Video summary

Tutorial SEM dengan SmartPLS 4 (Pemula)

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Summary of the Subtitles (SmartPLS 4 Beginner Tutorial)

  • The video explains how to perform PLS-SEM analysis in SmartPLS 4 from start to finish, aimed at beginners.
  • It demonstrates working with questionnaire data (reported as 139 questionnaires) containing multiple items/indicators grouped as A1–A9, B1–B7, and C1–C6.

Workflow: Importing Data → Building the Model → Running Analysis

  1. Prepare data in Excel

    • Questionnaire response data is moved into Excel.
    • The file is saved as CSV (via Open CSV / workbook → CSV).
  2. Create/load a SmartPLS 4 workspace and project

    • SmartPLS 4 is opened (noting it differs from PS3/SmartPLS 3).
    • A new workspace and new folder should be created (to avoid using an invalid workspace folder).
    • A new project is created (example name: “sam/sam1”).
    • The CSV file is imported into the project.
  3. Define the PLS-SEM model

    • A model is created and set to PLS-Mode.
    • Latent variables are added (example: A, B, C).
    • Indicators/items are connected to each latent variable:
      • A: A1–A9
      • B:
        • B1–B3 → linked to b11
        • B4–B7 → linked to b22
      • C: C1–C6
  4. Draw relationships (paths)

    • The model includes paths such as:
      • A → B11, A → B22
      • C → B11, C → B22
    • Indicator placement/layout differs from SmartPLS 3, so alignment options (left/right) may be needed.

Running the PLS Algorithm and Interpreting Outputs

  • The tutorial runs the procedure via:
    • Calculate → PLS Algorithm → Start Calculation

Outer model: Validity & Reliability

The outputs are used to check:

  • Convergent Validity

    • From outer loadings / loading factor
  • Discriminant Validity

    • Via cross-loading (described as a “not determinant” / cross-loading check)
  • Reliability

    • Cronbach’s Alpha
    • Composite Reliability
    • Average Variance Extracted (AVE) (mentioned as “eva”)

Inner model: Model fit / explained variance

Additional metrics include:

  • R Square (to assess inner model effectiveness)
  • Effect sizes / GOF are mentioned as additional measures

Hypothesis Testing (Bootstrapping)

  • The video covers hypothesis testing (inner model / path significance) using bootstrapping.
  • Bootstrapping takes time.
  • Interpretation uses path coefficient significance, with colors described as:
    • Red path = hypothesis rejected
    • Green path = hypothesis accepted
  • Outer loadings from bootstrapping are also shown to inspect indicator-to-construct relationships.

Example hypothesis outcomes (as stated in subtitles)

  • 2 hypotheses accepted
  • 2 hypotheses rejected
  • A specific case is mentioned (e.g., CGB2 / H0 accepted, and A→B11 rejected), though the exact labeling is slightly unclear due to subtitle noise.

Moderation Analysis (SmartPLS 4 vs. SmartPLS 3)

  • The tutorial explains adding moderation variables in SmartPLS 4:
    • A moderation effect is selected (workflow differs from SmartPLS 3).
    • A moderation line is drawn from the moderator to the relationship (connecting in the “middle”).
    • Example: using C as a moderation variable between A and B (affecting relationships to B11 and B22).

Moderation results described

  • Without moderation, paths are accepted/rejected similarly to the baseline model.
  • With moderation, effects change:
    • Moderation strengthens one relationship (described as accepted)
    • Moderation weakens / becomes not significant for another relationship (described as rejected for one path)
  • Overall summary from the subtitles:
    • Moderation on B11 appears stronger/accepted
    • Moderation on B22 appears weaker/not significant

Reusing/Adding New Data and Re-running Analysis

  • The tutorial shows how to add new data (or switch datasets):
    • SmartPLS 4 is described as easier than SmartPLS 3 for managing multiple datasets.
    • Instead of only one dataset, SmartPLS 4 allows choosing among multiple datasets.

Steps described:

  • Select a dataset (example: Data 3)
  • Adjust/replace data inputs
  • Run PLS Algorithm again
  • Re-check validity/reliability results (statuses/colors such as rejected vs accepted may change)

Main Speaker / Source

  • Single tutorial presenter (name not identified) demonstrating the SmartPLS 4 steps throughout.

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