response than learning without ICT-based.
Based on the design of the fourth stage of evaluation research that has been carried out in trial I, the evaluation results can be summarized as follows  Table 9 Summary of Test Results I, it can be seen that there is an increase in the ability of the results when learning before ICT-based that is by 10% for metacognition skills and for statistical abilities by 9.8%, to maximize the results of the role of ICT-based metacognition for statistical abilities then a trial II was conducted to get better results. For the results of student responses an increase of 45.6% a significant increase.

Conclusion
Based on the results and discussion above, it can be concluded that metacognition has a significant regression equation and the regression line is a linear regression line, and Pearson correlation X with Y is significant. In other words, metacognition has a significant influence on the ability of student statistics, which means that ICT-based metacognition has a significant role or an important role on the statistical abilities of Medan Potential Main students. The more the value of the metacognition ability of students increases the linear ability of student statistics will also increase. Likewise the students' responses to learning showed a positive response based on the results of the questionnaire and observation during learning in class and based on interviews with several students. The same thing with research [5] that ICT-based learning increases students' metacognition abilities.

Acknowledgment
Thanks to Kemenristekdikti-DRPM on the PDP grant scheme for funding in 2020, Utama Potential University, which has provided the opportunity and motivation to conduct research and as a research sample testing location, Muhammadyiah University, North Sumatra, as a place to test the validity of learning tools, and colleagues help directly or indirectly both morally and materially to support the writing of this journal.