Web scraping and naïve bayes classification for job search engine
| Main Authors: | Slamet, Cepy, Andrian, Rian, Maylawati, Dian Sa'adillah, Suhendar, Suhendar, Darmalaksana, Wahyudin, Ramdhani, Muhammad Ali |
|---|---|
| Format: | Proceeding PeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
, 2018
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| Subjects: | |
| Online Access: |
http://digilib.uinsgd.ac.id/5646/1/Slamet_2018_IOP_Conf._Ser.%253A_Mater._Sci._Eng._288_012038.pdf http://digilib.uinsgd.ac.id/5646/ |
Daftar Isi:
- Many organisations (government of non-government) use websites to share information of new recruitment for the workers. This information overflows on thousands of sites with various attributes and criteria. However, this availability forms a complex puzzle in the selection process and leadto inefficient runtime. This study proposes a simple method forjob searching simplification through a construction and collaboration of web scraping technique and classification using Naïve Bayes on search engine. This study is resulting an effective andefficient application for usersto seek a potential job that fit in with their interests.