Fuzzy Delphi Module for Jamovi

Background

The fuzzy Delphi method (FDM) is a modified version of the classical Delphi technique that applies fuzzy set theory to handle the ambiguity and vagueness in expert opinions. Jamovi is an open source statistical software that is user-friendly and based on R programming language. The project investigates the evolution of a FDM module that has been incorporated into Jamovi and explores its potential uses and benefits.

Paper link: coming soon

References

[1] Chan, LK (2024) FuzzyDelphiJmv (Version 1.0) [Computer software]. Retrieved from https://lerlerchan.github.io/FuzzyDelphiJmv/

[2] The jamovi project (2022). jamovi. (Version 2.3) [Computer Software]. Retrieved from https://www.jamovi.org.

Project Aim

To develop a flexible fuzzy Delphi module for the Jamovi statistical analysis platform that allows users to customize and refine the Delphi technique according to their own research needs and preferences.

Installation

Step-by-step images procedure can be view at Here

To install the Fuzzy Delphi module in Jamovi, follow these steps:

1. Click on the “+” icon in the top-right corner of Jamovi to access the module installation options.

2. Choose the Jamovi library from the menu that opens. OR download from Here

3. In the window that appears, click on “Available” (located at the top-middle).

4. Browse through the list of modules and click “INSTALL” for the Fuzzy Delphi module or any other module you’d like to use.

5. Finally, close the window by clicking the arrow pointing up in the top-right corner. Once installed, you’ll be able to utilize the Fuzzy Delphi module for your research needs and customize it according to your preferences

Demonstration Video

FuzzyDelphiJmv.v1.0.0-.User.Guide.-.Made.with.Clipchamp.mp4

Important Notes:

1. Name all your data header in "Item". For Example: Item1, Item2,....
2. Sample data in .csv to experience can be download from Here

Contributing

We are happy to receive bug reports, suggestions, questions, and (most of all) contributions to fix problems and add features. Pull Requests for contributions are encouraged.

Here are some simple ways in which you can contribute (in the increasing order of commitment):

• Read and correct any inconsistencies in the documentation
• Raise issues about bugs or wanted features
• Review code
• Add new functionality

License

MIT License till 27 April 2024

GPL-v3 License updated on 28 April 2024