DATA MINING (KLASTERISASI) PERBANDINGAN MAHASISWA YANG MENDAFTAR TERHADAP MAHASISWA YANG DITERIMA
DOI:
https://doi.org/10.31849/zn.v3i1.7638Keywords:
Data Mining, New Studen Admission, ClusterizationAbstract
The problem with data owned by a company or agency is data as a benchmark for basic information. However, these data are generally in a developing country or companies that have not utilized the sophisticated structure of information systems in the current era still see the data as a part of a process, which results in the data being used separately as a container of information to support decision making. . There is a need for a special study conducted by the research team to look at this problem subjectively, namely by sorting out the identification of data sources into useful information for leaders or officials. There are several methods that can be used to mine data (data mining), including: Classification, Clustering, Association and various appropriate methods can be used. The results of data mining can be information that can be easily understood by policy makers in an institution, especially leaders at the Faculty of Computer Science.
Downloads
Published
Issue
Section
License
CC BY-SA 4.0
Attribution-ShareAlike 4.0
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
