ALMENATA, MUHAMMAD RAIHAN and Yusliani, Novi and Rachmatullah, Muhammad Naufal (2023) KEYPHRASE EXTRACTION PADA TEKS BERBAHASA INDONESIA MENGGUNAKAN METODE TOPICRANK. Undergraduate thesis, Sriwijaya University.
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Abstract
This study investigates the implementation as well as the performance of the application of TopicRank method on performing keyphrase extraction towards Indonesian text. The utilisation of keyphrase as one of the tools on managing the growing textual information drives the need for a relevant keyphrase extraction methodology. By developing the keyphrase extraction system, applying the extraction process towards the title and abstract of Indonesian scientific paper and utilising the comparison of the keyphrase obtained by the extraction against the keyphrase determined by the writer, performance measurement was done towards the extraction process. The matter then followed by performing comparison between the obtained performance of TopicRank extraction process that did and didn’t utilise cosine similarity at the postprocessing stage. The obtained result shows that the extraction system utilising the TopicRank method managed to obtain the acquisition of performance metrics by the magnitude of value of 0.7 for accuracy, 0.08 for precision, 0.09 for recall, and 0.09 for f-score with the parameter configuration of 5 selected keyphrases which assessed to be optimal compared to 2 other parameter configuration. Furthermore, the extraction that applied the TopicRank methodology but didn’t utilise cosine similarity at the postprocessing stage obtained relatively lower performance metrics values against the optimal potency simulated through the application of cosine similarity at the postprocessing stage. The keyphrase extraction utilising the TopicRank method performed is judged to still be improvable in order to maximise the potency of the extraction performance.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Ekstraksi Frasa Kunci, Pemeringkatan Berbasis Grafik, TopicRank |
Subjects: | Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. Q Science > Q Science (General) > Q350-390 Information theory |
Divisions: | 09-Faculty of Computer Science > 55201-Informatics (S1) |
Depositing User: | Muhammad Raihan Almenata |
Date Deposited: | 21 Jul 2023 02:49 |
Last Modified: | 21 Jul 2023 02:49 |
URI: | http://repository.unsri.ac.id/id/eprint/119279 |
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