Assalmi, Fityan Hanif (2024) Implementasi Metode Long Short-Term Memory (LSTM) untuk Optimalisasi dan Peramalan Kata Kunci Pada Situs Web Monstermac. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
The purpose of this research is to provide MonsterMAC with early warning, analyze, and predict the most relevant keywords on the MonsterMAC website using the Long Short-Term Memory (LSTM) Method. Data from the website is captured, processed, and analyzed to identify trends that affect its visibility on the google search engine. The use of LSTM was chosen due to its proven ability to analyze sequential data patterns such as keywords over time. Hopefully, the results of this study can provide valuable insights into the most effective keywords to improve the visibility of MonsterMAC's website. With a better understanding of relevant keywords, website owners can develop more effective SEO strategies and improve their competitiveness in an increasingly competitive online environment. In addition, this research is expected to contribute to the understanding of the application of LSTM in keyword analysis and prediction for websites. It will also emphasize the importance of innovative SEO strategies in improving website visibility and competitiveness in today's digital era.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76.6 Computer Programming |
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| Divisions: | Faculty of Computer Science > Departemen of Data Science | ||||||||||||
| Depositing User: | Fityan Hanif Assalmi | ||||||||||||
| Date Deposited: | 30 Jul 2024 07:53 | ||||||||||||
| Last Modified: | 30 Jul 2024 07:53 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/28013 |
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