Text Analysis of Applicants for Personality Classification
Using Multinomial Naive Bayes and Decision Tree
NANDA YONDA HUTAMA
Informasi Umum
Kode
20.04.4194
Klasifikasi
621.389 28 - Security Electronics
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Informatics
Dilihat
38 kali
Informasi Lainnya
Abstraksi
In talent recruitment, companies seek talents who fit with their corporate culture among a large number of applicants. To conduct this process, companies carry out psychological tests to assess the fitness of applicants' personalities with their corporate culture. However, psychological testing requires cost and much effort. Thus, an automated system is required to assist companies in the talent recruitment process that can classify personalities through text and to reduce the effort needed. This research is conducted based on the personality traits according to the corporate culture in Telkom Indonesia. The data used is text data that has been labeled, pre-processed, and feature selected. The clean text data is used to create a classification model using multinomial naive Bayes and decision trees. There are 6 models built based on 3 work cultures. The decision tree achieves an accuracy of 33%, 66%, 80%, while multinomial naive Bayes with an accuracy of 83%, 50%, 60%, which resulted as better performance.
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Pengarang
| Nama | NANDA YONDA HUTAMA |
| Jenis | Perorangan |
| Penyunting | KEMAS MUSLIM LHAKSMANA, ISMAN KURNIAWAN |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Informatika |
| Kota | Bandung |
| Tahun | 2020 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
