Cara Uji Validitas Pearson Product Moment dan Uji Reliabilitas Cronbach Alpha Dengan SPSS Lengkap

Summary

This tutorial walks through the process of testing the validity and reliability of a questionnaire using SPSS. It covers the Product Moment validity test, where respondents' answers are correlated with the total score, and the Kombat Alpha reliability test, which assesses the consistency of the questionnaire. Key concepts such as significance values, R values, and Cronbach's Alpha are explained in detail, along with practical steps for performing the tests in SPSS. The tutorial concludes by highlighting how to interpret the results and the importance of validating research instruments.

Takeaways

• 😀 Validity testing using Product Moment method involves correlating each questionnaire item with the total score of the respondent’s answers.
• 😀 To conduct the validity test in SPSS, you compare the calculated R value with the R table value. If the calculated R is higher, the item is valid.
• 😀 If the significance value is smaller than 0.05, the item is considered valid. Otherwise, it is invalid.
• 😀 Reliability testing with Cronbach's Alpha measures the consistency of the questionnaire. A high value indicates high reliability.
• 😀 Cronbach’s Alpha values between 0.80 to 1.00 indicate very high reliability, while values between 0.60 and 0.80 indicate high reliability.
• 😀 SPSS allows you to enter data from Excel directly, making it easier to work with large sets of respondents and statements.
• 😀 The Product Moment validity test requires you to check both the R value and the significance value to determine validity.
• 😀 To test reliability in SPSS, use the 'Analyze' menu, select 'Scale' then 'Reliability Analysis,' and check the Cronbach’s Alpha value.
• 😀 If the Cronbach’s Alpha value is 0.95 or higher, the reliability of the test is considered very high, meeting the required standards.
• 😀 In the validity test, a significance value of less than 0.05 means the item is valid and can be retained in the questionnaire.
• 😀 The tutorial emphasizes that ensuring both validity and reliability is essential for confirming the quality of the questionnaire used in research.

Q & A

What is the main focus of this tutorial?

The tutorial focuses on performing validity and reliability tests using SPSS, specifically the Product Moment method for validity testing and Cronbach's Alpha for reliability testing.

What is the Product Moment method used for in this tutorial?

The Product Moment method is used to test the validity of a questionnaire by calculating the correlation between each item and the total score of the respondents.

How do we calculate the R table value for validity testing?

The R table value is calculated using the formula DF = n - 2, where n is the sample size. In this example, with 20 respondents, the R table value is 0.43.

What does it mean if the calculated R value is greater than the R table value?

If the calculated R value is greater than the R table value, the questionnaire item is considered valid.

What significance value indicates validity in the validity test?

If the significance value is less than 0.05, the item is considered valid.

What is the significance of Cronbach's Alpha in reliability testing?

Cronbach's Alpha is used to measure the reliability or consistency of a questionnaire. A high Cronbach's Alpha (0.80 to 1.00) indicates very high reliability.

How do you perform a validity test in SPSS?

To perform a validity test in SPSS, open the data, go to Analyze → Correlate → Bivariate, select all variables, and then check the Pearson correlation and significance value for each item.

What does a Cronbach's Alpha value of 0.953 mean in terms of reliability?

A Cronbach's Alpha value of 0.953 indicates that the questionnaire has very high reliability, as it falls in the 0.80 to 1.00 range.

What should you do if the significance value is greater than 0.05 in the validity test?

If the significance value is greater than 0.05, the item is considered invalid.

What is the purpose of testing both validity and reliability in a research questionnaire?

Testing validity ensures that the questionnaire measures what it intends to measure, while testing reliability ensures that the questionnaire produces consistent results over time.