Sabita, Hary and Fitria, Fitria and Herwanto, Riko (2021) ANALISA DAN PREDIKSI IKLAN LOWONGAN KERJA PALSU DENGAN METODE NATURAL LANGUAGE PROGRAMING DAN MACHINE LEARNING. Jurnal Informatika, 21 (1).
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Abstract
ABSTRACT This research was conducted using the data provided by Kaggle. This data contains features that describe job vacancies. This study used location-based data in the US, which covered 60% of all data. Job vacancies that are posted are categorized as real or fake. This research was conducted by following five stages, namely: defining the problem, collecting data, cleaning data (exploration and pre-processing) and modeling. The evaluation and validation models use Naïve Bayes as a baseline model and Small Group Discussion as end model. For the Naïve Bayes model, an accuracy value of 0.971 and an F1-score of 0.743 is obtained. While the Stochastic Gradient Descent obtained an accuracy value of 0.977 and an F1-score of 0.81. These final results indicate that SGD performs slightly better than Naïve Bayes.
| Item Type: | Article |
|---|---|
| Subjects: | Ilmu Komputer |
| Divisions: | Jurnal > Jurnal Ilmu Komputer |
| Depositing User: | Editor |
| Date Deposited: | 10 Aug 2022 08:39 |
| Last Modified: | 02 Feb 2023 07:04 |
| URI: | http://repo.darmajaya.ac.id/id/eprint/7991 |
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