Aplikasi Analisis Data Kualitatif Menggunakan Algoritma Rough Set
Abstract
Data analysis is a process carried out to produce a data modeling with a view to finding useful information so that it can provide clues to a study in making decisions on existing data. One algorithm that is used in the process of data analysis is the rough set algorithm used for qualitative data types. The rough set algorithm is widely used because this algorithm is easy to understand and can find a minimum set of data and can evaluate the significance of the data. To process large amounts of data in data analysis using this rough set algorithm, we need a tool that can simplify and speed up the calculation process. In this study an application was developed as a tool that can help the process. The application is built based on a GUI that can run on Windows, Linux and MacOS platforms. With this application the analysis process can be accelerated with the ability to process a small time and direct implementation of the rules that are owned. The number of objects in the decision system that can be processed is also greater than the application of its predecessor Rosetta. In the algorithm, the rules generated by this application meet the rough set principle, from the results of the comparison test of accuracy with the rules produced by Rosetta. With an average questionnaire score of 85.33%, proving that the application built provides ease and high use value.Published
Issue
Section
License
Copyright info for authors
1. Authors hold the copyright in any process, procedure, or article described in the work and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors retain publishing rights to re-use all or portion of the work in different work but can not granting third-party requests for reprinting and republishing the work.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) as it can lead to productive exchanges, as well as earlier and greater citation of published work.