Rizka Nurfatni Sipahutar, NPM 2009100152 (2024) OPTIMISASI PENILAIAN KINERJA KARYAWAN PT. TOLAN TIGA INDONESIA ESTATE PERLABIAN DENGAN ALGORITMA C4.5. Tugas_Akhir (Artikel) INFORMATIKA, 12 (2). pp. 199-207. ISSN 2615-1855 (e-ISSN) / 2303-2863 (p-ISSN)
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Abstract
In the face of fierce competition in the current global era, companies are required to prepare and always adjust their strategies to the changes that occur so that the company remains able to compete and survive. Employees who are in a company are workers which is the most important asset that must be owned and indispensable in the company and of course must be considered by all parties in order to create good performance as well as have goals to be achieved in the assessment of employee performance at PT. There Are Three Types Of Indonesian Real Estate. Employee performance appraisal in the company is seen as the driving force of the company because human resources play an active role in the running of an organization or company and the decision-making process. Machine learning tools used in predicting the assessment, using the C4.5 algorithm, the data obtained is more accurate. Machine learning is an artificial intelligence that can process data that is useful for consideration in making decisions and solving problems. C4.5 algorithm is one of the algorithms in data mining that serves to classify a class. This algorithm is a development of the ID3 algorithm. How the C4.5 algorithm works by forming a decision tree to produce a decision. Keywords : Data Mining, C4.5 Algorithm, Valuation, Employee Performance.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Data Mining, C4.5 Algorithm, Valuation, Employee Performance. |
| Subjects: | Z Bibliography. Library Science. Information Resources > ZA Information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources |
| Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 12 Aug 2024 03:23 |
| Last Modified: | 12 Aug 2024 03:23 |
| URI: | http://repository.ulb.ac.id/id/eprint/886 |
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